research paper on health care policy

Volume 20 Supplement 2

The Physician and Professionalism Today: Challenges to and strategies for ethical professional medical practice

• Open Access
• Published: 09 December 2020

Objectives, methods, and results in critical health systems and policy research: evaluating the healthcare market

• Jean-Pierre Unger 1 ,
• Ingrid Morales 2 &
• Pierre De Paepe 1  

BMC Health Services Research volume  20 , Article number:  1072 ( 2020 ) Cite this article

6455 Accesses

3 Citations

Metrics details

Since the 1980s, markets have turned increasingly to intangible goods – healthcare, education, the arts, and justice. Over 40 years, the authors investigated healthcare commoditisation to produce policy knowledge relevant to patients, physicians, health professionals, and taxpayers. This paper revisits their objectives, methods, and results to enlighten healthcare policy design and research.

This paper meta-analyses the authors’ research that evaluated the markets impact on healthcare and professional culture and investigated how they influenced patients’ timely access to quality care and physicians’ working conditions. Based on these findings, they explored the political economic of healthcare.

In low-income countries the analysed research showed that, through loans and cooperation, multilateral agencies restricted the function of public services to disease control, with subsequent catastrophic reductions in access to care, health de-medicalisation, increased avoidable mortality, and failure to attain the narrow MDGs in Africa.

The pro-market reforms enacted in middle-income countries entailed the purchaser-provider split, privatisation of healthcare pre-financing, and government contracting of health finance management to private insurance companies. To establish the materiality of a cause-and-effect relationship, the authors compared the efficiency of Latin American national health systems according to whether or not they were pro-market and complied with international policy standards.

While pro-market health economists acknowledge that no market can offer equitable access to healthcare without effective regulation and control, the authors showed that both regulation and control were severely constrained in Asia by governance and medical secrecy issues.

In high-income countries they questioned the interest for population health of healthcare insurance companies, whilst comparing access to care and health expenditures in the European Union vs. the U.S., the Netherlands, and Switzerland. They demonstrated that commoditising healthcare increases mortality and suffering amenable to care considerably and carries professional, cultural, and ethical risks for doctors and health professionals. Pro-market policies systems cause health systems inefficiency, inequity in access to care and strain professionals’ ethics.

Policy research methodologies benefit from being inductive, as health services and systems evaluations, and population health studies are prerequisites to challenge official discourse and to explore the historical, economic, sociocultural, and political determinants of public policies.

Since the 1980s, markets have turned increasingly to intangible goods – health care, education, arts, and justice. Political changes have accompanied the transformation of health systems. After World War II, the WHO was founded to counter the health effects of devastating destruction, but over the last decades its funding by the World Health Assembly dropped to 25% of its budget. Foundations and industrial countries funded the rest, that is, their preferred programmes. The 1978 Alma Ata Declaration establishing the Primary Health Care policy had resulted from able WHO leadership and a growing social movement demanding health for all. One year later, the Selective Primary Health Care movement promoted by the Rockefeller Foundation undermined its foundations. It led the international policy exclusively to support disease control programmes in LMICs and to turn their first-line health services into epidemiological units allegedly because comprehensive primary health care was costly.

After the collapse of the “socialist” camp in 1989, the Washington Consensus, WB, and IMF conditioned low-interest loans on moves to market economy and government withdrawal from health care provision and financing. Since the 2000s, governments in industrialized countries and their private sector set up international disease control programmes called Global Health Initiatives. These were actually epidemiological public-private partnerships that replaced international cooperation in the health sector.

With the Millennium Development Goals (MDGs) and subsequent Sustainable Development Goals (SDGs), the United Nations set quite unambitious global health goals. They assigned donor-driven targets to LMIC governments, that is, controlling a limited number of pathologies, first transmissible and then increasingly chronic ones.

Over this period the authors evaluated pro-market reforms and policies and identified their determinants through the lenses of patients, physicians and health professionals, and taxpayers. Patients are concerned about accessibility to healthcare services and the price and quality of care. Physicians’ interests are, or should also be, their problem-solving capacity, professional freedom, intellectual progress, medical ethics, work environment, and income. These were the authors’ yardsticks to assess health systems and conduct policy research. These studies thus covered curative medicine, preventive medical care, and medical education but not the important field of inter-sectoral public health policies.

It all started in 1982, when J.-P. Unger discovered in Boston the Rockefeller Foundation’s long-term strategy to commoditise healthcare financing worldwide. In investigating the health marketisation motives of the “Selective Primary Healthcare” strategy in low- and middle-income countries (LMICs), he interviewed J. Walsh and K. Warren, the authors of a publication released just 1 year after the Alma Ata conference that advocated an alternative to the Primary Healthcare strategy called “selective primary healthcare” [ 1 ]. Their message was that the Primary Healthcare Strategy endorsed by the World Health Assembly in Alma Ata in 1978 was unaffordable. Instead, the Rockefeller Foundation promoted a policy that would turn low-income countries’ (LICs) public health systems into structures fit to host disease control programmes – “like Christmas ornaments festooning a Christmas tree” – rather than delivering individual health care. A field experiment in Deschapelles, Haiti [ 2 ], was a central piece of evidence supporting this strategy to make LIC health centres in public services mere disease control structures. The scenario pushed by the Rockefeller Foundation eventually came to be in LICs in the 1980s, albeit with major variants.

In 1986, we invalidated the efficiency alibi of this strategy. As an answer to the Rockefeller strategy, an action research project covering 180,000 persons in Kasongo, Congo [ 3 ] (then Zaire), enabled us to show that the cost of delivering individual health care and a few disease control and other public health interventions under a single administration could be similar to those of first-line services providing just five disease control programmes, because the former solution made it possible to keep its administration simple [ 4 ]. That prompted us to study the economic motives and public health consequences of healthcare insurance commercialisation, healthcare commoditisation, and health service privatisation and to build a case with coordinated studies. This paper meta-analyses the objectives, methods, and results of evaluations and research into market based health systems and policies spanning over 35 years ( https://pure.itg.be/en/persons/jeanpierre-unger(92d91a56-f267-4b85-82e7-9e4f8a8cffed).html ). Specifically, it aims to make sense of an array of policy studies that all relied on the same medical and public health ethical criteria already formulated in 1972 [ 5 ]; and to delineate health policy research standards relevant to physicians, health professionals, and patients’ representatives committed to the human right to health, i.e., the right to access professional care in universal health systems [ 6 ].

Research strategy

On the grounds of the Kasongo experience and aforementioned Walsh and Warren interview, we formulated in 1983 the overarching hypothesis of our decades-long policy research: Pro-market reforms of healthcare financing and management expand the healthcare delivery and disease control market to the detriment of patients, populations, doctors, health professionals, and taxpayers.

To confirm or overturn this hypothesis, we tested four secondary hypotheses and tried to show a causal relationship between pro-market policies’ characteristics and the following phenomena:

Regarding the access of patients and persons with health risks to professionally delivered healthcare, we tried to verify whether the market tended to allocate individual, “discretional” health care to the rich and public health interventions to the poor, thereby reducing the general population’s access to care significantly.

Regarding disease control, we checked whether public health programmes often failed because the market assigned them a vertical structure to be better suited to absorbing medical equipment and pharmaceuticals with public financing.

Regarding fiscal justice, we strove to determine whether health markets ran counter to social justice in health as they precluded the efficient and equitable use of taxes in the care sector.

About professionals’ ethics and personal development, we aimed to verify if care commoditisation was compatible with the physician’s reliance on professional ethics and investments in medical equipment and pharmaceuticals might antagonise the conditions of doctors’ and teams professional development.

This paper meta-analyses the authors’ research evaluating the impact of markets on health care and professional culture and investigating how they influenced patients’ timely access to quality care and physicians’ working conditions. Based on these findings, they explored the political economy of health care. However, there was no early design of a long-term research strategy. They conducted the studies according to opportunities, although some principles were adopted from the start:

Interdisciplinarity

Testing the above hypotheses required ad hoc, interdisciplinary research methods in order to build a good case for a causal relationship.

Heterogeneous research setting

The hypotheses had to be tested in a large array of health systems, from low- to high-income countries. To allow generalisations about the healthcare environment, countries and regions would be key policy analysis units.

Inductive reasoning

Historical studies would be based on public health evaluation of healthcare systems. Interpreting policy decisions critically required previous ex-post demonstration of ill-functioning services.

The authors approached qualitative research in medical care and public health policies by making use of the concept of praxeology that Bourdieu developed and adapted to sociology in his “Outline of a Theory of Practice.” [ 7 ] They took this approach because both medicine and public health, like sociology research, are combinations of practice and theory [ 8 ]. They believed that the failure to connect them was a frequent weakness of contemporary medical and public health research. An important aspect of praxeology is inductive reasoning. It builds on and evaluates propositions that are abstractions of observations of individual instances of members of the same class. In this regard, the policy evaluations were problem-based and relied on paradoxical observations of care delivery and health service management. They were the raw material of the research and prerequisites for assessing health systems and policies and then exploring the social, political, and economic determinants of faulty ones. Figure 1 depicts the inductive chain generally used in these policy analyses.

Sequencing the authors’ research on (inter-)national health policies

Deconstruction of the policy discourse

Deconstruction is a form of critical analysis concerned with the relationship between text and meaning. Jacques Derrida’s 1967 work on grammatology introduced the majority of its influential concepts. The authors set out to deconstruct public policies with qualitative, interpretative research and nested probabilistic studies. Their goal in this respect was to verify the evidence sustaining pro-market reforms in LMIC and high-income country (HIC) settings; based on these findings, expose their practical, political economy rationale; and then tentatively deconstruct the pro-market discourse of multilateral agencies and commercial organisations. Case studies of national healthcare policies and disease control programmes would provide the material required to analyse international policies and national health sector reforms [ 9 ].

Explicit research values

The authors made explicit their ethical values of social justice and medical professionalism because research methodology, policy evaluation, and interpretation depend on social, economic, and professional standards. These values, published elsewhere, were conceived of for healthcare delivery, management, planning, financing, and disease control. In particular, the authors relied on three healthcare standards with policy implications formulated in 1971, namely, holistic (biopsychosocial and patient-centred), continuous, and integrated care [ 5 ]. In Belgium, they served as an ideology to cement alliances of professionals concerned about quality and equitable access to care for more than 40 years [ 10 , 11 ]. The authors also relied on another key standard of medical practice, the Hippocratic “self-effacement” tenet (“Into whatsoever houses I enter, I will enter to help the sick, and I will abstain from all intentional wrong-doing and harm”) that is expected to deter physicians from making self-interested clinical decisions and maximising their profits with ad hoc clinical decisions, i.e., practising commercial medicine.

Evaluating disease control programmes, the hub of international and national health policies in LICs

By 2015, Africa still had not attained the modest MDGs in health. In 2007, we reviewed the grey literature issued by the main multilateral agencies active in the LIC health sector. Under the aegis of the MDGs, disease control was the conceptual and operational hub of health system reform in LICs. Our review revealed that over the preceding 25 years, virtually all the multilateral agencies active in the health sector had adopted policies restricting the function of LICs’ public services to disease control, thereby allocating individual healthcare delivery to commercial services (and private, non-profit facilities where they existed) [ 12 ].

To convince physicians and policy makers in LICs to adhere to sectoral reforms and to replace individual care delivery by disease control in public services, the Bretton Wood agencies attached conditions to their loans and projects and financed a host of local experts to produce the “scientific” justifications of this policy.

For LIC populations, the avoidable mortality, suffering, and anxiety that followed the loss of access to individual care proved immense. In Africa, virtually none of the MDGs were attained, regardless of their limited scope, precisely because in failing to deliver individual healthcare, African public services could no longer implement disease control initiatives satisfactorily.

To explain why a huge financial effort (AIDS control funds, for instance, were multiplied twentyfold between 1997 and 2007) could not achieve the MDGs in Africa, the authors

showed mathematically that successful disease control programmes required health facilities to be used by patients with various symptoms, as they represented the pool of users that these programmes needed for early case detection and follow-up [ 15 ].

studied the mechanisms whereby integrated disease control interventions hampered access to care in the services in which they were integrated and so undermined public services. Although a few AIDS and under-five programmes had been known to deliver bio-psychosocial care, disease control programmes in Africa have reduced the problem-solving capacities of health services; shrunk the professional identity and skills of physicians and nurses; reduced access to drugs to those managed by Global Health Initiatives; and limited in-service training to collective care delivery [ 16 ].

showed this to be a “catch 22” situation, with disease control programmes drastically reducing the number of users in the (public service) facilities where such programmes were implemented [ 17 ].

analysed the evidence of pro-market policies for other characteristics, such as equitable access to quality health care; mismatch of commercial healthcare delivery with medical ethics [ 18 ]; the inability of public services focusing on disease control to respond to people’s demands for individual care, thus preventing community participation; and undue restrictions on professional autonomy in health services designed as “machine bureaucracies.” [ 19 ]

The authors concluded that Hypothesis 2 was plausible because of the following:

Disease control-based reforms strained access to care in LICs without achieving their alleged epidemiological goals.

Replacing individual health care by disease control interventions in LIC public services could be the real motive of the related (inter-)national policies. This was because these reforms practically, albeit tacitly, ushered in a situation in which competition between public and private providers in delivering individual care was made impossible. Multinationals linked to charities that were focusing LMIC public services on disease control took advantage of the disappearance of publicly delivered health care to sell medical care to LMIC middle and upper classes without having to face public sector competition. International disease control programmes not only permitted the use of cooperation funds to purchase drugs and medical equipment manufactured by HIC industries, so fomenting aid-dependent pharmaceutical markets in LICs, but were also structured to foster the healthcare market in urban settings.

How do health-financing markets perform in middle-income countries? Comparing Latin American national healthcare policies and evaluating healthcare regulation in Asia

In MICs, pro-market health system reforms focused on national health care financing. Starting in Chile in the 1980s (under a military government) and in Colombia in 1993 (under an authoritarian government), the privatisation of health financing in Latin America occurred in virtually every country, even those with “socialist” governments. The two exceptions that did not undergo market reforms, Costa Rica [ 20 ] and Cuba [ 21 ], were performance outliers. However, the reform scenarios and organisation of health systems were not identical across the continent. Schematically, Insurance companies made profits whilst managing government funds, capturing the health expenditures of the healthy and wealthy middle class, and employing or contracting physicians. The political economics of health sector reforms in MICs consisted of variable combinations of

under-financing public services;

unduly favouring investments in public services over their recurrent operating costs;

putting the physicians working for publicly-oriented institutions under economic and workload stress;

separating purchasers and providers by law so as to create a niche for commercial insurance banks;

allowing commercial entities to manage public funds and possibly making this scheme mandatory;

privatising public hospitals or imposing commercial competition rules on them (the so-called “management property split”) and on contracted, self-employed physicians, too;

stimulating private financing of public hospitals (“private finance initiatives”);

limiting public services’ activities to unprofitable care, e.g., for the poor (Medicaid) and the elderly (Medicare) in HICs, and to disease control programmes in LMICs; and

liberalising investments in health care under the aegis of international trade treaties.

Given the many cultural and political similarities across Latin American countries, their health systems offered a good setting to explore strategic variants of care commoditisation. The authors assessed primarily the effects of pro-market reforms in Latin America by comparing the performance of systems abiding by international (World Bank, International Monetary Fund, Inter-American Development Bank, etc.) health policies with those that did not [ 9 ]. They thus studied the histories and functioning of some national health systems and the impact of financing options on their management, care quality, and access to care. To study health systems’ productivity, they relied on aggregated production data, population-based care accessibility and continuity rates and ratios; direct observations in healthcare services and administration; and interviews of patients, physicians, health professionals, policy makers, and public health experts.

They studied the health care and outcomes of large-scale, nationwide, in vivo experiments of care commoditisation. The ones they studied did not show any benefits for patients, physicians, health professionals, and/or public finances:

Colombia, which had been a good student, by international standards, since 1993, had a deplorable health record [ 22 ]. In our interviews we studied and compared the barriers to access to care erected in Colombia by a managed competition model with the barriers in north-eastern Brazil, where public services were severely under-financed [ 23 , 24 ]. As expected, both had very poor results.

In 2006, Chile’s public services [ 25 ], which had survived the dictatorship, covered 84% of the population with half of the country’s health expenditure. However, with just 50% of the country’s health expenditures, the public services managed to make the country a positive outlier in Latin America on many health indicators. The technical challenge of this study was to relate health system features to indicators of output (utilisation and coverage rates, for instance) and outcome (maternal mortality, for instance).

Finally, in 2001, Costa Rica, with its publicly-oriented healthcare services and financing, had about the same demographic and epidemiological features as the United States, although it spent nine times less per capita on health than the U.S. [ 20 ]

To fuel the legal and institutional dynamics of health insurance privatisation, the WHO and other UN agencies promoted a strategy called “Universal Health Coverage” (UHC) [ 26 ], that is, universal access to health insurance. Its pro-market discourse endorsed the idea that only insured populations could access health care [ 27 ], despite evidence that expanding insurance coverage might reduce service utilisation, e.g., when public-private insurance mixes were supposed to achieve universal coverage of health risks [ 28 , 29 , 30 ] and evidence of the superior effectiveness, fairness, and efficiency of Latin American off-market health systems [ 20 , 21 ].

The findings of these international comparisons led the authors to question the UHC strategy as a way to secure universal access to care. This was not only because public-private mixes in healthcare financing give rise to severe inefficiency in health systems, but because access to care was shown to be highly dependent on non-financial factors (geographical and psychological accessibility of health services, for instance) [ 31 ] otherwise neglected by the UHC strategy and possibly even undermined by it. In the absence of performance-based evidence supporting health-financing marketisation, the hypothesised centrality of an economic agenda in Latin American health reforms became plausible.

In sum, these comparisons of the Chilean, Colombian, Costa Rican, and Brazilian health systems and historical studies of Bolivia and Ecuador support Hypothesis 1 regarding the negative impact of pro-market policies on access to care and quality of care and Hypothesis 3 regarding fiscal injustice and inefficient use of public funds by commercial health services and insurance companies.

In addition, the authors’ studies of Asian health systems showed that the health care market was structurally flawed by the impossibility of regulating and controlling the activities of the private but also public health care sector in MICs properly. Whilst the Rockefeller Foundation had tacitly admitted that without regulation and control, privatising health services could not produce equitable access to care [ 32 ], the authors showed through their observations in nine (maternal health) case studies of regulations in China, India, and Vietnam [ 33 ] and theoretical discussion [ 34 ] that regulation and control of for-profit care delivery were most likely to be ineffectual in the MIC care sector.

In Vietnam, for instance, sex-selective abortion was responsible for a serious gender imbalance in spite of a decade of State regulation and control. Although a regulation against the practice had been passed in 2003 and implemented since 2006, regional disparities in gender-specific birth rates increased between 2006 and 2011. As a “critical incident”, the number of ultrasound violations detected in 2011 had been 1 positive out of 83,192 controls done in the health districts under study. And in 2016, the gender ratio still was 112 females/100 males in Vietnam. Against a background of strong social demand for sex-selective abortion in the middle class, selective abortions remained undetected in spite of the regulation and inspections because of the policy-makers’ failure to allocate sufficient resources to this exercise, weak governance, medical secrecy, conflicts of interests, dual physicians’ employment (in public and private healthcare services), the opacity of the medical market, and difficulties specifying contingency in clinical situations [ 33 ].

This set of nine studies in China, India, and Vietnam thus supports the plausibility of Hypothesis 4, as they confirm the vulnerability of medical ethics to care commoditisation policies when regulation and control of medical practice are ineffectual, which actually they are because of the socio-political and technical characteristics of middle income countries.

Assessing the impact of health markets on access to care in Europe

At the end of World War II, unionised blue-collar workers imposed social protection schemes in health. In a bipolar world, the workers’ organisations took advantage of progressive ideologies that were gathering strong followings in Europe. Whilst the weakened employers’ organisations prevailed upon the Social Democrats and Social Christians to join them in the anti-Communist struggle, they conceded the pillarization of European States. Workers’ trade unions, mutual societies, and political parties entered the parliaments (as was the case before Word War II), but also the State’s executive branches, judiciary, and social and health services, education, the police, and the army. That is how workers’ representatives limited the impact of corruption in State constituencies, i.e., preventing those who had the will and resources from buying the State’s policy and administrative decisions. They locked the sustainability of social security into government structures and secured access to professional health care in universal health systems as a human right. Admittedly, the users of healthcare services paid for this State pillarization with a dose of nepotism and its consequences. Still, European States had acquired key democratic features. Heated negotiations between representatives of social classes with opposing interests produced sectoral priorities within the overarching framework of national health budgets. In Belgium, for instance, this debate was institutionalised in the national social security organisation. Footnote 1

The macroeconomic result of this pillarization of the State can be seen in two inversely proportional numbers that show the importance of risk-pooling and solidarity in European health care financing, namely:

a government share in total health spending that long exceeded 80% and

total health expenditures that were high enough (about US$4000 per capita in 2014, of which approximately 10% was for the commercial sector) to make the publicly-oriented healthcare services Footnote 2 effective but sufficiently modest (10% of European GDP versus 17.1% of U.S. GDP in 2014) to favour economic growth outside the health sector.

That is how employees’ and employers’ taxes and social contributions made it possible to limit household expenditures on health care whilst securing one of the best geographically, financially, psychologically, and technically accessible forms of professional health care. Importantly, these schemes gave physicians sufficient professional autonomy. Access to professional care was equitable thanks to cost-redistributing, non-profit, non-actuarial health care financing and a sufficiently large proportion of non-material investments in the health sector.

With government social security schemes that included fairly comprehensive universal health insurance, Europeans enjoyed a high degree of social protection from 1945 to 1989 in Eastern Europe, until the 2008 financial crisis in Southern Europe, and even later in other countries.

Unfortunately, the institutional pillarization did not prevail at the European Union and Commission level. Rather, European politicians, civil servants, and political parties were the targets of more than 30,000 commercial lobbyists (1.4 per European Commission (EC) civil servant) [ 35 ] working to foster the interests of the international insurance banks that were investing in health, amongst other things. In contradiction to the provisions of the Treaty of Rome [ 36 ], the EC intervened in the Member States’ health care systems by negotiating international trade treaties involving investments in health care that could make healthcare management and medical practice subject to a commercial rationale. In addition, the 3% budget deficit rule that the Maastricht Treaty imposed on Member States gave political parties an opportunity and a plausible reason to cut public expenditures on health until healthcare financing would be sufficiently privatised, as the WB and IMF had done earlier in Latin America.

Public expenditure on health care was severely constrained but once health laws and regulations had been modified, as shown by the history of Dutch, Swiss, and Colombian health systems, insurance banks strove to maximise public and private expenditures on health care and governments found the needed resources through inter-branch arbitration.

In the U.S., where the health market was mature, the wealthy faced more problems accessing health care than the poor in most OECD countries, whilst the U.S. government alone spent more on health per capita than the total (public and private) per capita spending of most European countries [ 37 ]. Nevertheless, over the last 10 years, the number of uninsured Americans varied between 35 and 50 million. Many more were poorly insured. If the U.S. insurance coverage rate were applied to Europe, the number of uninsured Europeans would reach about 75 million. If the European ratio of mortality amenable to care became that of the United States, avoidable mortality would increase by up to 100,000 deaths per year.

In Latin American countries, the same financial structure yielded the same health effects as in the U.S. but, admittedly, not in the Netherlands and Switzerland. The sustainable performance of these two health systems is central to policy debates in Europe and, expectedly, insurance banks praise their functioning, except for one small detail: Since health care financing has been marketed (respectively in 1996 and 2006), the Swiss and Dutch health expenditures have skyrocketed [ 38 ].

What are the reasons to believe that health insurance markets are environments hostile to the universal right to care? The authors evaluated [ 39 ] the performances of the U.S., the Netherlands, and Switzerland, three industrial nations that pursued market-based financing models, with a focus on equity in access to care, care quality, health status, and efficiency. They then assessed the consistency of their findings with those of various research teams. Using secondary data obtained from a semi-structured review of articles from 2000 to 2017, inter alia, they discussed the hypothesis that commercial health care insurance was detrimental to access to professional health care and population health status.

The findings can be summarised as follows:

In 2010, poor Americans had twice the unmet care needs of Americans with above-average incomes and ten times more than the UK poor. The unmet care needs of the rich in the U.S. exceeded those of the poor in several industrial countries [ 40 ]. The number of Dutchmen and -women experiencing financial obstacles to health care quadrupled between 2007 and 2013 [ 41 ]. Switzerland ranked second worst in a 2016 survey of 11 countries, just ahead of the USA, with 22% of Swiss adults likely to skip needed care [ 42 ].

The most negative impacts of “managed care” on care quality were its tight constraints on physicians’ professional autonomy, large reliance on the physicians’ material motivation, the fragmentation of health services, and a tendency to apply evidence-based medicine too rigidly. In requiring strict application of clinical protocols, commercially managed care was less likely to be favourable to care quality than systems giving physicians sufficient freedom to rely on professional decision-making and medical ethics.

The prevalence of burnout amongst MDs made medical practice the riskiest occupation in the United States and one of the riskiest occupations in Europe [ 43 ]. This burnout was not related to insufficient income but to excessive workloads and to perceiving existential threats to their professional identity, ethics, and autonomy in the way health care was organised. This observation supports Hypothesis 4 because these psychological and professional status threats actually result from the commoditisation of care [ 44 ].

Countries with a commercial insurance monopoly generally remained above the maternal, infant, and neonatal mortality rates v. the health-spending regression line [ 45 ]. And the growth rates of health expenditure were the highest in the U.S. and Switzerland, with the Netherlands not far behind [ 46 ].

Controlling for the impact of the obesity confounding factor, these studies reveal that the industrialisation of care contributes to the comparatively poor performance of the U.S., Dutch, and Swiss health systems, with the Dutch first-line services being an exception made possible by the GPs’ medical culture and the low cost to patient.

International trade treaties may further worsen the mortality rates of cardiovascular and cerebrovascular conditions, diabetes, and cancers in Europe, since they favour the food industry’s market penetration [ 47 ].

These findings admittedly conflict with recent influential health system rankings, perhaps because of the ways their health indicators are constructed and a bias towards assessing first-line healthcare services.

In conclusion, the comparison of US, Dutch, and Swiss health systems with the others in Europe supports the validity of Hypotheses 1 and 3. The most inefficient system is where the insurance market has achieved its maximal development, that is, in the U.S. In general, healthcare expenditures rose faster where health insurance was commoditised. The Netherlands and Switzerland reveal that increasing expenditure on health care enables health systems based on commercial insurance to maintain decent access to professionally-delivered health care for a few years.

The sizeably better, much more equitable access to health care in Western Europe (and its demographic and epidemiological superiority over the U.S.) and its much lower cost is generally explained by redistributive laws and regulations (tax-based or mandatory social security) channelled through health care public services or mutual societies that permit solidarity in health care financing.

The analysis of the U.S. health system’s disappointing performance reveals that actuarial management of health finances and the commercial management of health services are responsible for deficient accessibility to care and services. In particular, actuarial management of health care reduces risk pooling and solidarity in health financing between men and women, the young and the elderly, the sick and the well, high and low risks, and rich and poor.

Methodological lessons for descriptive, policy studies

Identifying health services productivity shortfalls and dysfunctional structures

The authors tried to provide patients’ and physicians’ organisations with the evidence and clues about policies from the angle of the human right to care and professional endeavour. Their research assessed the influence of policies on health services’ productivity in defined historical contexts from various standpoints: those of patients (e.g., care quality and accessibility); physicians (e.g., continuing medical education and teamwork); taxpayers (efficiency and equity in use of public monies); and public health specialists (health care and disease control management).

From an inductive study perspective, documenting health services’ structural and functional deficiencies provided the raw material for assessing health systems and possibly challenging policy decisions and official discourse.

To gauge the quality of health care, the authors used medical knowledge to observe clinical practice (sometimes as mock patients) [ 48 ]. For instance, to assess the impact of managed care techniques on care quality in Costa Rica, they sat in on consultations. The research hypotheses had been formulated by the Limon region’s GPs, who suggested that there was a relationship between managed care ( compromisos de gestión ) and the lack of time available for interpersonal communication and deficient care accessibility [ 49 ]. In addition, they collected data on disease-specific indicators to explore the extent to which managed care techniques were responsible for decreasing care quality and data reliability.

To assess care accessibility, they often used the services’ routine production data, with indicators such as population-based utilisation rates of curative care in first-line services and hospital admission rates [ 31 ], referral completion rates, and preventive (vaccination, antenatal clinics, etc.) coverage rates, and then they validated them by triangulation when possible. As a proxy for the financial accessibility of health care, they used “catastrophic health expenditures.” [ 50 ] Routine data proved cheaper, readily available, and a good reflection of the services’ operations in large geographical areas, but the method had limits even when it was combined with data triangulation and controls:

In Colombia, semi-structured interviews of patients and professionals proved indispensable to gauge care accessibility [ 51 , 52 , 53 ] because networks of “sentinel physicians” were not organised to collect service utilisation and epidemiological data; population-based statistics were not available and the denominators would have consisted of populations affiliated with a myriad of health insurers and care providers; and private insurance companies were reluctant to provide data that could undermine their reputations.

The routine data were sometimes biased, such as in the case of a state administration in charge of determining regional maternal mortality rates in Asia. Aside from the technical difficulties of establishing the maternal mortality rate (MMR), middle line managers were likely to be penalised when this indicator was too high but also too low, because in the latter case the administration did not trust the data’s validity [ 33 ]. Hence a regression to the mean …

In general, the authors relied on output indicators rather than on population outcome. However, two demographic indicators proved particularly interesting for critical assessment of healthcare systems:

The Maternal Mortality Rate (MMR) reflects access to the entire healthcare system pyramid [ 54 ], particularly in LMICs [ 55 ] and probably in any situation where it exceeds 40 per thousand. This is in contrast to the Infant Mortality Rate (IMR), which in LICs often mirrors low-cost interventions that may reduce access to care (such as immunisation campaigns) [ 56 ] and biomedical/sociocultural health determinants (such as the availability of food and clean water and women’s education, respectively). Since the lower the per capita GDP, the cheaper and less reliable the demographic indicators used [ 57 ], the authors retained in practice only the gross differences when comparing the health systems’ performances in terms of MMR. In 2010, for instance, Moldova, the poorest country in Europe, had the same MMR as the U.S., despite spending 1/20 as much on health per capita.

In HICs, life expectancy and population mortality rates mirror obesity-associated pathologies but, just as importantly, access to quality health care. Up to 80% of premature deaths in Poland were explained by unsatisfactory access to health care [ 58 ]. According to Kruk and co-workers, 15.6 million excess deaths from 61 conditions occurred in LMIC in 2016. This research compared case fatality between each LMIC with corresponding numbers from 23 high-income reference countries with strong health systems. After excluding deaths that were preventable by public health measures, the authors found that 55% of excess deaths were amenable to health care and could be put down to either the receipt of poor-quality care or the non-utilisation of health care [ 59 ].

To evaluate health systems by the design and performance of their disease control programmes, the authors relied on two models:

An all-purpose disease control model (“ vertical analysis” ), designed by P. Mercenier [ 60 ] to provide standards for the design of disease-specific control programmes. It was based on the systemic representation of the disease-specific syndromes and vector development stages and biomedical and socio-cultural interventions to interrupt the disease chain in the field, from aetiology to patient death.

M. Piot’s model [ 61 ] to assess care continuity for any defined disease. It establishes the disease-specific cure rate as the product of coefficients measuring detection, diagnosis, and treatment activities. As the model reveals the health system characteristics needed to secure, say, early detection and care continuity, they used it to contrast the performances of public and private sectors in tuberculosis control in India [ 62 ] and to evaluate malaria control programmes in Mali and Sub-Saharan Africa in general [ 15 ].

Once health system productivity had been studied, the authors analysed the organisation of health services and systems. For this they relied on managerial models and standards specific to

publicly-minded care management (e.g., concerned with access to professional health care, professional autonomy and well-being, professional ethics, and public health) [ 63 ];

the systemic management of hospital(s) and first-line facilities networks [ 18 ]; and

“divisionalised adhocracy”, an organisation pattern that favours knowledge management and teamwork [ 19 ] and is suited to systems whose end-line producers are highly skilled and sufficiently autonomous professionals (as are physicians) rather than workers and technicians, as assumed by the classic generic management theories.

Studies of health financing and systems characteristics that cause low services productivity

Health system case studies and the existence of large databases in the health sector provided the opportunity to single out natural, quasi-experimental study designs – time series and non-equivalent comparisons – to contrast health systems with and without or before and after pro-market health reforms:

For non-equivalent groups (countries, regions, etc.), the authors compared the performances of national/regional health systems in Latin America compliant with the international policy standards with those of “disobedient” ones [ 9 ] and established a typology of reforms.

With time series, we showed long-standing, substandard performances in the quality, accessibility, and financing of health care (for instance, after the privatisation of health insurance in Colombia).

Time series of health services’ routine data also proved useful to reveal contradictory interactions of health activities in populations. For instance, in the late 1980s, the utilisation of medical consultations decreased steadily in Senegal whilst immunisation campaigns were implemented in health care services [ 64 ]. The challenge of the study consisted in demonstrating a causal relationship between these campaigns and the subsequent sustained deterioration of care accessibility in public services.

Beyond substandard care performances: political economics

Inductive research made it possible to deconstruct official self-apologetic discourses. The authors were then able to seek the real motives for ill-conceived policies whose results belied the stated objectives. Their entry point in the complex socio-cultural and political determinants of health policies was political economics because of the huge weight of health expenditures in the global economy (up to 17% of U.S. GDP and 11.3% of Germany’s GDP) and the political leverage acquired by the economic players. The economic determinism of health care policies was so powerful that these players did not even need to be coordinated to gear health systems towards care markets [ 65 ].

From corruption [ 66 ], political leverage, and lobbying to trade, it takes time for relationships between commercial organisations and public institutions to result in health systems’ structures and new professional practice. Some studies thus adopted an historical viewpoint [ 12 , 65 , 67 , 68 ] to probe the care commoditisation mechanisms. Even in non-profit organisations, the main determinant of poor healthcare accessibility proved to be the business mission of health financing, management, and medical practice.

However, correlations between events, sequences, sociological observations, and relationships between historical times enabled us to identify professional, cultural, and geostrategic determinants of health policies alongside economic ones. The prevailing order was reflected in professional culture thanks to education, information, scientific ideology, and advertising. The resulting personal characteristics, identity, and knowledge of physicians and professionals were the conditions of health systems’ reproducibility. Bourdieu calls these internal features “habitus,” i.e., ways of doing and being, and “representations”.

Since 1985, the trend has been towards the privatisation of health financing, public subsidies for private health care providers, commercial management of health services, and for-profit medical practice, in spite of the wealth of evidence pointing to the risks of large-scale mortality and morbidity and threats to professional ethics associated with the commoditisation of care.

Governments and multilateral agencies ought to be held accountable when health policies cause avoidable mortality and suffering and thus human rights violations, or at least “be shamed”, as Sir Michael Marmot once said. Therefore, with States being fields “structured according to oppositions linked to specific forms of capital” [ 69 ], health system and policy research should not so much address the knowledge needs of policy makers directly as those of physicians, socially-minded professionals, and patients’ organisations that could leverage them. Political indictments on the impact of health policies require these organisations to access the relevant scientific and professional information in order to question and challenge public policies in the health sector.

The studies analysed here stemmed from the human right to access professional care in universal health systems and the knowledge they produced was directed at physicians, health professionals, and patients’ organisations sharing moral values and interested in lobbying health policies. The present meta-analysis sheds light on the requirements of this type of research:

Inductive, multidisciplinary policy research is time-consuming but often a condition to study health policies independently:

International health policies assessments benefit from analysing national healthcare policies and disease control programmes.

National health policies should be studied with political economy and medical concepts, and through the lenses of political science and history, but importantly on the grounds of health systems and services productivity assessment.

Medical concepts, public health models, and indicators of professional care delivery and non-profit health management make it possible to evaluate health systems from a professionally- and socially-driven, problem-based perspective.

Health systems and policy researchers need scientific and professional knowledge. Academics should engage in medical, managerial, and policy-making work alongside their research and teaching activities. Therefore, medical and public health schools should learn to assess the academic’s professional proficiency and ability to derive validated theory from their practice.

Professional ethics should be a criterion for evaluating care quality:

Although values are an obstacle to Weberian axiological neutrality in medical, public health, and education policy studies, they are indispensable to assess care quality, health services, and healthcare systems. From a phenomenological perspective, they ought to be made available to the reader.

Health systems have evolved rapidly over the last three decades. Long-term reliance on the same set of explicit ethical and technical criteria applicable to medical practice and health services organisation is what allows valid conclusions to be drawn from time series and comparative or historical studies of health systems that belong to different eras.

Such studies ought not to be only descriptive and critical but also designed as proposals to improve health systems and policies. Those analysed here reveal many nationwide experiences to improve access to professional care. Some countries (Costa Rica, Cuba, Spain, Sri Lanka, Thailand, and Italy), states (e.g. , Kerala), regions or cities (e.g. Rosario, Argentina), and health systems (Chilean public services) acquired collective knowledge to develop non-commercial care delivery and promote ethical, medical practice. There is no doubt that decades of neoliberal policy have compromised their professional achievements, to the point that they are often no longer perceptible.

Medical journals ought to be devoted to professional practice and not only to science, and be independent and publicly financed. Given the undeclared conflict of interest created by the presence of insurance banks in the shareholding of top impact-factor medical journals, physicians’ and patients’ organisations should lobby public universities to stop relying on the researcher’s bibliometrics and the impact factor to decide on scientists’ careers.

The hypothesis that the authors formulated in 1983 can reasonably be accepted. Health markets most likely undermine patients’ health, physicians and professionals’ status and morale, and taxpayers’ interests. The key function of health sector reforms is not public health but economic: they aim to privatise the profitable part of health care financing; maximise the return on health care with commercial healthcare management of services and for-profit care delivery; prevent public services from being involved in a competition with the private sector for health care delivery, management, and financing; and open markets in LMICs with public aid funds to medical and pharmaceutical goods preferably manufactured in industrialised countries.

The studies analysed here show physicians and their organisations that commercial healthcare financing is incompatible with ethical, medical practice because, with or without vertical integration (in HMOs or PPOs), whether through contracts or wages, it imposes the goal of maximising shareholders’ profits on physicians and health professionals, whereas this commercial mission goes against the grain of Hippocratic ethics.

To patients’ organisations, the studies analysed here prove worldwide that care commercialisation prevents solidarity in healthcare financing and obstructs equal access to care. Markets segment health systems, they foment competition between physicians, whilst cooperation among them is essential to peoples’ health [ 13 ]. Moreover, they use public expenditure on healthcare inefficiently.

This research thus opens avenues for joint political action by patients’ and physicians’ organisations to defend and promote social protection in health because it shows that both doctors and patients benefit from professional care delivery and publicly-oriented care financing and management; the major contemporary threat to care accessibility and quality, namely, the privatisation of health care financing, also jeopardises the physicians’ autonomy, ethics, and incomes.

Finally, this research shows that competition prevails between not only commercial entities but also sectors. The interests of insurance banks investing in health and those of all the other economic actors are contradictory: Inter-country comparisons of total health expenditures reveal that the commodisation of care is accompanied by broad inter-sectoral, macro-economic redistribution. Economic agents that do not invest in health insurances would do better to learn from this.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

Whilst these schemes had been forced upon employers, they unexpectedly proved to be highly favourable to economic growth.

Referring to health services and systems, we use the terms “publicly oriented”, “publicly minded”, “socially driven”, “non commercial”, and “not for profit” interchangeably

Abbreviations

Disability-adjusted life years

European Commission

Global health initiatives

General practitioner

High income countries

Infant mortality rate

Low and middle income countries

Medical doctor

Millennium development goals

Maternal mortality rate

Quality-adjusted life years

Sustainable development goals

Walsh JA, Warren KS. Selective primary healthcare: an interim strategy for disease control in developing countries. N Engl J Med. 1979;301(18):967–74.

Article   CAS   PubMed   Google Scholar  

Berggren WL, Ewbank D, Berggren G. Reduction of mortality in rural Haiti through a primary-health-care program. N Engl J Med. 1981;304:1324–30.

The Kasongo project. Annales belges de médecine tropicale. 1981. 60, suppl.

Google Scholar  

Unger JP, Killingsworth JR. Selective primary healthcare: methods and results. Soc Sci Med. 1986;22:1001–13.

G.E.R.M. Pour une politique de la santé. Bruxelles: La Revue Nouvelle; 1971.

Unger JP, Morales I, De Paepe P, Roland M. Medical heuristics and action-research. Professionalism versus science. Forthcoming as part of BMC Health Services Research Volume 20 Supplement 2, 2020: “ The Physician and Professionalism Today: Challenges to and strategies for ethical professional medical practice ." The full contents of the supplement are available online at https://bmchealthservres.biomedcentral.com/articles/supplements/volume-20-supplement-2 .

Bourdieu P. Esquisse d'une théorie de la pratique. Paris: Les Editions du Seuil; 2000.

Unger JP, De Paepe P, Van Dessel P, Stolkiner A. The production of critical theories in Health Systems Research and Education. An epistemological approach to emancipating public research and education from private interests. Health Cult Soc. 2011;1,1:ISSN 2161–6590. https://doi.org/10.5195/hcs.2011.50 http://hcs.pitt.edu . (online).

Article   Google Scholar  

International Health and Aid Policies. Unger J.P., De Paepe P., Sen S. & Soors W., editors. Cambridge University Press; 2010. Available: http://www.cambridge.org/us/catalogue/catalogue.asp?isbn=9780521174268 . Accessed 13 Sept 2020.

http://www.maisonmedicale.org . Accessed 13 Sept 2020.

http://www.sante-solidarite.be . Accessed 13 Sept 2020.

De Paepe P, Soors W, Unger JP. International aid policy: public disease control and private curative care? Cad Saude Publica. 2007;23(Suppl.2):S273–81.

Article   PubMed   Google Scholar  

Segall M. District health systems in a neoliberal world: a review of five keypolicy areas. Int J Health Plann Manag. 2003;18:S5–S26.

Van der Stuyft P, Unger JP. Improving the performance of health systems: the world health report as go-between for scientific evidence and ideological discourse. Tropical Med Int Health. 2000;5(10):675–7.

Unger JP, d’Alessandro U, De Paepe P, Green A. Can malaria be controlled where basic health services are not used? Tropical Med Int Health. 2006;11(3):314–22.

Unger JP, De Paepe P, Green A. A code of best practice for disease control programs to avoid damaging healthcare services in developing countries. Int J Health Plann Manag. 2003;18:S27–39.

Unger JP, De Paepe P, Ghilbert P, Soors W, Green A. Disintegrated care: the Achilles heel of international health policies. In low and middle income countries. Int J Integr Care. 2006;6:e14.

PubMed   PubMed Central   Google Scholar  

Unger JP, De Paepe P, Ghilbert P, Soors W, Green A. Integrated care: a fresh perspective for international health policies in low and middle-income countries. Int J Integr Care. 2006;6:e15.

Unger JP, Macq J, Bredo F, Boelaert M. Through Mintzberg's glasses: a fresh look at the organisation of ministries of health. Bull World Health Organ. 2000;78(8):1005–14.

CAS   PubMed   PubMed Central   Google Scholar  

Unger JP, De Paepe P, Buitrón R, Soors W. Achievements of a heterodox health policy. Am J Public Health. 2008;98(4):636–43.

Article   PubMed   PubMed Central   Google Scholar  

De Vos P, De Ceukelaire W, Van der Stuyft P. Colombia and Cuba, contrasting models in Latin America’s health sector reform. Tropical Med Int Health. 2006;11(10):1604–12.

De Groote T, De Paepe P, Unger JP. Colombia: in vivo test of health sector privatisation in the developing world. Int J Health Serv. 2005;35(1):125–41.

Vargas I, Vázquez ML, Mogollón-Perez AS, Unger JP. Barriers of access to care in a managed competition model: lessons from Colombia. BMC Health Serv Res. 2010;10(297):1–12.

Garcia-Subirats I, Vargas I, Mogollón-Perez AS, De Paepe P, Ferreira da Silva MR, Unger JP, et al. Inequities in access to healthcare in different health systems. A study in municipalities of central Colombia and north-eastern Brazil. Int J Equity Health. 2014;13(10):1–15.

Unger JP, De Paepe P, Arteaga HO, Solimano CG. Chile’s neoliberal health reform: an assessment and a critique. PLoS Med. 2008;5:4e79:0001–6.

http://www.bmg.bund.de/fileadmin/redaktion/pdf_who/Information_Ministerial_Conference_.pdf . Accessed 22 Apr 2016.

https://oi-files-d8-prod.s3.eu-west-2.amazonaws.com/s3fs-public/file_attachments/bp176-universal-health-coverage-091013-summ-en__1.pdf . Accessed 13 Sept 2020.

Andoh-Adjei FX. Assessing the performance of district mutual health insurance schemes in Ghana. International course in health development 46;2009/2010. Amsterdam: Royal Tropical Institute; 2010.

Guarnizo-Herreño CC, Agudelo C. Equidad de Género en el Acceso a los Servicios de Salud en Colombia. Rev Salud Pública Colomb. 2008;10(Sup1):44–57.

Consorcio de Investigación Economica y Social. Investigaciones sobre salud. 2011. http://www.cies.org.pe/investigaciones/salud .

De Paepe P, Rojas E, Abad L, Van Dessel P, Unger JP. Improving access. In: Unger JP, De Paepe P, Sen K, Soors W, editors. International health and aid policies; the need for alternatives. Cambridge: Cambridge University Press; 2010. p. p210–24.

Chapter   Google Scholar  

Lagomarsino G, Nachuk S, Singh KS. Public stewardship of private providers in mixed health systems. Washington DC: Synthesis from the Rockefeller Foundation. Results for Development Institute; 2009.

Unger J.P., Van Dessel P., Van der Veer C. & Shelmerdine S. Maternal health regulations in Vietnam, India and China. A comparison across case studies and countries. Deliverable 5.1. HESVIC project ‘Health system stewardship and regulation in Vietnam, India and China’. Institute of Tropical Medicine, Antwerp. A project financed by the European Commission. 154 pages. 2012. Available: https://medicinehealth.leeds.ac.uk/downloads/download/122/hesvic_-_comparative_report_d5_1_120713_final . Accessed 13 Sept 2020.

Shuftan C, Unger JP. The Rockefeller Foundation’s public stewardship of private providers in mixed health systems: a point-by-point critique. Soc Med. 2011;6(2):128–36.

The Guardian. 30,000 lobbyists and counting: is Brussels under corporate sway? 2014.

In Article 152 (consolidated, Amsterdam version of the Rome Treaty): “Community action in the field of public health shall fully respect the responsibilities of the Member States for the organisation and delivery of health services and medical care. In particular, measures referred to in paragraph 4(a) shall not affect national provisions on the donation or medical use of organs and blood”.

OECD. Health data set, the Commonwealth Fund, and the 2012 WHO Global Health expenditure database as in Gapminder. 2012.

http://www.oecd.org/els/health-systems/health-data.htm . Accessed 25 Mar 2018.

Unger J-P, De Paepe P. Commercial health care financing: the cause of U.S., Dutch, and Swiss health systems inefficiency? Int J Health Serv. 2019;9(3):431–56 https://doi.org/10.1177/0020731419847113 .

Unmet care needs due to costs in eleven OECD countries by income group. Commonwealth Fund Health Survey. 2010.

Experienced cost-related access problem, 2007 and 2013. The Commonwealth Fund. Interactives and data. 2014. Available: http://www.commonwealthfund.org/interactivesand/international-survey-data .

Osborn R., Squires D., Doty M.M., Sarnak D.O. & Schneider E.C. In new survey of eleven countries, US adults still struggle with access to and affordability of healthcare Health Aff. Published online November 16, 2016.

Shanafelt TD, Boone S, Tan L, et al. Burnout and satisfaction with work-life balance among US physicians relative to the general US population. Arch Intern Med. 2012;172(18):1377–85. https://doi.org/10.1001/archinternmed.2012.3199 .

Unger J-P. Physicians’ burnout (and that of psychologists, nurses, magistrates, researchers, and professors). For a Control Program. Int J Health Serv. 2019; https://doi.org/10.1177/0020731419883525 .

Gapminder data drawn from the OECD’s 2012 and 2018 health data sets. OECD QWIDS through www.gapminder.org .

OECD Health Statistics. 2018 https://stats.oecd.org/Index.aspx?DataSetCode=SHA . Accessed 5 Nov 2020.

Thow AM, Snowdon W, Labonté R, Gleeson D, Stuckler D, Hattersley L, et al. Will the next generation of preferential trade and investment agreements undermine prevention of non communicable diseases? A prospective policy analysis of the trans Pacific partnership agreement. Health Pol. 2015;119:88–96.

Unger J-P, Marchal B, Dugas S, Wuidar MJ, Burdet D, Leemans P, Unger J. Interface flow process audit: using the patient's career as a tracer of quality of care and of system organisation. Int J Integr Care. 2004;4:ISSN 1568–4156 http://www.ijic.org/ .

Soors W, De Paepe P, Unger JP. Management commitments and primary care: another lesson from Costa Rica for the world? Int J Health Serv. 2014;44(2):337–53.

Xu K, Evans DB, Kawabata K, Zeramdini, Klavus J, Murray CJL. Household catastrophic health expenditure: a multicountry analysis. Lancet. 2003;362:111–7.

Vargas I, Unger JP, Mogollon A, Vazquez ML. Effects of managed care mechanisms on access to healthcare: results from a qualitative study in Colombia. Int J Health Plann Manag. 2013;28(1):e13–33.

Garcia-Subirats I, Vargas I, Mogollón AS, De Paepe P, Ferreira da Silva MR, Unger JP, Vázquez ML. Barriers in access to healthcare in countries with different health systems. A cross-sectional study in municipalities of central Colombia and north-eastern Brazil. Soc Sci Med. 2014;106C:204–13.

Vargas I, Mogollón AS, De Paepe P, Ferreira da Silva MR, Unger JP, Vázquez ML. Do existing mechanisms contribute to improvements in care coordination across levels of care in health services networks? Opinions of the health personnel in Colombia and Brazil. BMC Health Serv Res. 2015;15:213. https://doi.org/10.1186/s12913-015-0882-4 .

Filippi V, Ronsmans C, Campbell OMR, Graham WJ, Mills A, Borghi J, et al. Maternal health in poor countries: the broader context and a call for action. Lancet. 2006;368,9546:1535–41.

Unger JP, Van Dessel P, Sen K, De Paepe P. International health policy and stagnating maternal mortality. Is there a causal link? Reprod Health Matters. 2009;17,33:91–104.

Unger JP. Can intensive campaigns dynamise front line health services ? The evaluation of a vaccination campaign in Thiès Medical District, Senegal. Soc Sci Med. 1991;32(3):249–59.

Hogan MC, Foreman KJ, Naghavi M, et al. Maternal mortality for 181 countries, 1980–2008: a systematic analysis of progress towards millennium development goal 5. Lancet. 2010;375(9726):1609–23.

Nolte E, Scholz R, Shkolnikov V, McKee M. The contribution of medical care to changing life expectancy in Germany and Poland. Soc Sci Med. 2002;55(11):1905–21 Available: http://www.demogr.mpg.de/publications/files/1257_1042711497_1_Avoid-Germ-Poland.pdf .

Kruk ME, Gage AD, Joseph NT, Danaei G, García-Saisó S, Salomon JA. Mortality due to low-quality health systems in the universal health coverage era: a systematic analysis of amenable deaths in 137 countries. Lancet. 2018;392:2203–12.

Unger JP, Criel B, Mercenier P. L'approche verticale: une méthodologie d'identification des priorités stratégiques du contrôle des maladies tropicales. In: Van Lerberghe W, de Béthune X, editors. Intégration et recherche Antwerp Institute of Tropical Medicine; 1998. p. 17–43.

Piot MA. A simulation model of case finding and treatment in tuberculosis control programmes. Geneva: WHO; 1967.

Unger JP, De Paepe P, Ghilbert P, Zocchi W, Van Dessel P, Qadeer I, et al. Privatisation (PPM-DOTS) strategy for tuberculosis control: how evidence-based is it? In: Unger JP, De Paepe P, Sen K, Soors W, editors. International health and aid policies; the need for alternatives. Cambridge: Cambridge University Press; 2010. p. 57–66.

Unger J-P, Marchal B, Green A. Quality standards for health care delivery and management in publicly-oriented health services. Int J Health Plann Manag. 2003;18:S79–88.

Unger JP, Mbaye A, Diao M. Can intensive campaigns dynamise front line health services ? The evaluation of a vaccination campaign in Thiès Medical District, Senegal. Soc Sci Med. 1991;32(3):249–59.

De Paepe P, Echeverria RE, Aguilar SE, Unger JP. Ecuador’s silent health reform. Int J Health Serv. 2012;42(2):219–33.

Lewis M. Governance and corruption in public healthcare systems: Center for Global Development. The World Bank; 2006.

Tejerina H, De Paepe P, Closon MC, Van Dessel P, Darras C, Unger JP. Forty years of USAID health cooperation in Bolivia. A lose–lose game? Int J Health Plann Manag. 2014;29(1):90–107.

Tejerina H, De Paepe P, Soors W, Lanza OV, Closon MC, Van Dessel P, Unger JP. Revisiting health policy and the World Bank in Bolivia. Global Soc Policy. 2011;11:22–44 Available: http://gsp.sagepub.com/cgi/content/abstract/11/1/22 .

Bourdieu P. Sur l'État. Cours au Collège de France (1989–1992). Paris: Seuil; 2012.

Download references

Acknowledgements

We are indebted to Professors Charlene Harrington (Department of Social & Behavioral Sciences, University of California San Francisco), Antonio Ugalde (University of Texas at Austin, College of Liberal Arts), and Matt Anderson (Albert Einstein College of Medicine, New York) for their indispensable comments. Gaby Leyden edited the manuscript thoroughly. No error can be attributed to them.

About this supplement

This article has been published as part of BMC Health Services Research Volume 20 Supplement 2, 2020: “The Physician and Professionalism Today: Challenges to and strategies for ethical professional medical practice”. The full contents of the supplement are available online at https://bmchealthservres.biomedcentral.com/articles/supplements/volume-20-supplement-2 .

Publication of the supplement has been funded by the Institute of Tropical Medicine, Antwerp, Belgium.

Author information

Authors and affiliations.

Department of Public Health, Institute of Tropical Medicine, Nationalestraat 155, B-2000, Antwerp, Belgium

Jean-Pierre Unger & Pierre De Paepe

Medical Director, Office de la Naissance et de l’Enfance, French Community of Belgium, Chaussée de Charleroi 95, B-1060, Brussels, Belgium

Ingrid Morales

You can also search for this author in PubMed   Google Scholar

Contributions

The author(s) read and approved the final manuscript.

Corresponding author

Correspondence to Jean-Pierre Unger .

Ethics declarations

Ethics approval and consent to participate.

Not Applicable (this manuscript does not involve human participants, human data or human tissue)

Consent for publication

Not Applicable (this manuscript does not contain any individual person’s data)

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Cite this article.

Unger, JP., Morales, I. & De Paepe, P. Objectives, methods, and results in critical health systems and policy research: evaluating the healthcare market. BMC Health Serv Res 20 (Suppl 2), 1072 (2020). https://doi.org/10.1186/s12913-020-05889-w

Download citation

Published : 09 December 2020

DOI : https://doi.org/10.1186/s12913-020-05889-w

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Health policy
• Health systems research
• Research methodology

BMC Health Services Research

ISSN: 1472-6963

• Submission enquiries: [email protected]
• General enquiries: [email protected]

• Privacy Policy
• Career Connection
• Member Forums

© Copyright 2023 American College of Physicians, Inc. All Rights Reserved. 190 North Independence Mall West, Philadelphia, PA 19106-1572 800-ACP-1915 (800-227-1915) or 215-351-2600

If you are unable to login, please try clearing your cookies . We apologize for the inconvenience.

Current Public Policy Papers

ACP public policy papers summarize and dissect published research and discussion on current issues involving clinical practice, medical education, bioethics, and health care financing and delivery, and make specific recommendations for internal medicine physicians, patients, and policy makers. Read about ACP's public policy development process .

Learn more about where ACP stands on important and timely issues:

Coronavirus Disease 2019 (COVID-19)

Racial health disparities, prejudice and violence, health care reform/access, payment/delivery system reform, health information technology, medicare and medicaid, controlling costs, improving effectiveness, prescription drugs and public health related topics, workforce and physician shortage, acp policy compendium, updated june 2023.

Download an up-to-date summary of ACP's policy positions. 

^ Back to Top

• The Integration of Care for Mental Health, Substance Abuse, and Other Behavioral Health Conditions into Primary Care (August 2015)
• Lesbian, Gay, Bisexual, and Transgender Health Disparities (May 2015)
• Full Paper  
• Full Paper and Issue Brief  
• Assessing the Patient Care Implications of "Concierge" and Other Direct Patient Contracting Practices (November 2015)
• Retail Health Clinics (October 2015)
• Full paper and Issue Brief  
• Full paper  
• Health Information Privacy, Protection, and Use in the Expanding Digital Health Ecosystem (April 2021)
• Policy Recommendations to Guide the Use of Telemedicine in Primary Care Settings (September 2015)
• Clinical Documentation in the 21st Century (January 2015)
• Appendix 1: Playbook
• Principles Supporting Dynamic Clinical Care Teams (September 2013)
• Full Paper and Issue Brief

All rights reserved. Individuals may reproduce all or parts of Public Policy Papers for educational, not-for-profit uses. These papers may not be reproduced for commercial, for-profit use in any form, by any means (electronic, mechanical, xerographic, or other) or held in any information storage or retrieval system without the written permission of the publisher.

For questions about the content of Public Policy Papers, please contact the ACP Division of Governmental Affairs and Public Policy , 25 Massachusetts Ave. NW, Suite 700, Washington, DC 20001-7401. 202-261-4500. To order copies of position papers, please contact us .

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• Advanced Search
• Journal List
• Health Serv Res
• v.47(1 Pt 2); 2012 Feb

From Research to Health Policy Impact

The opportunities for researchers to improve health and health care by contributing to the formulation and implementation of policy are almost unlimited. Indeed, the availability of these opportunities is a tribute to a generation of health services researchers questioning existing policies or studying essential “Why?” and “What if?” questions using rigorous analysis. Moreover, the steady albeit uneven transition of health care delivery from a paper-based cottage industry toward an enterprise that provides transparent information to clinicians, patients, policy makers and the public, and potentially vast amounts of data to policy researchers, combined with the expectations of an increasingly information-savvy public, have increased the focus on health care quality, access, and costs.

Our health care system, like those in other countries, confronts continued pressures from increasing costs; inconsistent quality; avoidable patient harms; pervasive disparities in health and health care associated with individual characteristics such as race, ethnicity, income, education and geography; and poor population health outcomes. The persistence of many of these challenges reflects, in part, a failure of science alone to improve heath. Strategies to address many of these challenges exist in the laboratory, but the contribution of this science to the health of the public is limited by a research enterprise that values discovery of new knowledge far more than its successful application.

The Robert Wood Johnson Foundation (RWJF) Clinical Scholars Program, now approaching its 40th birthday, was designed to create “change agents” for the U.S. health care system by training physicians interested in creating and applying innovative research or other approaches to address important societal health challenges. Prior scholars have received advanced training in fields from anthropology and history to business administration. Alumni of the program have served in major leadership roles in both public (federal and state governments, health departments) and private (health systems, business, nonprofit organizations, medical professional organizations) sector organizations for many years. This unprecedented long-term investment in human capital has yielded leaders who have made a tangible difference in health policy. Those leaders have forged new paths that blend clinical training and expertise with science-informed policy development and implementation, whether in academia, government, or the private or nonprofit sectors.

This commentary, by authors now directly engaged in policy, describes the ways that research influences policy and offers reflections on the culture and imperatives of a policy environment.

Examples of How Research Informs Policy

On the surface, health services researchers and policy makers often seem locked in an unrequited love affair. Each seeks the attention and respect of the other and each is endlessly frustrated. Beneath the surface, however, the relationship is more successful than it appears. Almost all recent developments in health policy—from the conceptualization of accountable care organizations to the structure of health insurance expansions—are rooted in policy-informed research, because researchers increasingly recognize the importance of applying their energies to policy-relevant questions.

Health services researchers can influence policy making in four ways. They can identify critical problems, research the benefits and harms of policy solutions, estimate the costs and consequences of policy proposals, and actively participate in the policy process to aid real-time decision making.

The role of research in informing policy begins by defining the contours of a problem. For example, physicians and hospitals have always made mistakes. Iatrogenic injury has been recognized since the time of Hippocrates. Highly publicized incidents, media attention, and public advocacy drew attention to these mistakes. But research, such as the analyses of hospital records in New York, Colorado, and Utah, which has illuminated how frequently errors occur, persuaded policy makers that the problem deserved more than sympathy and hand-wringing ( Brennan et al. 1991 ; Thomas et al. 2000 ). Advocates and media used these estimates, suitably crafted to be clear to a nonspecialist audience, to make their case that policy was needed. This is a slow process—it took nearly two decades between the time Brennan et al. published the Harvard Medical Practice Study and the time that serious policy inroads were made to address medical errors.

Identifying problems is a critical, but also dangerous step in policy making. Policy makers, faced with compelling narratives of human suffering, are reluctant to just sit there and not do something, even when it is not at all clear what the something ought to be. Policy analysis can identify the potential strengths and weaknesses of policy options, but good decision making requires an understanding not only of what might happen, but of what is most likely. Health services research, through studies of small-scale natural or controlled experiments, is critical to advancing from a problem toward a solution. For example, careful studies of insurance plans that implemented value-based insurance design persuaded policy makers to incorporate these designs into the Affordable Care Act ( Fendrick et al. 2001 ; Chernew, Rosen, and Fendrick 2007 ). Policy solutions, such as value-based insurance design, are more likely to penetrate the policy making process if their logic can be explained easily (say in an elevator), if the empirical design of studies is straightforward enough to be understood by nonspecialist staffers, and if practitioners and patients can provide compelling narratives of these projects in operation. Research on policy solutions can influence the policy process more quickly than research that identifies problems. However, researchers are rarely successful alone and can benefit from collaboration with deft communicators and advocates to help make their case in language the public and policy makers understand. Nevertheless, researchers should expect a good decade's delay even if the problem is clearly important.

A third venue for research to affect policy is in the budget. Estimates of the budget agencies—the Congressional Budget Office and the Office of Management Budget—of the costs and consequences of legislative proposals often determine their fate. The budget estimators ground their estimates in the published literature, often directly citing publications in their documentation. Budget estimators seek research that is rigorous and highly specific to the problem at hand and expert estimators are usually aware of the latest findings. For example, the Congressional Budget Office's estimates of the costs of mental health parity in 2007, which were instrumental in passage of the Mental Health Parity and Addiction Equity Act of 2008 (PL110-343), relied heavily on a study of parity in the Federal Employee Health Benefits plan, published just a year before the budget estimate ( Goldman et al. 2006 ; Congressional Budget Office 2007 ). The key to influencing policy in this way is keeping a close watch on the policy process and choosing appropriately salient areas of research.

A fourth place where researchers can influence policy making is in the implementation of legislation or development of other policies. Policy implementation happens in real time, addresses problems that have often not been studied before, and continually balances competing interests. Researchers can rarely affect implementation decisions by publishing papers. There just is not enough time and, by design, the data to evaluate a brand new program generally do not exist. But researchers who actively participate in the policy process, such as RWJF Clinical Scholars and Policy Fellows visiting in administrative departments, can bring their research and clinical experience to bear in this real-time decision making.

Career Paths—Academia to Policy Environment

Influencing policy requires a different approach than academia for health services researchers, like the integrative approach of the RWJF Clinical Scholars. The most immediately familiar path for scholars is one based in academia. Researchers have created and refined the multidisciplinary field of health services research, and focus on issues that are highly relevant to addressing the challenges confronting health care today. In today's economic climate the challenges of obtaining external support for research can be daunting, but the requirements and milestones, that is, funding, publications, and promotion, are quite clear. At the same time, the culture and imperatives of academic life can be strikingly different from those of a policy environment. Where academia rewards scholarly productivity and teaching, often allows schedule flexibility, and values extensive debate, most policy positions offer the potential of influencing decisions that affect the lives of millions, guarantee unpredictable events and interruptions, and often have an excruciatingly short time frame for summarizing and applying scientific knowledge to the decision at hand. To be valuable to policy makers, researchers have to move beyond their scholarly cautions and calls for further research. Policy makers have to be convinced that a proposed intervention will work—in the real world. Assessing the latter dimension requires clear understanding of program operations and constraints, that is, the context for implementation. For example, the appeal of value-based benefit design (see article by Fendrick and others in this issue) is undeniable. Its immediate application must be shaped by an understanding of current payment systems and the capacity to persuade policy makers that this approach won't create immeasurable administrative burden or other unintended consequences. Academic researchers are frequently consulted on specific issues by policy makers, but the opportunity to contribute usually comes with short, inflexible (and often unpredictable) time frames.

Academic researchers yearning for impact often arrange intermittent, temporary stints working directly in policy. Indeed, all three authors have taken full advantage of bringing in visiting scholars, including clinical scholars and health policy fellows, for anywhere from 3 months to 2 years or more. This arrangement has the advantage of minimizing the cultural or social distance between research and policy, and offers the benefits of immersion in the constraints inherent in the application of research to decision making. This approach has also resulted in meaningful policy development. For example, clinical scholars have contributed to the development of strategies to use social media in preparedness and response ( Merchant, Elmer, and Lurie 2011 ), and contributed to the development of a strategic plan for the Emergency Care Coordination Center within the Office of the Assistant Secretary for Preparedness and Response, Department of Health and Human Services (HHS). Health policy fellows who joined the Agency for Healthcare Research and Quality (AHRQ) went on to lead important programs in health information technology and enhance the health care system's role in public health emergency preparedness. Fellows working in the HHS Office of the Assistant Secretary for Planning and Evaluation (ASPE) recently have contributed to research on child health insurance expansions and to the development of workforce policy in the Department. The relationships developed on the job may provide a platform from which future opportunities for researchers to advise policy makers emerge. For example, a clinical scholar working at AHRQ and ASPE as a White House Fellow now leads major quality improvement efforts at the Centers for Medicare & Medicaid Services, following a brief return to academia. Notwithstanding advances in information and communication technology, “immersion” of researchers in a policy environment requires geographic proximity for a period of time; advising may not, particularly after relationships with policy makers have been established.

Other researchers may identify change agents not directly involved in making policy, whose efforts can benefit from their work, ranging from medical professional organizations to nonprofit organizations. For example, federal agencies frequently call on external groups to identify individuals with specific expertise to participate in expert or advisory panels who may influence policy options. Collaborating with colleagues in think tanks, accreditation organizations, or similar entities is an alternative model. Identifying and seizing opportunities to testify or work with groups focused on state or local issues in one's area of expertise is another course. Of note, many researchers, including the three of us, transition between these options during their careers. Since U.S. health care is by definition a mix of public and private financing and delivery, leaders in the private sector are frequently consulted about policy options. In addition to health care systems, employers in businesses far removed from health care play an important role in influencing and implementing health policies.

The context and temporal requirements of health policy are two main challenges facing the health services researcher aiming to influence policy with relevant evidence. One implicit assumption of a pure academic model to informing policy is that proximity to policy making risks biasing or even “politicizing” science, so research that is conducted at a safe distance remains objective. A more practical premise recognizes that change in health and health care requires policy development and implementation, and that that implementation occurs in a context that is shaped by Americans’ beliefs, concerns and ultimately, votes ( Blendon and Benson 2001 ). In addition, moving from research to implementation is not possible in any sphere without explicitly understanding the context and landscape in which research is to be applied. Everett Rogers’ work on diffusion of innovation clearly articulates the critical need for work that clarifies the interaction between an intervention and context, including assessing how the intervention is modified as a result ( Rogers 2003 ).

There are also striking differences in the temporal requirements of policy. While a number of policy-relevant, peer-reviewed journals have accelerated paths for publishing papers that address a timely issue, application of research findings and skills to policy often occurs at an even more rapid pace. Policy windows are often brief and unpredictable, and do not wait for reviewers’ comments to come in. For example, when the H1N1 epidemic arrived in 2009, information regarding its likely impact was imperfect, existing data systems were far from ideal, and many people were frightened. Immediate decisions had to be made with the best possible information, and innovative approaches to tracking real-time impact put in place quickly. That said, subsequent evaluations of some of these systems provide the opportunity to improve future responses.

An essential component of the daily work of health services researchers is communicating scientific findings to colleagues and decision makers from very different backgrounds. This is often enhanced by consulting academic colleagues and external stakeholders, similar to the skills now emphasized in the current RWJF Clinical Scholars Program working with communities.

Research does and should influence policy. But simply producing rigorous and precise results about important problems is not enough to make it happen. Instead, just as policy research must be informed by a knowledge of the institutional context, policy researchers are much more likely to contribute to the policy process if they understand the context in which they are working. Clinical scholars, who spend time deeply engaged both with policy problems and the policy process, are an excellent example of this contextual immersion.

• Blendon RJ, Benson JM. “American's Views on Health Policy: A Fifty-Year Historical Perspective” Health Affairs. 2001; 20 (2):33–46. [ PubMed ] [ Google Scholar ]
• Brennan TA, Leape LL, Laird NM, Hebert L, Localio AR, Lawthers AG, Newhouse JP, Weiler PC, Hiatt HH. “Incidence of Adverse Events and Negligence in Hospitalized Patients. Results of the Harvard Medical Practice Study” New England Journal of Medicine. 1991; 324 :370–6. [ PubMed ] [ Google Scholar ]
• Chernew ME, Rosen AB, Fendrick AM. “Value-Based Insurance Design” Health Affairs. 2007 Epub ahead of print January 2007, doi: 10.1377/hlthaff.26.2.w195 . [ PubMed ] [ Google Scholar ]
• Congressional Budget Office. 2007. Available at: http://www.cbo.gov/ftpdocs/78xx/doc7894/s558.pdf .
• Fendrick AM, Smith DG, Chernew ME, Shah SN. “A Benefit-Based Copay for Prescription Drugs: Patient Contribution Based on Total Benefits, not Drug Acquisition Cost” American Journal of Managed Care. 2001; 7 (9):861–7. [ PubMed ] [ Google Scholar ]
• Goldman HH, Frank RG, Burnam MA, Huskamp HA, Ridgely MS, Normand S-L, Young AS, Barry CL, Azzone V, Busch AB, Azrin ST, Moran G, Lichtenstein C, Blasinsky M. “Behavioral Health Insurance Parity for Federal Employees” New England Journal of Medicine. 2006; 354 :1378–86. [ PubMed ] [ Google Scholar ]
• Merchant RM, Elmer S, Lurie N. “Integrating Social Media Into Emergency-Preparedness Efforts” New England Journal of Medicine. 2011; 365 :289–91. [ PubMed ] [ Google Scholar ]
• Rogers EM. Diffusion of Innovations. 5th Edition. New York: Free Press; 2003. [ Google Scholar ]
• Thomas J, Studdert DM, Burstin HR, Orav EJ, Zeena T, Williams EJ, Howard KM, Weiler PC, Brennan TA. “Incidence and Types of Adverse Events and Negligent Care in Utah and Colorado” Medical Care. 2000; 38 (3):261–71. [ PubMed ] [ Google Scholar ]

Featured Clinical Reviews

• Glaucoma in Adults—Screening, Diagnosis, and Management: A Review JAMA Review January 12, 2021
• Diagnosis and Treatment of Alcohol-Associated Liver Disease: A Review JAMA Review July 13, 2021

Select Your Interests

Customize your JAMA Network experience by selecting one or more topics from the list below.

• Academic Medicine
• Acid Base, Electrolytes, Fluids
• Allergy and Clinical Immunology
• Anesthesiology
• Anticoagulation
• Art and Images in Psychiatry
• Assisted Reproduction
• Bleeding and Transfusion
• Caring for the Critically Ill Patient
• Challenges in Clinical Electrocardiography
• Climate and Health
• Clinical Challenge
• Clinical Decision Support
• Clinical Implications of Basic Neuroscience
• Clinical Pharmacy and Pharmacology
• Complementary and Alternative Medicine
• Consensus Statements
• Coronavirus (COVID-19)
• Critical Care Medicine
• Cultural Competency
• Dental Medicine
• Dermatology
• Diabetes and Endocrinology
• Diagnostic Test Interpretation
• Drug Development
• Electronic Health Records
• Emergency Medicine
• End of Life
• Environmental Health
• Equity, Diversity, and Inclusion
• Facial Plastic Surgery
• Gastroenterology and Hepatology
• Genetics and Genomics
• Genomics and Precision Health
• Global Health
• Guide to Statistics and Methods
• Hair Disorders
• Health Care Delivery Models
• Health Care Economics, Insurance, Payment
• Health Care Quality
• Health Care Reform
• Health Care Safety
• Health Care Workforce
• Health Disparities
• Health Inequities
• Health Informatics
• Health Policy
• History of Medicine
• Hypertension
• Images in Neurology
• Implementation Science
• Infectious Diseases
• Innovations in Health Care Delivery
• JAMA Infographic
• Law and Medicine
• Leading Change
• Less is More
• LGBTQIA Medicine
• Lifestyle Behaviors
• Medical Coding
• Medical Devices and Equipment
• Medical Education
• Medical Education and Training
• Medical Journals and Publishing
• Mobile Health and Telemedicine
• Narrative Medicine
• Neuroscience and Psychiatry
• Notable Notes
• Nutrition, Obesity, Exercise
• Obstetrics and Gynecology
• Occupational Health
• Ophthalmology
• Orthopedics
• Otolaryngology
• Pain Medicine
• Pathology and Laboratory Medicine
• Patient Care
• Patient Information
• Performance Improvement
• Performance Measures
• Perioperative Care and Consultation
• Pharmacoeconomics
• Pharmacoepidemiology
• Pharmacogenetics
• Pharmacy and Clinical Pharmacology
• Physical Medicine and Rehabilitation
• Physical Therapy
• Physician Leadership
• Population Health
• Professional Well-being
• Professionalism
• Psychiatry and Behavioral Health
• Public Health
• Pulmonary Medicine
• Regulatory Agencies
• Research, Methods, Statistics
• Resuscitation
• Rheumatology
• Risk Management
• Scientific Discovery and the Future of Medicine
• Shared Decision Making and Communication
• Sleep Medicine
• Sports Medicine
• Stem Cell Transplantation
• Substance Use and Addiction Medicine
• Surgical Innovation
• Surgical Pearls
• Teachable Moment
• Technology and Finance
• The Art of JAMA
• The Arts and Medicine
• The Rational Clinical Examination
• Tobacco and e-Cigarettes
• Translational Medicine
• Trauma and Injury
• Treatment Adherence
• Ultrasonography
• Users' Guide to the Medical Literature
• Vaccination
• Venous Thromboembolism
• Veterans Health
• Women's Health
• Workflow and Process
• Wound Care, Infection, Healing
• Download PDF
• Share Twitter Facebook Email LinkedIn
• Permissions

Health Care Policy After the COVID-19 Pandemic

• 1 Stanford Institute for Economic Policy Research, Stanford University, Stanford, California
• JAMA Forum After COVID-19—Thinking Differently About Running the Health Care System Stuart M. Butler, PhD
• Viewpoint Cognitive Bias and Public Health Policy During the COVID-19 Pandemic Scott D. Halpern, MD, PhD; Robert D. Truog, MD; Franklin G. Miller, PhD

The coronavirus disease 2019 (COVID-19) pandemic will end sooner or later as all pandemics do. Even though the severe acute respiratory syndrome coronavirus 2, like many other viruses, may linger, it will no longer be an existential threat. Neither the reason for the end, nor its timing, is clear now, but it is not too soon to begin discussing postpandemic health care policy.

To simply return to the prepandemic health care system during a presidential election year would be a mistake. This is a time to think more boldly about the future of the US health care system. The health care system is dysfunctional for many individuals in the US; it is too costly, too unequal, and too uncertain in its eligibility and coverage, with an increasing number of uninsured. However, designing and implementing a better health care system will not be easy. In exploring the challenges and difficulties ahead, it is useful to distinguish between those that are primarily technical issues (although these are not exempt from politics) and those that are political obstacles to significant reform.

Technical Issues

The technical issues involve 2 main issues: how to raise the nearly $4 trillion each year to pay for US health care; and how to organize and deliver the care and compensate those who provide it. The experience of other high-income countries indicates that the most efficient and equitable method to finance universal coverage is through a flat tax on consumption, such as a value-added tax, collected from businesses but passed on to consumers via higher prices. 1 An alternative is a retail sales tax, which is more cumbersome and costly to collect than a value-added tax, but makes the connection between the tax and health insurance more apparent to the public.

Those who object to a flat tax (the same rate for everyone) because they think it is not progressive are mistaken. High-income individuals pay more because they consume more, but everyone gets similar health insurance regardless of income. The combination of the tax and the insurance is quite progressive. If it were not, left of center governments in the Organization for Economic Cooperation and Development would not eagerly embrace a value-added tax. In contrast, employment-based insurance sets essentially the same price for any given policy regardless of income. High-income individuals only pay more if they choose a more expensive policy, but that does not help pay for care for low-income or unemployed individuals.

An important goal of health care reform should be to replace the current byzantine system of premiums, taxes, tax exemptions, deductions, subsidies, and out-of-pocket payments with a much simpler system of financing health care. An equally important goal is to replace the current multiplicity of public and private health insurance programs with 1 universal program that covers everyone from birth to death. Because the US health care system is so large, it would probably be necessary to approach these goals in stages. It is important, however, to realize that the complexity of the current system is one of the main reasons it is so costly, with high administrative expenses.

A few countries find it more feasible to achieve universal coverage through compulsory health insurance administered by insurance companies under close regulation and supervision by the government. The intent and effect of such programs is similar to that achieved by tax-supported public insurance. For historical and political reasons, the US might prefer this approach in contrast to a so-called single-payer system. Regardless of approach, universal systems have proven to be the best way to ensure that everyone has access to care without bankrupting individuals or governments. 2

How to raise the money to pay for health care is important and continues to receive attention. But more important are questions about how to organize and deliver care and how to compensate the individuals and organizations that provide it. Answers to these questions could have a substantial effect on how much money must be raised (ie, the cost of care). If US health care spending was at the same per-capita rate as other high-income countries, the total would be $2.7 trillion instead of $3.7 trillion, admittedly it is difficult to reduce health care costs. It is critical that savings be found so that those dollars can be redistributed to provide more effective care to more people. 3

Most health policy experts agree that the prepandemic health care system was inefficient. However, there is no consensus as to what delivery system would be better for the US diversity of health plans. The competition among the plans will have several advantages if the plans follow a few general principles. First, the health plans should be private. Government-run health care would not work well for the US for its entire population. Over the past decade, Medicare has become increasingly privatized, with about 35% of its recipients enrolled in private insurance plans. Second, public insurance would pay for everyone to be enrolled in a health plan of their choice, with open enrollment every year for anyone who wants to change plans. Third, the plans would receive a risk-adjusted capitation fee to compensate plans for the differences in the expected use of enrolled populations.

Capitation reimbursement provides incentives to use resources efficiently, unlike fee-for-service reimbursement that provides incentives for overuse. This is not just a theoretical proposition. The Kaiser Permanente Health Plan has been paid per capita for more than 50 years and has seen its enrollment increase to 12 million patients, one-third more than in the Veterans Health Administration care system. Fourth, within that general framework, each health plan should be free to deploy resources as they deem best. Some plans might want to pay physicians a fixed salary; others might want to have productivity incentives for their physicians. Some plans might choose to deploy many nurse practitioners and physician assistants, others might not. Most plans would probably want to emphasize primary care, reserving specialists and subspecialists for patients who need their attention. The details of this kind of health care system have been published. 2

Most goods and services do not have or require capitation payment because price serves to allocate resources according to the customer’s willingness and ability to pay. Consumers do not knowingly pay more for a good or service than the benefit they expect to get from it. Health insurance changes the dynamic. When insurance is paying the costs of medical services, patients want any care that offers some expected benefit, regardless of cost. Physician-led health plans that receive risk-adjusted capitation payment are in the best position to allocate resources more efficiently and effectively according to judgments about benefits and costs.

Political Obstacles

Changes in the health care system have always been opposed by many. As Machiavelli observed, 4 proposals for a new order face strong opposition from those who benefit from the old order. This group includes high-income patients who prefer a health care system that caters to their interests and values. 5 The prepandemic system allowed direct visits to specialists and subspecialists. It provided quick access to expensive diagnostic technology, surgical interventions, and high-priced new drugs that offered only minor improvement in length or quality of life. It featured hospitals that had patient rooms that were larger and more private than in other countries and that had relatively more intensive care units. The cost of this system, more than $11 000 per person per year, is tolerable for those with high incomes, but oppressive to most individuals in the US and ruinous for many, leading to missed medicines and bankruptcy.

High-income individuals also prefer US health care research that emphasizes product improvement and ignores cost of care. Other countries also engage in product research, but there is a substantial difference when purchasing that product. Those countries have research organizations like England’s National Institute for Health and Care Excellence or other institutional arrangements to compare the benefit of a clinical innovation with its cost. 6 If the innovation is judged to be too costly relative to its benefit, it will not be approved. US laws explicitly prohibit consideration of costs. That approach works well for those with high incomes but not so well for those with average or low incomes. Opposition to change will also come from the manufacturers of drugs, devices, and equipment who have made large profits under the old system, and from some physician specialists who have made large incomes.

Most voters do not have high incomes, but another major obstacle is distrust of the government by many in the general population. In a Pew Research Center survey from 2017, the public was asked to choose between larger government with more services and smaller government with fewer services. Forty-five percent of 5009 respondents chose smaller government. 7 That sentiment may still be true but may change as current events unfold. Proponents of health system reform should think for ways to reduce, if not eliminate opposition. For example, high-income individuals should have the right to access care not covered by the public insurance if they pay for it. Such options are common in England, Israel, and most countries that have universal coverage with public insurance. The manufacturers of drugs, devices, and equipment will not like harder bargaining over price, but they might realize that the alternative would probably be price controls, which increases inefficiency all around.

Distrust of the government is difficult to dispel, but it is possible to do so as President Roosevelt proved with his New Deal reforms in the 1930s. Even though it has seemed that major reform of health care would only occur in the wake of a major war, a depression, or large-scale civil unrest that changed the political balance, it now appears that the COVID-19 pandemic may provide the dynamic for major political change. 8 If that occurs, major health care reform will be more attainable.

Corresponding Author: Victor R. Fuchs, PhD, Stanford Institute for Economic Policy Research, Stanford University, 366 Galvez, Stanford, CA 94305 ( [email protected] ).

Published Online: June 12, 2020. doi: 10.1001/jama.2020.10777

Conflict of Interest Disclosures: None reported.

See More About

Fuchs VR. Health Care Policy After the COVID-19 Pandemic. JAMA. 2020;324(3):233–234. doi:10.1001/jama.2020.10777

Download citation file:

© 2023

Artificial Intelligence Resource Center

Cardiology in JAMA : Read the Latest

Browse and subscribe to JAMA Network podcasts!

Others Also Liked

• Register for email alerts with links to free full-text articles
• Access PDFs of free articles
• Manage your interests
• Save searches and receive search alerts

• Open Access
• Published: 23 September 2014

Health policy – why research it and how: health political science

• Evelyne de Leeuw 1 ,
• Carole Clavier 2 &
• Eric Breton 3  

Health Research Policy and Systems volume  12 , Article number:  55 ( 2014 ) Cite this article

44k Accesses

111 Citations

69 Altmetric

Metrics details

The establishment of policy is key to the implementation of actions for health. We review the nature of policy and the definition and directions of health policy. In doing so, we explicitly cast a health political science gaze on setting parameters for researching policy change for health. A brief overview of core theories of the policy process for health promotion is presented, and illustrated with empirical evidence.

The key arguments are that (a) policy is not an intervention, but drives intervention development and implementation; (b) understanding policy processes and their pertinent theories is pivotal for the potential to influence policy change; (c) those theories and associated empirical work need to recognise the wicked, multi-level, and incremental nature of elements in the process; and, therefore, (d) the public health, health promotion, and education research toolbox should more explicitly embrace health political science insights.

The rigorous application of insights from and theories of the policy process will enhance our understanding of not just how, but also why health policy is structured and implemented the way it is.

Peer Review reports

Background: policy is not an intervention

Systems perspectives on population health development entered research and practice agendas from the early 1980s. Two complementary traditions emerged; McLeroy et al. [ 1 ] consider health behaviour change as the resultant of the complex interaction between behavioural determinants and higher-level environmental and policy conditions. The Ottawa Charter for Health Promotion [ 2 ] emphasises the development of supportive environments, reorientation of health services, and building of health public policy to enable societies making healthier choices the easier choices. Neither tradition has managed to comprehensively shift research focus, nor has it generated evidence of effectiveness from individual behaviourist perspectives to deep insight in the workings of broader social determinants of health.

Yet, the capacity to develop and assess policy processes for health promotion has been appreciated and formalized across jurisdictions. For Europe, the CompHP Core Competencies Framework for Health Promotion Handbook ([ 3 ], p. 1) states that: " A competent workforce that has the necessary knowledge, skills and abilities in translating policy, theory and research into effective action is recognised as being critical to the future growth and development of global health promotion ". Paragraph 5.7 of the Australian Health Promotion Association’s Core Competencies for Health Promotion Practitioners [ 4 ] states that " an entry level health promotion practitioner is able to demonstrate knowledge of: health promotion strategies to promote health—health education, advocacy, lobbying, media campaigns, community development processes, policy development, legislation ". Interestingly, the most detailed listing of policy competencies is provided by the US National Commission for Health Education Credentialing under section ‘7.5 Influence Policy to Promote Health’ [ 5 ], as indicated below.

7.5.1 Use evaluation and research findings in policy analysis;

7.5.2 Identify the significance and implications of health policy for individuals, groups, and communities;

7.5.3 Advocate for health-related policies, regulations, laws, or rules;

7.5.4 Use evidence-based research to develop policies to promote health;

7.5.5 Employ policy and media advocacy techniques to influence decision-makers.

Yet, for many health educators and health promoters ‘policy’ is a critical yet elusive concept [ 6 ]. On the one hand, they recognise public policy as a critical element in shaping the opportunities for the profession and setting the parameters for its effectiveness [ 7 ]. On the other, they consider policy as an abstract construct best left to politicians, or as a distal determinant of health that can be changed following Cartesian heuristics. Those that have attempted the latter and have failed would claim that policy-making is not just abstract but obscure, without any appreciable logic.

Within the health promotion and health education realm the discourse around policy has been obfuscated further by lumping policy change together with ‘environmental’ perspectives on ‘(social) ecological’ approaches for promoting or improving health behaviour [ 8 ]. Most of the North American literature remains implicit and surprisingly limited in defining, describing, or operationalising what such policy change is or encompasses. For instance, Kahn-Marshall and Gallant [ 9 ] carried out a meta-analysis to assess whether there is demonstrable effect of environmental and policy change on workplace health. However, nowhere in the piece they operationalise what precisely constitutes ‘policy change’ (or for that matter, ‘environmental change’) – it appears to be some undefined notion of modification in organisational parameters.

In this paper, we contend that public health experts, health educators, and health promoters would benefit from considering public policy through the lens of political science rather than through the lens of intervention research. The key arguments are (a) that policy is not an intervention, but drives intervention development and implementation; (b) that understanding policy processes and their pertinent theories is pivotal for the potential to influence policy change; (c) that those theories and associated empirical work need to recognise the wicked, multi-level, and incremental nature of elements in the process; and, therefore, (d) that the health promotion and education research toolbox should more explicitly embrace health political science insights.

Health, policy

Although this is not the place to fully review the academic and practice-oriented discourse around the concepts of ‘health’ or ‘policy’, it seems important to delineate a few issues around the use and application of the expression ‘health policy’.

Policy is in itself a fuzzy concept for political science scholars, variably apprehended as " The actions of government and the intentions that determine those actions " [ 10 ], or rather " Anything a government chooses to do or not to do " ([ 11 ], p. 2). Some would simply see policy as ‘The Plan’ or ‘The Law’ [ 6 ]. Richards and Smith say that " ‘Policy’ is a general term used to describe a formal decision or plan of action adopted by an actor … to achieve a particular goal… ‘Public policy’ is a more specific term applied to a formal decision or a plan of action that has been taken by, or has involved, a state organisation " [ 12 ]. De Leeuw [ 13 ], and Breton and De Leeuw [ 14 ], follow a European tradition in political science that specifies public policy as " the expressed intent of government to allocate resources and capacities to resolve an expressly identified issue within a certain timeframe " . The latter clearly distinguishes between the policy issue, its resolution, and the tools or policy instruments that should be dedicated to attaining that resolution.

Health policy is possibly an even fuzzier term. It has been described unequivocally as " policy that aims to impact positively on population health " [ 15 ] and has been framed as equivalent to " healthy public policy " [ 16 ]. Milio [ 17 ], the first to coin the latter term, later developed a glossary in which she states that " Healthy public policies improve the conditions under which people live: secure, safe, adequate, and sustainable livelihoods, lifestyles, and environments, including housing, education, nutrition, information exchange, child care, transportation, and necessary community and personal social and health services. Policy adequacy may be measured by its impact on population health. " More recently, healthy public policies reincarnated as Health in All Policies [ 18 , 19 ]: " a collaborative approach to improving the health of all people by incorporating health considerations into decision-making across sectors and policy areas. " Variations on this theme have been compiled by Rudolph et al. [ 19 ].

HiAP conceptualisations (Appendix, Rudolph et al., 2013) [ 19 ]

" Health in All Policies is a collaborative approach that integrates and articulates health considerations into policy making across sectors, and at all levels, to improve the health of all communities and people. " – Association of State and Territorial Health Officers (ASTHO).

" Health in All Policies is a collaborative approach to improving the health of all people by incorporating health considerations into decision-making across sectors and policy areas. " –California Health in All Policies Task Force.

" Health in All Policies is the policy practice of including, integrating or internalizing health in other policies that shape or influence the [Social Determinants of Health (SDoH)] …Health in All Policies is a policy practice adopted by leaders and policy makers to integrate consideration of health, well-being and equity during the development, implementation and evaluation of policies. " – European Observatory on Health Systems and Policies.

" Health in All Policies is an innovative, systems change approach to the processes through which policies are created and implemented. " – National Association of County and City Health Officials (NACCHO).

" Health in All Policies aims to improve the health of the population through increasing the positive impacts of policy initiatives across all sectors of government and at the same time contributing to the achievement of other sectors’ core goals. " – South Australia.

‘Health policy’ , thus, is both Healthy Public Policy and Health in All Policy, and may include public health policy and health care policy. Public health policy can be conceived either as public sector (government) policy for population health (public health policy) or any policy (including corporate and other civil society approaches) concerned with the public’s health (public health policy).

‘Health care policy’ in principle focuses on health care as the organised enterprise of curing or caring for disease, disability, and infirmity, and includes efforts at regulating and organising health care professions, pharmaceuticals, financing of the healthcare system, and access to healthcare facilities. Health care in essence is disease care [ 20 ] and at its core focuses on individual outcomes rather than population issues. This is potentially confusing as in most nation-states the healthcare system includes the public health system, although efforts have been made to separate the two, for instance in Canada with the creation of the (short-lived) Health Promotion Directorate following the publication of the Lalonde Report [ 21 ], and in Kenya with a ministerial public health and sanitation portfolio [ 22 ].

When the literature refers to ‘health policy’, it usually convolutes several of the above demarcations. Most often, the phrase ‘health policy’ will be used to talk about health care policy, i.e., when actually disease or healthcare policy is meant. Admittedly, health care policy research is already a dominant and powerful driver of developments in health political science, both in terms of the number of studies and in terms of the theoretical developments it yields. However, in its scope and impact, healthcare policy research is less interested in the politics of population health. In analysing the impact and outcome of health policy, therefore, any scholar should conscientiously delineate what s/he (a) considers ‘policy’ to be, and (b) considers as the scope of ‘health’. In this paper, we use the phrase health policy in a broader way to designate all government action to improve population health, i.e., Healthy Public Policy and Health in All Policy.

The policy process

Studying health policy requires an understanding of its development process. This is particularly important if we want to have an impact on the direction of policy and its framed health objectives. The application of theories of the policy process would enable an appreciation of the range of stakeholders and determinants of policy choice. Mackenbach [ 23 ] recently called for the further development of a ‘political epidemiology’ identifying the causal effects of political variables (structures, processes, outputs) on population health. In fact, the political sciences have developed a powerful toolbox of theories of the policy process framing these political variables (notably the work of Sabatier [ 24 ] with recent updates by Nowlin [ 25 ] and Schlager and Weible [ 26 ]).

Some of the theories that have been tried and tested include the event-driven Multiple Streams Theory empirically developed by Kingdon [ 27 ]; the Punctuated Equilibrium framework by Baumgartner and Jones [ 28 ], in which long periods of policy stability are alternated by general shifts in policy perspectives and ambitions; the Advocacy Coalition Framework [ 29 , 30 ] that emphasises the importance of coalition formation of camps of proponents and opponents to new policy directions; the Policy Domains approach coming from different perspectives on network governance [ 31 , 32 ]; and Social Movement Theory [ 33 ] arguing that disenchanted people will join social movements in order to mobilise resources and political opportunity to change public policy to their advantage. The scope of political science theory relevant to studying public policy and public policy change is even broader [ 34 , 35 ], ranging from hybrid approaches that mix these perspectives [ 25 ] or address specific processes such as coalition structuring [ 36 ].

We were keen to explore to what extent this body of theories of the policy process has made in-roads into health promotion and health education research [ 37 ]. The outcome of our systematic review was no less than disappointing: we identified 8,337 health promotion and health education research articles since the ‘healthy public policy’ rhetoric became mainstream in 1986, of which only 21 explicitly and conscientiously applied a political science theory. A systematic review of the use of ‘commonly identified policy analysis theories’ to the study of social determinants of health and health equity public policy arrived at similar results, with seven articles making use of such theories out of a total of 6,200 articles [ 38 ].

The importance of rigorous application of theory to solving social problems has been proffered by Birckmayer and Weiss in their Theory-Based Evaluation approach [ 39 ], and is a key doctrine for health promotion and health education development and evaluation [ 40 ]. The selection of an appropriate theory would provide answers to questions that ask why things are (not) happening beyond a mere description that they are (not) happening. A recent example of a policy issue that was investigated without the appropriate application of theories of the policy process was authored by Gonzalez and Glantz [ 41 ]. The authors record an extensive case study of a policy failure in The Netherlands. The country is a signatory to the Framework Convention on Tobacco Control and passed comprehensive legislation regulating all aspects of its MPOWER strategy ( M onitor tobacco use and prevention policies; P rotect people from tobacco smoke; O ffer help to quit tobacco use; W arn about the dangers of tobacco; E nforce bans on tobacco advertising, promotion, and sponsorship; R aise taxes on tobacco). In its implementation, however, The Netherlands failed to comprehensively ban smoking from all public drinking holes. Gonzalez and Glantz reach the conclusion that the legislative approach was unsuccessful because of " …poor implementation efforts and the failure to anticipate and deal with opposition to the law. " This is hardly a profound, or useful, political insight: " It didn’t work because it didn’t work. "

In a theory-based policy evaluation approach the authors might have made their assumptions of the phenomenon under study explicit and subsequently selected an appropriate theoretical framework. They may have already had some ‘gut feeling’ that policy implementation was to blame for the issue and applied a political science theory that claimed to identify relations between (Mackenbach’s) policy implementation structures, processes, and outputs. This may have led to the selection of Mazmanian and Sabatier’s policy implementation framework [ 42 ] – see below. Alternatively, they might have seen implementation failure as the result of a breakdown of governance arrangements between different policy levels and sectors, and selected, for instance, Hill and Hupe’s multi-level governance perspectives [ 43 ] to explain what went wrong, where, between whom and what, and how.

Assuming they would have selected the Mazmanian and Sabatier model (Figure  1 ) [ 42 ], this would have led to the careful operationalization of variables and data to be collected – rather than drawing on a fairly randomly selected collection of informants and media expressions. The conclusions, then, would have allowed for specific propositions as regards to the identification and management of the policy problem, the ability of the Dutch governments and its agents and structures to take measures leading to implementation, and measured descriptions of facilitators and barriers beyond the control of government that impact on the implementation process. One would assume that a carefully crafted methodology in which qualitative and quantitative approaches would supplement each other would yield a much more pointed analysis and conclusions that would provide evidence-based courses of action for policy entrepreneurs and smoking-or-health activists.

Variables involved in the implementation process (adapted from Figure  2 .1 in [ 42 ] ).

A similar theoretical naïveté can be observed in a recent, albeit slightly more astute, analysis of the determinants of tobacco excise tax in the USA [ 44 ]. The analysis is more astute as the authors find that ‘political’ determinants determine tax levels. That is, the level of tax is not dependent on economic considerations, but purely on ‘political characteristics’ – these being operationalised as Democratic-Mixed-Republican control of the executive and legislative branches of State government, governor time in office, and popular attitudes toward tax levels. The conclusion is that tobacco taxes in Republican states tend to be lower, and that there are many factors (and political variables) beyond the scope of the study. Should the recommendation to the policy entrepreneur and tobacco-or-health activist therefore be to join the campaign team of the Democratic Party for the next election? The answer, as Breton and colleagues have demonstrated for the tobacco control policy development in Quebec [ 36 ], is more complicated. In their description of the evolution of advocacy coalitions (based on Sabatier and Jenkins-Smith [ 30 ] and Lemieux [ 45 ]), they show how policy elites manage and manipulate events and pool resources, and tobacco control proponents break up emerging unification of opponent coalitions. Similar policy research, with foundations in Golden, Ribisl, and Perreira data [ 44 ], would potentially highlight vastly more astute political action to solidify and secure not just tobacco control but more broadly all health policy.

The stages heuristic and beyond

There seem to be a few barriers to the application of theories of the policy process to the health sciences in general. One is that few health scientists are trained in political science, and where they are, they do not seem to enter the health education and health promotion fields. Conversely, few students of public policy and public administration have taken an interest in health policy with the broad population and social determinant scope we described above. Most political science research is concerned with health care systems inquiry much more than with public health policy. Second, there is a lack of good benchmark studies that would set a standard for research applying theories of the policy process to public health policy, and consequently the kinds of superficial and uninsightful papers as discussed above find their way through editorial and peer-reviewed processes too easily. Third, we attribute the dearth of published studies inspired by theories of the policy process to a serious lack of (competitive) funding [ 14 ]. The proportion of grants devoted to public health is a fraction of the total medical research pool, and within the public health field funding for political research is virtually absent. Fourth, as Albert et al. demonstrated [ 46 ], members of health grant review panels do not regard social science research methods – and within that realm political science approaches – as a legitimate paradigm to study health matters. Fifth, the policy discourse in the health field is highly value-laden, intermingling debates about identity, equality [ 47 – 49 ], and – in the case of health care policy specifically – the role of technology and expertise [ 50 ], which clouds the legitimate application of the available evidence.

However, the two research examples given above highlight an issue that many health promotion and health education policy researchers seem to be struggling with most. This issue touches on the very nature of theories of the policy process. Theories applied in behavioural research are typically linear, at best with a feedback loop: a number of inputs (say, ‘attitudes’ and ‘beliefs’) are transformed through a number of conditioners (say, ‘social norm’ and ‘self-efficacy’) to produce intermediary (‘intention’) and final (‘behavioural’) change. In more complex behavioural systems there may be iterative and more incremental steps, and sometimes the models may take the shape of a cycle.

This, then, is also how policy development is typically modelled. Such a policy cycle can variably exist of as little as three steps (problem – solution – evaluation), four stages (agenda setting – policy formation – policy implementation – policy review) with as many as 15 sub-processes, to retrospective policy analyses that yield dozens of policy development instances, phases, and events.

All of these represent the policy process as displaying a curved linearity in which one stage –sometimes under conditions – leads to the next stage, just like the behavioural theories introduced above. While this representation of the policy process still permeates the health sciences – but also policy advice to governments [ 35 ] – policy students have now come to the realisation that policy making is a messy (some would say ‘wicked’) affair that does not neatly stick to stages.

It is not just that one stage or step coincides with another (for instance, the specification of policy alternatives may interface with the selection of policy instruments/interventions). In fact, often a step that comes ‘later’ in the stages heuristic in fact precedes an earlier phase in the cycle. A ‘real life’ example would be policy implementation. Implementation, as we have seen above, is driven by a wide array of contextual factors, including shifting power relations. Even when the policy problem is debated (as a first ‘agenda setting’ exercise), actors in the system implicitly, or by default, know that some implementation strategies will be impossible to develop. Regardless of how well-planned and analytical earlier stages in the policy process are, only certain types of interventions can be favoured. In a comprehensive review of the literature on policy instruments and interventions, Bemelmans-Videc, Rist, and Vedung formulate the ‘least coercion rule’ [ 51 ]: policy-makers choose the intervention that is least intrusive into individual choice of populations (as evidenced for obesity policy by, for instance, Allender et al. [ 52 ]). Thus, despite following the policy planning process conscientiously, the outcome in implementation terms favours communicative over facilitative or regulatory interventions. Steps in the cycle are therefore in reality rarely sequential or with feedback loops between sequential stages: often the process jumps a few steps ahead, to return to a previous step, or it finds itself going both clockwise and counter-clockwise for only sections of the cycle.

We were recently commissioned by WHO to develop a tool that would guide the development and application of Health in All Policies [ 53 ]. Through discussions with key stakeholders around the world we identified ten issues that need to be analysed and mapped in order to enhance the feasibility of Health in All Policies development. We drafted a Health in All Policies cycle (Figure  2 ) for discussion with Health in All Policies experts, showing both the clockwise and counter-clockwise sequential options for considering these options. The feedback on the figure demonstrated that the intuitive response to the graph was to diligently follow each of the stages, assuming there was a progressive logic to them. At the same time our panel agreed that the reality is that " everything happens at the same time ".

Proposed policy process cycle for developing Health in All Policies.

This is the essence of the critique that has been voiced by political scientist on the ‘stages heuristic’ [ 24 , 25 ] – that there is no causality between the different stages and therefore stages heuristic models defy theoretical testing mechanisms. The stages heuristic is useful as a mnemonic and an analytical visualisation of elements of the policy process, but does not describe the complex interactions within, between, and beyond its different features. Hassenteufel [ 54 ] furthermore argued that the analytical linearity of the stages heuristic clouds the symbolic nature of policy making in society as a sense-making activity rather than a purely methodical enterprise.We found that the best visual metaphor for this reality of the policy process is that of juggling (Figure  3 ).

Health in All Policies juggling process.

The juggling metaphor appears to ring true to policy entrepreneurs and activists at the coal face of policy development and change. It recognises that, although keeping all balls in the air virtually simultaneously creates an apparently hugely chaotic scene, systematic and disciplined action is required at all times. Juggling is decidedly not the same as the idea of policy making as a garbage-can process (most profoundly professed by March & Olsen [ 55 ]) – the application of theories highlighted above would aim at structuring and making sense of the logic, diligence, and structure of managing a chaotic process. Theory-led discussions between academics and practitioners have been suggested to work towards this end [ 35 ]. Is the ability to keep all balls in the air also predictive of policy effectiveness?

Assessing policy outcomes

Policies are formulated to address problems. In their ideal types, resources are allocated to develop evidence-based interventions and policy instruments and one would assume that, steeped in a validated body of knowledge, the policy will achieve its stated outcomes. However, as we have seen above, not all implementation strategies or policy ambitions are necessarily grounded in evidence. They follow the ‘least coercion rule’ [ 51 ]; are grounded in value-based rather than evidence-based policy ontologies [ 56 ]; are only symbolic to project an image of government concern [ 57 ]; or address a tangible yet insignificant element of the complexity of the real problem [ 58 ].

It is the responsibility of the policy analyst to expose such flaws through the systematic assessment of the policy process and its assumptions. Walt et al. [ 59 ] describe the multiple meanings and challenges in undertaking ‘proper’ health policy analysis. Following our argument above they contend that a conscientious, structured, and rigorous application of theories of the policy process to policy analysis is important. At the same time, however, the aims of policy analysis may be diffuse and its starting point should be to delineate its purpose. Paraphrasing a policy analysis training manual by the United Nations Environment Programme [ 60 ], the causal and final chains of drivers and consequences of policies and their contexts are hard to map, and many policies fail to include specific performance criteria or direct intervention parameters. Setting the boundaries of a policy analysis therefore becomes a negotiated process between many stakeholders, for which Pawson and Tilley [ 61 ] suggest a ‘realist’ approach that recognises the uniqueness of each policy issue and context. In showing policy ‘effectiveness’, evaluators therefore focus on intermediate policy effects rather than end-point health impact.

Case study: environments for health policy research – Environments for Health (E4H) policy effectiveness

In 2001, the government of the Australian State of Victoria adopted its E4H policy framework [ 62 ]. It connects with legislation that requires local governments in the State to develop Municipal Public Health Plans (MPHPs). E4H provides evidence-based guidance for the development of local policy that addresses social and environmental determinants of health in the overlapping domains of the social, built, economic, and natural environments. E4H explicitly embraces a social model of health, and the policy package provides local government with a comprehensive evidence base, capacity building for local health bureaucrats and communities, and exemplars of policy action.

Five years after adoption, the Victorian Department of Health commissioned an evaluation into E4H policy effectiveness. The evaluation objectives were to assess the extent to which the E4H Framework had:

 Been incorporated by local governments in their policies and practices;

 Contributed to greater consistency and quality in the scope and approach of municipal public health planning across the state;

 Led to the integration of MPHPs with other council plans;

 Increased the level of understanding among appropriate local government staff of the impact of the social, economic, natural, and built environments on health and wellbeing;

 Created additional opportunities for health gain through strengthened intersectoral partnerships to address the social determinants of health; and

 Been supported effectively by the Department of Human Services and other stakeholders [ 63 ].

The evaluation objectives were the outcome of negotiations between a range of stakeholders, including the Department of Human Services, local governments, and research sector representatives. The consequence was that hybridization of a number of political theories was required in a realist evaluation framework [ 61 ], notably policy diffusion theory [ 64 ], implementation theory [ 42 ], and Multiple Streams theory [ 27 ]. The resulting methodology drew on a range of data collection strategies:

 Document analysis of Victorian Local Government Authorities’ MPHPs (62 plans);

 Seventy-three individual and group interviews with key stakeholders in municipal public health planning;

 Online survey of individuals involved in municipal public health planning (councillors, council staff, non-council organisations, and community members) (108 survey respondents);

 Five community forums to present preliminary evaluation findings and obtain input from additional stakeholder groups.

In summary [ 65 ], the evaluation found that E4H had substantially changed the way local governments think about health; improved the way local governments plan for health; and started sectoral integration. However, developing a MPHP was frequently seen as a – statutorily required – means in itself, and implementation was often lagging. The Department of Health consequently launched programmes for implementation knowledge co-creation, capacity-building, and networking at the local level, case models for – especially economic – E4H development, and political skills.

Conclusions

Determining the evidence of effectiveness of policy change for health is an art and a science that is still in its infancy. A systematic and theory-driven approach needs to be applied. In this paper we have demonstrated that insights from political science would allow for better and more profound insights into the reasons why and how policies fail or succeed. This is a perspective that transcends a current tradition merely describing failure or success of policy initiatives.

Our empirical material shows that policy research, assessment, and analysis needs to be a negotiated process between stakeholders that is seemingly chaotic, but in reality must be driven by the appropriate – and often hybrid – application of theories from the social sciences, notably political science.

A conscientious and transparent approach to determining what policy is and entails is a critical starting point for the further development of this field. It is recognised that such a determination is frequently impossible as even policymakers, policy entrepreneurs, and decision makers themselves are deliberately equivocal about what they pursue – the eminent economist John Maynard Keynes pointed at the need to keep options open as long as possible by writing " There is nothing a Government hates more than to be well-informed; for it makes the process of arriving at decisions much more complicated and difficult " [ 66 ]. It is the responsibility of public health policy analysts to expose any efforts at purposely obscuring the strictures of policy making. Good scholarly process, rigour in research, and theory-based evaluation, should enable us to do exactly that.

McLeroy KR, Bibeau D, Steckler A, Glanz K: An ecological perspective on health promotion programs. Health Educ Behav. 1998, 15: 351-377.

Article   Google Scholar  

World Health Organization, Canadian Public Health Association, Health Canada: The Ottawa charter for health promotion. Health Promot. 1986, 1: i-v.

Google Scholar  

Dempsey C, Battel-Kirk B, Barry MM, the CompHP Project Partners: The CompHP Core Competencies Framework for Health Promotion Handbook. 2011, Paris: IUHPE

Australian Health Promotion Association: Core Competencies for Health Promotion Practitioners. 2009, Maroochydore: AHPA, University of the Sunshine Coast

Doyle E: A Competency-Based Framework for Health Education Specialists – 2010. 2010, Whitehall, PA: National Commission for Health Education Credentialing (NCHEC), Society for Public Health Education (SOPHE), American Association for Health Education (AAHE), Washington DC

Clavier C, de Leeuw E: Health Promotion and the Policy Process. 2013, Oxford: Oxford University Press

Book   Google Scholar  

CSDH: Closing the Gap in a Generation. Health Equity through Action on the Social Determinants of Health. Final Report of the Commission on Social Determinants of Health. 2008, Geneva: World Health Organization

Lieberman L, Golden SD, Earp JAL: Structural approaches to health promotion: what do we need to know about policy and environmental change?. Health Educ Promot. 2013, 49: 520-525.

Kahn-Marshall JL, Gallant MP: Making healthy behaviors the easy choice for employees: a review of the Literature on environmental and policy changes in worksite health promotion. Health Educ Behav. 2012, 39: 752-776. 10.1177/1090198111434153.

Article   PubMed   Google Scholar  

Cochran CE: American Public Policy: An Introduction. 1999, New York: St. Martin’s Press, 6

Dye TR: Understanding Public Policy. 1972, NJ, Englewood Cliffs

Richards D, Smith MJ: Governance and Public Policy in the United Kingdom. 2008, Oxford: Oxford University Press

de Leeuw E: Policies for Health. The Effectiveness of the Development, Adoption and Implementation. Global Perspectives on Health Promotion Effectiveness. Edited by: McQueen D, Jones CM. 2007, New York: Springer, 51-66.

Chapter   Google Scholar  

Breton E, de Leeuw E: Theories of the policy process in health promotion research: a review. Health Promot Int. 2011, 26: 82-90. 10.1093/heapro/daq051.

de Leeuw E: Health Policy. An Exploratory Inquiry into the Development of Policy for the New Public Health in The Netherlands. 1989, Maastricht, The Netherlands: Dissertation, University of Limburg

Milio N: Promoting Health through Public Policy. 1981, Philadelphia: FA Davis Company

Milio N: Glossary: healthy public policy. J Epidemiol Community Health. 2001, 55: 622-623. 10.1136/jech.55.9.622.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Ståhl T, Wismar M, Ollila E, Lahtinen E, Leppo K: Health in All Policies. Prospects and Potentials. In Health in All Policies. Prospects and Potentials. 2006, Helsinki: Ministry of Social Affairs and Health & European Observatory on Health Systems and Policies

Rudolph L, Caplan J, Ben-Moshe K, Dillon L: Health in All Policies: A Guide for State and Local Governments. 2013, Washington, DC and Oakland, CA: American Public Health Association and Public Health Institute

de Leeuw E, Keizer M, Hoeijmakers M: Health policy networks: connecting the disconnected. Health Promotion and the Policy Process. Edited by: Clavier C, de Leeuw E. 2013, Oxford: Oxford University Press, 154-173.

Hancock T: Health promotion in Canada: 25 years of unfulfilled promise. Health Promot Int. 2011, 26: ii263-ii267. 10.1093/heapro/daq054.

Chuma J, Okungu V: Viewing the Kenyan health system through an equity lens: implications for universal coverage. Int J Equity Health. 2011, 10: 1-14. 10.1186/1475-9276-10-1.

Mackenbach J: Political determinants of health. Eur J Public Health. 2014, 24: 2-

Sabatier PA: The need for better theories. Theories of the Policy Process. Edited by: Sabatier PA. 2007, Cambridge, MA: Westview Press, 3-17.

Nowlin MC: Theories of the policy process: state of the research and emerging trends. Policy Stud J. 2011, 39: 41-60.

Schlager E, Weible CM: New theories of the policy process. Policy Stud J. 2013, 41: 389-396. 10.1111/psj.12030.

Kingdon JW: Agendas, Alternatives and Public Policies. 1984, Boston: Little, Brown and Co

Baumgartner F, Jones B: Agendas and Instability in American Politics. 1993, Chicago: University of Chicago Press

Sabatier PA: An advocacy coalition framework of policy change and the role of policy-oriented learning therein. Policy Sci. 1988, 21: 129-168. 10.1007/BF00136406.

Sabatier PA, Jenkins-Smith HC: Policy Change and Learning: An Advocacy Coalition Approach. 1993, Boulder, CO: Westview Press

Laumann EO, Knoke D: The Organizational State. Social Choice in National Policy. 1987, Wisconsin: The University of Wisconsin Press

Börzel TA: Organizing Babylon - on the different conceptions of policy networks. Public Adm. 1998, 76: 253-273. 10.1111/1467-9299.00100.

McCarthy JD, Zald MN: Resource mobilization and social movements: a partial theory. Am J Sociol. 1977, 82: 1212-1241. 10.1086/226464.

Smith K: Beyond Evidence-based Policy in Public Health: The Interplay of Ideas. 2013, New York: Palgrave Macmillan

Cairney P: How can policy theory have an impact on policy making? The Role of theory-led academic–practitioner discussions. Teach Public Adm. 2014, 2014: 0144739414532284-

Breton E, Richard L, Gagnon F, Jacques M, Bergeron P: Health promotion research and practice require sound policy analysis models: the case of Quebec’s tobacco act. Soc Sci Med. 2008, 67: 1679-1689. 10.1016/j.socscimed.2008.07.028.

de Leeuw É, Breton E: Policy change theories in health promotion research: a review. Health Promotion and the Policy Process. Edited by: Clavier C, de Leeuw E. 2013, Oxford: Oxford University Press, 23-42.

Embrett MG, Randall GE: Social determinants of health and health equity policy research: exploring the use, misuse, and nonuse of policy analysis theory. Soc Sci Med. 2014, 108: 147-155.

Birckmayer JD, Weiss CH: Theory-based evaluation in practice: what do we learn?. Eval Rev. 2000, 24: 407-431. 10.1177/0193841X0002400404.

Article   CAS   PubMed   Google Scholar  

Bartholomew LK, Parcel GS, Kok G, Gottlieb NH, Fernandez ME: Planning Health Promotion Programs: An Intervention Mapping Approach. 2011, San Francisco, CA: Jossey-Bass, 3

Gonzalez M, Glantz SA: Failure of policy regarding smoke-free bars in the Netherlands. Eur J Public Health. 2013, 23: 139-145. 10.1093/eurpub/ckr173.

Mazmanian DA, Sabatier PA: Implementation and Public Policy. 1983, Glenview, IL: Scott Foresman

Hill M, Hupe P: Analysing policy processes as multiple governance: accountability in social policy. Policy Polit. 2006, 34: 557-573. 10.1332/030557306777695280.

Golden SD, Ribisl KM, Perreira KM: Economic and political influence on tobacco tax rates: a nationwide analysis of 31 years of state data. Am J Public Health. 2014, 0: e1-e8.

Lemieux V: Les Coalitions Liens, Transactions et Contrôles. 1998, Paris: Paris Presses Universitaires de France

Albert M, Laberge S, Hodges BD, Regehr G, Lingard L: Biomedical scientists’ perception of the social sciences in health research. Soc Sci Med. 2008, 66: 2520-2531. 10.1016/j.socscimed.2008.01.052.

Collovald A, Gaïti B: Discours sous surveillance: le social à l’Assemblée. Le "social" Transfiguré Sur la Représentation Politique des Préoccupations "Sociales". Edited by: Gaxie D, Collovald A, Gaïti B, Lehingue P, Poirmeur Y. 1990, Paris: CURAPP et PUF, 9-54.

Fassin D: L’espace Politique de la Santé. Essai de Généalogie. 1996, Paris: PUF

Oliver TR: The politics of public health policy. Annu Rev Public Health. 2006, 27: 195-233. 10.1146/annurev.publhealth.25.101802.123126.

Carpenter D: Is health politics different?. Annu Rev Polit Sci. 2012, 15: 287-311. 10.1146/annurev-polisci-050409-113009.

Bemelmans-Videc M-L, Rist RC, Vedung E: Carrots, Sticks & Sermons: Policy Instruments and their Evaluation. 1998, New Brunswick, NJ: Transaction Publishers

Allender S, Gleeson E, Crammond B, Sacks G, Lawrence M, Peeters A, Loff B, Swinburn B: Policy change to create supportive environments for physical activity and healthy eating: which options are the most realistic for local government?. Health Promot Int. 2012, 27: 261-274. 10.1093/heapro/dar018.

de Leeuw E, Peters D: Nine questions to guide development and implementation of health in all policies. Health Promot Int. 2014, In press

Hassenteufel P: Sociologie Politique: L’action Publique (2ème édition). 2011, Paris: Armand-Colin

March JG, Olsen JP: The new institutionalism: organizational factors in political life. Am Polit Sci Rev. 1984, 78: 734-749. 10.2307/1961840.

Milewa T, de Leeuw E: Reason, power and protest in the new urban public health movement: a basis for sociological analysis of political discourse in the ‘healthy city’. Br J Sociol. 1996, 47: 657-670. 10.2307/591078.

Fotaki M: Why do public policies fail so often? Exploring health policy-making as an imaginary and symbolic construction. Organization. 2000, 17: 703-720.

Blackman T, Hunter DJ, Marks L, Harrington B, Elliott E, Williams G, McKee L: Wicked comparisons: reflections on cross-national research about health inequalities in the UK. Evaluation. 2010, 16: 43-57. 10.1177/1356389009350016.

Walt G, Shiffman J, Schneider H, Murray SF, Brugha R, Gilson L: ‘Doing’ health policy analysis: methodological and conceptual reflections and challenges. Health Pol Plann. 2008, 23: 308-317. 10.1093/heapol/czn024.

UNEP: Training Manual - Module 5–6.5.1 Understanding Policy Effects and Policy Effectiveness. 2014, [ http://www.unep.org/ieacp/iea/training/manual/module5/1236.aspx ]. Accessed 3 February 2014

Pawson R, Tilley N: Realist Evaluation. 1997, Thousand Oaks: Sage

Department of Human Services: Environments for Health: Promoting Health and Wellbeing through Built, Social, Economic and Natural Environments. Municipal Public Health Planning Framework. 2001, Melbourne, Victoria: Department of Human Services

de Leeuw E, Butterworth I, Garrard J, Palermo J, Godbold T, Tacticos T: Evaluation of the Environments for Health Framework. 2006, Melbourne, Victoria: Deakin University and the University of Melbourne

Lindblom CE: The science of ‘Muddling Through’. Public Adm Rev. 1959, 19: 79-88. 10.2307/973677.

Department of Health: Local Government Planning for Health and Wellbeing - Resources. 2014, [ http://www.health.vic.gov.au/localgov/resources.htm ]. Accessed 4 February 2014

Keynes JM, Moggridge D: The Collected Writings of John Maynard Keynes. Volume 21. Activities 1931–1939; World Crisis and Policies in Britain and America. 1982, London and New York: Macmillan and Cambridge University Press for the Royal Economic Society

Download references

Author information

Authors and affiliations.

Public Health, La Trobe University, Melbourne, VIC 3000, Australia

Evelyne de Leeuw

Département de Science Politique, Université du Québec à Montréal, Case postale 8888, succ. Centre-Ville, Montréal, Québec, H3C 3P8, Canada

Carole Clavier

Ecole des Hautes Études en santé Publique (EHESP), Avenue du Professeur Léon-Bernard - CS 74312, 35043, Rennes cedex, France

Eric Breton

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Evelyne de Leeuw .

Additional information

Competing interests.

The authors declare that they have no competing interests.

Authors’ contributions

EdL conceived the argument for this paper and developed a first draft. CC and EB provided case material, further referencing and sections to the draft, and edited the work. The first submission was prepared by EdL, with resubmission editing provided by CC. All authors read and approved the final manuscript.

Authors’ original submitted files for images

Below are the links to the authors’ original submitted files for images.

Authors’ original file for figure 1

Authors’ original file for figure 2, authors’ original file for figure 3, authors’ original file for figure 4, authors’ original file for figure 5, authors’ original file for figure 6, rights and permissions.

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated.

Reprints and Permissions

About this article

Cite this article.

de Leeuw, E., Clavier, C. & Breton, E. Health policy – why research it and how: health political science. Health Res Policy Sys 12 , 55 (2014). https://doi.org/10.1186/1478-4505-12-55

Download citation

Received : 24 June 2014

Accepted : 02 September 2014

Published : 23 September 2014

DOI : https://doi.org/10.1186/1478-4505-12-55

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Health Research Policy and Systems

ISSN: 1478-4505

• Submission enquiries: Access here and click Contact Us
• General enquiries: [email protected]

• Youth Program
• Wharton Online

Research Papers / Publications

Loading metrics

Open Access

Peer-reviewed

Research Article

Assessing the impact of healthcare research: A systematic review of methodological frameworks

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Validation, Writing – original draft, Writing – review & editing

Affiliation Centre for Patient Reported Outcomes Research, Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom

Roles Conceptualization, Formal analysis, Funding acquisition, Methodology, Project administration, Supervision, Validation, Writing – review & editing

* E-mail: [email protected]

Roles Data curation, Formal analysis, Methodology, Validation, Writing – review & editing

Roles Formal analysis, Methodology, Supervision, Validation, Writing – review & editing

• Samantha Cruz Rivera, 
• Derek G. Kyte, 
• Olalekan Lee Aiyegbusi, 
• Thomas J. Keeley, 
• Melanie J. Calvert

• Published: August 9, 2017
• https://doi.org/10.1371/journal.pmed.1002370
• Reader Comments

Increasingly, researchers need to demonstrate the impact of their research to their sponsors, funders, and fellow academics. However, the most appropriate way of measuring the impact of healthcare research is subject to debate. We aimed to identify the existing methodological frameworks used to measure healthcare research impact and to summarise the common themes and metrics in an impact matrix.

Methods and findings

Two independent investigators systematically searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), the Excerpta Medica Database (EMBASE), the Cumulative Index to Nursing and Allied Health Literature (CINAHL+), the Health Management Information Consortium, and the Journal of Research Evaluation from inception until May 2017 for publications that presented a methodological framework for research impact. We then summarised the common concepts and themes across methodological frameworks and identified the metrics used to evaluate differing forms of impact. Twenty-four unique methodological frameworks were identified, addressing 5 broad categories of impact: (1) ‘primary research-related impact’, (2) ‘influence on policy making’, (3) ‘health and health systems impact’, (4) ‘health-related and societal impact’, and (5) ‘broader economic impact’. These categories were subdivided into 16 common impact subgroups. Authors of the included publications proposed 80 different metrics aimed at measuring impact in these areas. The main limitation of the study was the potential exclusion of relevant articles, as a consequence of the poor indexing of the databases searched.

Conclusions

The measurement of research impact is an essential exercise to help direct the allocation of limited research resources, to maximise research benefit, and to help minimise research waste. This review provides a collective summary of existing methodological frameworks for research impact, which funders may use to inform the measurement of research impact and researchers may use to inform study design decisions aimed at maximising the short-, medium-, and long-term impact of their research.

Author summary

Why was this study done.

• There is a growing interest in demonstrating the impact of research in order to minimise research waste, allocate resources efficiently, and maximise the benefit of research. However, there is no consensus on which is the most appropriate tool to measure the impact of research.
• To our knowledge, this review is the first to synthesise existing methodological frameworks for healthcare research impact, and the associated impact metrics by which various authors have proposed impact should be measured, into a unified matrix.

What did the researchers do and find?

• We conducted a systematic review identifying 24 existing methodological research impact frameworks.
• We scrutinised the sample, identifying and summarising 5 proposed impact categories, 16 impact subcategories, and over 80 metrics into an impact matrix and methodological framework.

What do these findings mean?

• This simplified consolidated methodological framework will help researchers to understand how a research study may give rise to differing forms of impact, as well as in what ways and at which time points these potential impacts might be measured.
• Incorporating these insights into the design of a study could enhance impact, optimizing the use of research resources.

Citation: Cruz Rivera S, Kyte DG, Aiyegbusi OL, Keeley TJ, Calvert MJ (2017) Assessing the impact of healthcare research: A systematic review of methodological frameworks. PLoS Med 14(8): e1002370. https://doi.org/10.1371/journal.pmed.1002370

Academic Editor: Mike Clarke, Queens University Belfast, UNITED KINGDOM

Received: February 28, 2017; Accepted: July 7, 2017; Published: August 9, 2017

Copyright: © 2017 Cruz Rivera et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and supporting files.

Funding: Funding was received from Consejo Nacional de Ciencia y Tecnología (CONACYT). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript ( http://www.conacyt.mx/ ).

Competing interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: MJC has received consultancy fees from Astellas and Ferring pharma and travel fees from the European Society of Cardiology outside the submitted work. TJK is in full-time paid employment for PAREXEL International.

Abbreviations: AIHS, Alberta Innovates—Health Solutions; CAHS, Canadian Academy of Health Sciences; CIHR, Canadian Institutes of Health Research; CINAHL+, Cumulative Index to Nursing and Allied Health Literature; EMBASE, Excerpta Medica Database; ERA, Excellence in Research for Australia; HEFCE, Higher Education Funding Council for England; HMIC, Health Management Information Consortium; HTA, Health Technology Assessment; IOM, Impact Oriented Monitoring; MDG, Millennium Development Goal; NHS, National Health Service; MEDLINE, Medical Literature Analysis and Retrieval System Online; PHC RIS, Primary Health Care Research & Information Service; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; PROM, patient-reported outcome measures; QALY, quality-adjusted life year; R&D, research and development; RAE, Research Assessment Exercise; REF, Research Excellence Framework; RIF, Research Impact Framework; RQF, Research Quality Framework; SDG, Sustainable Development Goal; SIAMPI, Social Impact Assessment Methods for research and funding instruments through the study of Productive Interactions between science and society

Introduction

In 2010, approximately US$240 billion was invested in healthcare research worldwide [ 1 ]. Such research is utilised by policy makers, healthcare providers, and clinicians to make important evidence-based decisions aimed at maximising patient benefit, whilst ensuring that limited healthcare resources are used as efficiently as possible to facilitate effective and sustainable service delivery. It is therefore essential that this research is of high quality and that it is impactful—i.e., it delivers demonstrable benefits to society and the wider economy whilst minimising research waste [ 1 , 2 ]. Research impact can be defined as ‘any identifiable ‘benefit to, or positive influence on the economy, society, public policy or services, health, the environment, quality of life or academia’ (p. 26) [ 3 ].

There are many purported benefits associated with the measurement of research impact, including the ability to (1) assess the quality of the research and its subsequent benefits to society; (2) inform and influence optimal policy and funding allocation; (3) demonstrate accountability, the value of research in terms of efficiency and effectiveness to the government, stakeholders, and society; and (4) maximise impact through better understanding the concept and pathways to impact [ 4 – 7 ].

Measuring and monitoring the impact of healthcare research has become increasingly common in the United Kingdom [ 5 ], Australia [ 5 ], and Canada [ 8 ], as governments, organisations, and higher education institutions seek a framework to allocate funds to projects that are more likely to bring the most benefit to society and the economy [ 5 ]. For example, in the UK, the 2014 Research Excellence Framework (REF) has recently been used to assess the quality and impact of research in higher education institutions, through the assessment of impact cases studies and selected qualitative impact metrics [ 9 ]. This is the first initiative to allocate research funding based on the economic, societal, and cultural impact of research, although it should be noted that research impact only drives a proportion of this allocation (approximately 20%) [ 9 ].

In the UK REF, the measurement of research impact is seen as increasingly important. However, the impact element of the REF has been criticised in some quarters [ 10 , 11 ]. Critics deride the fact that REF impact is determined in a relatively simplistic way, utilising researcher-generated case studies, which commonly attempt to link a particular research outcome to an associated policy or health improvement despite the fact that the wider literature highlights great diversity in the way research impact may be demonstrated [ 12 , 13 ]. This led to the current debate about the optimal method of measuring impact in the future REF [ 10 , 14 ]. The Stern review suggested that research impact should not only focus on socioeconomic impact but should also include impact on government policy, public engagement, academic impacts outside the field, and teaching to showcase interdisciplinary collaborative impact [ 10 , 11 ]. The Higher Education Funding Council for England (HEFCE) has recently set out the proposals for the REF 2021 exercise, confirming that the measurement of such impact will continue to form an important part of the process [ 15 ].

With increasing pressure for healthcare research to lead to demonstrable health, economic, and societal impact, there is a need for researchers to understand existing methodological impact frameworks and the means by which impact may be quantified (i.e., impact metrics; see Box 1 , 'Definitions’) to better inform research activities and funding decisions. From a researcher’s perspective, understanding the optimal pathways to impact can help inform study design aimed at maximising the impact of the project. At the same time, funders need to understand which aspects of impact they should focus on when allocating awards so they can make the most of their investment and bring the greatest benefit to patients and society [ 2 , 4 , 5 , 16 , 17 ].

Box 1. Definitions

• Research impact: ‘any identifiable benefit to, or positive influence on, the economy, society, public policy or services, health, the environment, quality of life, or academia’ (p. 26) [ 3 ].
• Methodological framework: ‘a body of methods, rules and postulates employed by a particular procedure or set of procedures (i.e., framework characteristics and development)’ [ 18 ].
• Pathway: ‘a way of achieving a specified result; a course of action’ [ 19 ].
• Quantitative metrics: ‘a system or standard of [quantitative] measurement’ [ 20 ].
• Narrative metrics: ‘a spoken or written account of connected events; a story’ [ 21 ].

Whilst previous researchers have summarised existing methodological frameworks and impact case studies [ 4 , 22 – 27 ], they have not summarised the metrics for use by researchers, funders, and policy makers. The aim of this review was therefore to (1) identify the methodological frameworks used to measure healthcare research impact using systematic methods, (2) summarise common impact themes and metrics in an impact matrix, and (3) provide a simplified consolidated resource for use by funders, researchers, and policy makers.

Search strategy and selection criteria

Initially, a search strategy was developed to identify the available literature regarding the different methods to measure research impact. The following keywords: ‘Impact’, ‘Framework’, and ‘Research’, and their synonyms, were used during the search of the Medical Literature Analysis and Retrieval System Online (MEDLINE; Ovid) database, the Excerpta Medica Database (EMBASE), the Health Management Information Consortium (HMIC) database, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL+) database (inception to May 2017; see S1 Appendix for the full search strategy). Additionally, the nonindexed Journal of Research Evaluation was hand searched during the same timeframe using the keyword ‘Impact’. Other relevant articles were identified through 3 Internet search engines (Google, Google Scholar, and Google Images) using the keywords ‘Impact’, ‘Framework’, and ‘Research’, with the first 50 results screened. Google Images was searched because different methodological frameworks are summarised in a single image and can easily be identified through this search engine. Finally, additional publications were sought through communication with experts.

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (see S1 PRISMA Checklist ), 2 independent investigators systematically screened for publications describing, evaluating, or utilising a methodological research impact framework within the context of healthcare research [ 28 ]. Papers were eligible if they included full or partial methodological frameworks or pathways to research impact; both primary research and systematic reviews fitting these criteria were included. We included any methodological framework identified (original or modified versions) at the point of first occurrence. In addition, methodological frameworks were included if they were applicable to the healthcare discipline with no need of modification within their structure. We defined ‘methodological framework’ as ‘a body of methods, rules and postulates employed by a particular procedure or set of procedures (i.e., framework characteristics and development)’ [ 18 ], whereas we defined ‘pathway’ as ‘a way of achieving a specified result; a course of action’ [ 19 ]. Studies were excluded if they presented an existing (unmodified) methodological framework previously available elsewhere, did not explicitly describe a methodological framework but rather focused on a single metric (e.g., bibliometric analysis), focused on the impact or effectiveness of interventions rather than that of the research, or presented case study data only. There were no language restrictions.

Data screening

Records were downloaded into Endnote (version X7.3.1), and duplicates were removed. Two independent investigators (SCR and OLA) conducted all screening following a pilot aimed at refining the process. The records were screened by title and abstract before full-text articles of potentially eligible publications were retrieved for evaluation. A full-text screening identified the publications included for data extraction. Discrepancies were resolved through discussion, with the involvement of a third reviewer (MJC, DGK, and TJK) when necessary.

Data extraction and analysis

Data extraction occurred after the final selection of included articles. SCR and OLA independently extracted details of impact methodological frameworks, the country of origin, and the year of publication, as well as the source, the framework description, and the methodology used to develop the framework. Information regarding the methodology used to develop each methodological framework was also extracted from framework webpages where available. Investigators also extracted details regarding each framework’s impact categories and subgroups, along with their proposed time to impact (‘short-term’, ‘mid-term’, or ‘long-term’) and the details of any metrics that had been proposed to measure impact, which are depicted in an impact matrix. The structure of the matrix was informed by the work of M. Buxton and S. Hanney [ 2 ], P. Buykx et al. [ 5 ], S. Kuruvila et al. [ 29 ], and A. Weiss [ 30 ], with the intention of mapping metrics presented in previous methodological frameworks in a concise way. A consensus meeting with MJC, DGK, and TJK was held to solve disagreements and finalise the data extraction process.

Included studies

Our original search strategy identified 359 citations from MEDLINE (Ovid), EMBASE, CINAHL+, HMIC, and the Journal of Research Evaluation, and 101 citations were returned using other sources (Google, Google Images, Google Scholar, and expert communication) (see Fig 1 ) [ 28 ]. In total, we retrieved 54 full-text articles for review. At this stage, 39 articles were excluded, as they did not propose new or modified methodological frameworks. An additional 15 articles were included following the backward and forward citation method. A total of 31 relevant articles were included in the final analysis, of which 24 were articles presenting unique frameworks and the remaining 7 were systematic reviews [ 4 , 22 – 27 ]. The search strategy was rerun on 15 May 2017. A further 19 publications were screened, and 2 were taken forward to full-text screening but were ineligible for inclusion.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pmed.1002370.g001

Methodological framework characteristics

The characteristics of the 24 included methodological frameworks are summarised in Table 1 , 'Methodological framework characteristics’. Fourteen publications proposed academic-orientated frameworks, which focused on measuring academic, societal, economic, and cultural impact using narrative and quantitative metrics [ 2 , 3 , 5 , 8 , 29 , 31 – 39 ]. Five publications focused on assessing the impact of research by focusing on the interaction process between stakeholders and researchers (‘productive interactions’), which is a requirement to achieve research impact. This approach tries to address the issue of attributing research impact to metrics [ 7 , 40 – 43 ]. Two frameworks focused on the importance of partnerships between researchers and policy makers, as a core element to accomplish research impact [ 44 , 45 ]. An additional 2 frameworks focused on evaluating the pathways to impact, i.e., linking processes between research and impact [ 30 , 46 ]. One framework assessed the ability of health technology to influence efficiency of healthcare systems [ 47 ]. Eight frameworks were developed in the UK [ 2 , 3 , 29 , 37 , 39 , 42 , 43 , 45 ], 6 in Canada [ 8 , 33 , 34 , 44 , 46 , 47 ], 4 in Australia [ 5 , 31 , 35 , 38 ], 3 in the Netherlands [ 7 , 40 , 41 ], and 2 in the United States [ 30 , 36 ], with 1 model developed with input from various countries [ 32 ].

https://doi.org/10.1371/journal.pmed.1002370.t001

Methodological framework development

The included methodological frameworks varied in their development process, but there were some common approaches employed. Most included a literature review [ 2 , 5 , 7 , 8 , 31 , 33 , 36 , 37 , 40 – 46 ], although none of them used a recognised systematic method. Most also consulted with various stakeholders [ 3 , 8 , 29 , 31 , 33 , 35 – 38 , 43 , 44 , 46 , 47 ] but used differing methods to incorporate their views, including quantitative surveys [ 32 , 35 , 43 , 46 ], face-to-face interviews [ 7 , 29 , 33 , 35 , 37 , 42 , 43 ], telephone interviews [ 31 , 46 ], consultation [ 3 , 7 , 36 ], and focus groups [ 39 , 43 ]. A range of stakeholder groups were approached across the sample, including principal investigators [ 7 , 29 , 43 ], research end users [ 7 , 42 , 43 ], academics [ 3 , 8 , 39 , 40 , 43 , 46 ], award holders [ 43 ], experts [ 33 , 38 , 39 ], sponsors [ 33 , 39 ], project coordinators [ 32 , 42 ], and chief investigators [ 31 , 35 ]. However, some authors failed to identify the stakeholders involved in the development of their frameworks [ 2 , 5 , 34 , 41 , 45 ], making it difficult to assess their appropriateness. In addition, only 4 of the included papers reported using formal analytic methods to interpret stakeholder responses. These included the Canadian Academy of Health Sciences framework, which used conceptual cluster analysis [ 33 ]. The Research Contribution [ 42 ], Research Impact [ 29 ], and Primary Health Care & Information Service [ 31 ] used a thematic analysis approach. Finally, some authors went on to pilot their framework, which shaped refinements on the methodological frameworks until approval. Methods used to pilot the frameworks included a case study approach [ 2 , 3 , 30 , 32 , 33 , 36 , 40 , 42 , 44 , 45 ], contrasting results against available literature [ 29 ], the use of stakeholders’ feedback [ 7 ], and assessment tools [ 35 , 46 ].

Major impact categories

1. primary research-related impact..

A number of methodological frameworks advocated the evaluation of ‘research-related impact’. This encompassed content related to the generation of new knowledge, knowledge dissemination, capacity building, training, leadership, and the development of research networks. These outcomes were considered the direct or primary impacts of a research project, as these are often the first evidenced returns [ 30 , 62 ].

A number of subgroups were identified within this category, with frameworks supporting the collection of impact data across the following constructs: ‘research and innovation outcomes’; ‘dissemination and knowledge transfer’; ‘capacity building, training, and leadership’; and ‘academic collaborations, research networks, and data sharing’.

1 . 1 . Research and innovation outcomes . Twenty of the 24 frameworks advocated the evaluation of ‘research and innovation outcomes’ [ 2 , 3 , 5 , 7 , 8 , 29 – 39 , 41 , 43 , 44 , 46 ]. This subgroup included the following metrics: number of publications; number of peer-reviewed articles (including journal impact factor); citation rates; requests for reprints, number of reviews, and meta-analysis; and new or changes in existing products (interventions or technology), patents, and research. Additionally, some frameworks also sought to gather information regarding ‘methods/methodological contributions’. These advocated the collection of systematic reviews and appraisals in order to identify gaps in knowledge and determine whether the knowledge generated had been assessed before being put into practice [ 29 ].

1 . 2 . Dissemination and knowledge transfer . Nineteen of the 24 frameworks advocated the assessment of ‘dissemination and knowledge transfer’ [ 2 , 3 , 5 , 7 , 29 – 32 , 34 – 43 , 46 ]. This comprised collection of the following information: number of conferences, seminars, workshops, and presentations; teaching output (i.e., number of lectures given to disseminate the research findings); number of reads for published articles; article download rate and number of journal webpage visits; and citations rates in nonjournal media such as newspapers and mass and social media (i.e., Twitter and blogs). Furthermore, this impact subgroup considered the measurement of research uptake and translatability and the adoption of research findings in technological and clinical applications and by different fields. These can be measured through patents, clinical trials, and partnerships between industry and business, government and nongovernmental organisations, and university research units and researchers [ 29 ].

1 . 3 . Capacity building , training , and leadership . Fourteen of 24 frameworks suggested the evaluation of ‘capacity building, training, and leadership’ [ 2 , 3 , 5 , 8 , 29 , 31 – 35 , 39 – 41 , 43 ]. This involved collecting information regarding the number of doctoral and postdoctoral studentships (including those generated as a result of the research findings and those appointed to conduct the research), as well as the number of researchers and research-related staff involved in the research projects. In addition, authors advocated the collection of ‘leadership’ metrics, including the number of research projects managed and coordinated and the membership of boards and funding bodies, journal editorial boards, and advisory committees [ 29 ]. Additional metrics in this category included public recognition (number of fellowships and awards for significant research achievements), academic career advancement, and subsequent grants received. Lastly, the impact metric ‘research system management’ comprised the collection of information that can lead to preserving the health of the population, such as modifying research priorities, resource allocation strategies, and linking health research to other disciplines to maximise benefits [ 29 ].

1 . 4 . Academic collaborations , research networks , and data sharing . Lastly, 10 of the 24 frameworks advocated the collection of impact data regarding ‘academic collaborations (internal and external collaborations to complete a research project), research networks, and data sharing’ [ 2 , 3 , 5 , 7 , 29 , 34 , 37 , 39 , 41 , 43 ].

2. Influence on policy making.

Methodological frameworks addressing this major impact category focused on measurable improvements within a given knowledge base and on interactions between academics and policy makers, which may influence policy-making development and implementation. The returns generated in this impact category are generally considered as intermediate or midterm (1 to 3 years). These represent an important interim stage in the process towards the final expected impacts, such as quantifiable health improvements and economic benefits, without which policy change may not occur [ 30 , 62 ]. The following impact subgroups were identified within this category: ‘type and nature of policy impact’, ‘level of policy making’, and ‘policy networks’.

2 . 1 . Type and nature of policy impact . The most common impact subgroup, mentioned in 18 of the 24 frameworks, was ‘type and nature of policy impact’ [ 2 , 7 , 29 – 38 , 41 – 43 , 45 – 47 ]. Methodological frameworks addressing this subgroup stressed the importance of collecting information regarding the influence of research on policy (i.e., changes in practice or terminology). For instance, a project looking at trafficked adolescents and women (2003) influenced the WHO guidelines (2003) on ethics regarding this particular group [ 17 , 21 , 63 ].

2 . 2 . Level of policy impact . Thirteen of 24 frameworks addressed aspects surrounding the need to record the ‘level of policy impact’ (international, national, or local) and the organisations within a level that were influenced (local policy makers, clinical commissioning groups, and health and wellbeing trusts) [ 2 , 5 , 8 , 29 , 31 , 34 , 38 , 41 , 43 – 47 ]. Authors considered it important to measure the ‘level of policy impact’ to provide evidence of collaboration, coordination, and efficiency within health organisations and between researchers and health organisations [ 29 , 31 ].

2 . 3 . Policy networks . Five methodological frameworks highlighted the need to collect information regarding collaborative research with industry and staff movement between academia and industry [ 5 , 7 , 29 , 41 , 43 ]. A policy network emphasises the relationship between policy communities, researchers, and policy makers. This relationship can influence and lead to incremental changes in policy processes [ 62 ].

3. Health and health systems impact.

A number of methodological frameworks advocated the measurement of impacts on health and healthcare systems across the following impact subgroups: ‘quality of care and service delivering’, ‘evidence-based practice’, ‘improved information and health information management’, ‘cost containment and effectiveness’, ‘resource allocation’, and ‘health workforce’.

3 . 1 . Quality of care and service delivery . Twelve of the 24 frameworks highlighted the importance of evaluating ‘quality of care and service delivery’ [ 2 , 5 , 8 , 29 – 31 , 33 – 36 , 41 , 47 ]. There were a number of suggested metrics that could be potentially used for this purpose, including health outcomes such as quality-adjusted life years (QALYs), patient-reported outcome measures (PROMs), patient satisfaction and experience surveys, and qualitative data on waiting times and service accessibility.

3 . 2 . Evidence-based practice . ‘Evidence-based practice’, mentioned in 5 of the 24 frameworks, refers to making changes in clinical diagnosis, clinical practice, treatment decisions, or decision making based on research evidence [ 5 , 8 , 29 , 31 , 33 ]. The suggested metrics to demonstrate evidence-based practice were adoption of health technologies and research outcomes to improve the healthcare systems and inform policies and guidelines [ 29 ].

3 . 3 . Improved information and health information management . This impact subcategory, mentioned in 5 of the 24 frameworks, refers to the influence of research on the provision of health services and management of the health system to prevent additional costs [ 5 , 29 , 33 , 34 , 38 ]. Methodological frameworks advocated the collection of health system financial, nonfinancial (i.e., transport and sociopolitical implications), and insurance information in order to determine constraints within a health system.

3 . 4 . Cost containment and cost-effectiveness . Six of the 24 frameworks advocated the subcategory ‘cost containment and cost-effectiveness’ [ 2 , 5 , 8 , 17 , 33 , 36 ]. ‘Cost containment’ comprised the collection of information regarding how research has influenced the provision and management of health services and its implication in healthcare resource allocation and use [ 29 ]. ‘Cost-effectiveness’ refers to information concerning economic evaluations to assess improvements in effectiveness and health outcomes—for instance, the cost-effectiveness (cost and health outcome benefits) assessment of introducing a new health technology to replace an older one [ 29 , 31 , 64 ].

3 . 5 . Resource allocation . ‘Resource allocation’, mentioned in 6frameworks, can be measured through 2 impact metrics: new funding attributed to the intervention in question and equity while allocating resources, such as improved allocation of resources at an area level; better targeting, accessibility, and utilisation; and coverage of health services [ 2 , 5 , 29 , 31 , 45 , 47 ]. The allocation of resources and targeting can be measured through health services research reports, with the utilisation of health services measured by the probability of providing an intervention when needed, the probability of requiring it again in the future, and the probability of receiving an intervention based on previous experience [ 29 , 31 ].

3 . 6 . Health workforce . Lastly, ‘health workforce’, present in 3 methodological frameworks, refers to the reduction in the days of work lost because of a particular illness [ 2 , 5 , 31 ].

4. Health-related and societal impact.

Three subgroups were included in this category: ‘health literacy’; ‘health knowledge, attitudes, and behaviours’; and ‘improved social equity, inclusion, or cohesion’.

4 . 1 . Health knowledge , attitudes , and behaviours . Eight of the 24 frameworks suggested the assessment of ‘health knowledge, attitudes, behaviours, and outcomes’, which could be measured through the evaluation of levels of public engagement with science and research (e.g., National Health Service (NHS) Choices end-user visit rate) or by using focus groups to analyse changes in knowledge, attitudes, and behaviour among society [ 2 , 5 , 29 , 33 – 35 , 38 , 43 ].

4 . 2 . Improved equity , inclusion , or cohesion and human rights . Other methodological frameworks, 4 of the 24, suggested capturing improvements in equity, inclusion, or cohesion and human rights. Authors suggested these could be using a resource like the United Nations Millennium Development Goals (MDGs) (superseded by Sustainable Development Goals [SDGs] in 2015) and human rights [ 29 , 33 , 34 , 38 ]. For instance, a cluster-randomised controlled trial in Nepal, which had female participants, has demonstrated the reduction of neonatal mortality through the introduction of maternity health care, distribution of delivery kits, and home visits. This illustrates how research can target vulnerable and disadvantaged groups. Additionally, this research has been introduced by the World Health Organisation to achieve the MDG ‘improve maternal health’ [ 16 , 29 , 65 ].

4 . 3 . Health literacy . Some methodological frameworks, 3 of the 24, focused on tracking changes in the ability of patients to make informed healthcare decisions, reduce health risks, and improve quality of life, which were demonstrably linked to a particular programme of research [ 5 , 29 , 43 ]. For example, a systematic review showed that when HIV health literacy/knowledge is spread among people living with the condition, antiretroviral adherence and quality of life improve [ 66 ].

5. Broader economic impacts.

Some methodological frameworks, 9 of 24, included aspects related to the broader economic impacts of health research—for example, the economic benefits emerging from the commercialisation of research outputs [ 2 , 5 , 29 , 31 , 33 , 35 , 36 , 38 , 67 ]. Suggested metrics included the amount of funding for research and development (R&D) that was competitively awarded by the NHS, medical charities, and overseas companies. Additional metrics were income from intellectual property, spillover effects (any secondary benefit gained as a repercussion of investing directly in a primary activity, i.e., the social and economic returns of investing on R&D) [ 33 ], patents granted, licences awarded and brought to the market, the development and sales of spinout companies, research contracts, and income from industry.

The benefits contained within the categories ‘health and health systems impact’, ‘health-related and societal impact’, and ‘broader economic impacts’ are considered the expected and final returns of the resources allocated in healthcare research [ 30 , 62 ]. These benefits commonly arise in the long term, beyond 5 years according to some authors, but there was a recognition that this could differ depending on the project and its associated research area [ 4 ].

Data synthesis

Five major impact categories were identified across the 24 included methodological frameworks: (1) ‘primary research-related impact’, (2) ‘influence on policy making’, (3) ‘health and health systems impact’, (4) ‘health-related and societal impact’, and (5) ‘broader economic impact’. These major impact categories were further subdivided into 16 impact subgroups. The included publications proposed 80 different metrics to measure research impact. This impact typology synthesis is depicted in ‘the impact matrix’ ( Fig 2 and Fig 3 ).

CIHR, Canadian Institutes of Health Research; HTA, Health Technology Assessment; PHC RIS, Primary Health Care Research & Information Service; RAE, Research Assessment Exercise; RQF, Research Quality Framework.

https://doi.org/10.1371/journal.pmed.1002370.g002

AIHS, Alberta Innovates—Health Solutions; CAHS, Canadian Institutes of Health Research; IOM, Impact Oriented Monitoring; REF, Research Excellence Framework; SIAMPI, Social Impact Assessment Methods for research and funding instruments through the study of Productive Interactions between science and society.

https://doi.org/10.1371/journal.pmed.1002370.g003

Commonality and differences across frameworks

The ‘Research Impact Framework’ and the ‘Health Services Research Impact Framework’ were the models that encompassed the largest number of the metrics extracted. The most dominant methodological framework was the Payback Framework; 7 other methodological framework models used the Payback Framework as a starting point for development [ 8 , 29 , 31 – 35 ]. Additional methodological frameworks that were commonly incorporated into other tools included the CIHR framework, the CAHS model, the AIHS framework, and the Exchange model [ 8 , 33 , 34 , 44 ]. The capture of ‘research-related impact’ was the most widely advocated concept across methodological frameworks, illustrating the importance with which primary short-term impact outcomes were viewed by the included papers. Thus, measurement of impact via number of publications, citations, and peer-reviewed articles was the most common. ‘Influence on policy making’ was the predominant midterm impact category, specifically the subgroup ‘type and nature of policy impact’, in which frameworks advocated the measurement of (i) changes to legislation, regulations, and government policy; (ii) influence and involvement in decision-making processes; and (iii) changes to clinical or healthcare training, practice, or guidelines. Within more long-term impact measurement, the evaluations of changes in the ‘quality of care and service delivery’ were commonly advocated.

In light of the commonalities and differences among the methodological frameworks, the ‘pathways to research impact’ diagram ( Fig 4 ) was developed to provide researchers, funders, and policy makers a more comprehensive and exhaustive way to measure healthcare research impact. The diagram has the advantage of assorting all the impact metrics proposed by previous frameworks and grouping them into different impact subgroups and categories. Prospectively, this global picture will help researchers, funders, and policy makers plan strategies to achieve multiple pathways to impact before carrying the research out. The analysis of the data extraction and construction of the impact matrix led to the development of the ‘pathways to research impact’ diagram ( Fig 4 ). The diagram aims to provide an exhaustive and comprehensive way of tracing research impact by combining all the impact metrics presented by the different 24 frameworks, grouping those metrics into different impact subgroups, and grouping these into broader impact categories.

NHS, National Health Service; PROM, patient-reported outcome measure; QALY, quality-adjusted life year; R&D, research and development.

https://doi.org/10.1371/journal.pmed.1002370.g004

This review has summarised existing methodological impact frameworks together for the first time using systematic methods ( Fig 4 ). It allows researchers and funders to consider pathways to impact at the design stage of a study and to understand the elements and metrics that need to be considered to facilitate prospective assessment of impact. Users do not necessarily need to cover all the aspects of the methodological framework, as every research project can impact on different categories and subgroups. This review provides information that can assist researchers to better demonstrate impact, potentially increasing the likelihood of conducting impactful research and reducing research waste. Existing reviews have not presented a methodological framework that includes different pathways to impact, health impact categories, subgroups, and metrics in a single methodological framework.

Academic-orientated frameworks included in this review advocated the measurement of impact predominantly using so-called ‘quantitative’ metrics—for example, the number of peer-reviewed articles, journal impact factor, and citation rates. This may be because they are well-established measures, relatively easy to capture and objective, and are supported by research funding systems. However, these metrics primarily measure the dissemination of research finding rather than its impact [ 30 , 68 ]. Whilst it is true that wider dissemination, especially when delivered via world-leading international journals, may well lead eventually to changes in healthcare, this is by no means certain. For instance, case studies evaluated by Flinders University of Australia demonstrated that some research projects with non-peer-reviewed publications led to significant changes in health policy, whilst the studies with peer-reviewed publications did not result in any type of impact [ 68 ]. As a result, contemporary literature has tended to advocate the collection of information regarding a variety of different potential forms of impact alongside publication/citations metrics [ 2 , 3 , 5 , 7 , 8 , 29 – 47 ], as outlined in this review.

The 2014 REF exercise adjusted UK university research funding allocation based on evidence of the wider impact of research (through case narrative studies and quantitative metrics), rather than simply according to the quality of research [ 12 ]. The intention was to ensure funds were directed to high-quality research that could demonstrate actual realised benefit. The inclusion of a mixed-method approach to the measurement of impact in the REF (narrative and quantitative metrics) reflects a widespread belief—expressed by the majority of authors of the included methodological frameworks in the review—that individual quantitative impact metrics (e.g., number of citations and publications) do not necessary capture the complexity of the relationships involved in a research project and may exclude measurement of specific aspects of the research pathway [ 10 , 12 ].

Many of the frameworks included in this review advocated the collection of a range of academic, societal, economic, and cultural impact metrics; this is consistent with recent recommendations from the Stern review [ 10 ]. However, a number of these metrics encounter research ‘lag’: i.e., the time between the point at which the research is conducted and when the actual benefits arise [ 69 ]. For instance, some cardiovascular research has taken up to 25 years to generate impact [ 70 ]. Likewise, the impact may not arise exclusively from a single piece of research. Different processes (such as networking interactions and knowledge and research translation) and multiple individuals and organisations are often involved [ 4 , 71 ]. Therefore, attributing the contribution made by each of the different actors involved in the process can be a challenge [ 4 ]. An additional problem associated to attribution is the lack of evidence to link research and impact. The outcomes of research may emerge slowly and be absorbed gradually. Consequently, it is difficult to determine the influence of research in the development of a new policy, practice, or guidelines [ 4 , 23 ].

A further problem is that impact evaluation is conducted ‘ex post’, after the research has concluded. Collecting information retrospectively can be an issue, as the data required might not be available. ‘ex ante’ assessment is vital for funding allocation, as it is necessary to determine the potential forthcoming impact before research is carried out [ 69 ]. Additionally, ex ante evaluation of potential benefit can overcome the issues regarding identifying and capturing evidence, which can be used in the future [ 4 ]. In order to conduct ex ante evaluation of potential benefit, some authors suggest the early involvement of policy makers in a research project coupled with a well-designed strategy of dissemination [ 40 , 69 ].

Providing an alternate view, the authors of methodological frameworks such as the SIAMPI, Contribution Mapping, Research Contribution, and the Exchange model suggest that the problems of attribution are a consequence of assigning the impact of research to a particular impact metric [ 7 , 40 , 42 , 44 ]. To address these issues, these authors propose focusing on the contribution of research through assessing the processes and interactions between stakeholders and researchers, which arguably take into consideration all the processes and actors involved in a research project [ 7 , 40 , 42 , 43 ]. Additionally, contributions highlight the importance of the interactions between stakeholders and researchers from an early stage in the research process, leading to a successful ex ante and ex post evaluation by setting expected impacts and determining how the research outcomes have been utilised, respectively [ 7 , 40 , 42 , 43 ]. However, contribution metrics are generally harder to measure in comparison to academic-orientated indicators [ 72 ].

Currently, there is a debate surrounding the optimal methodological impact framework, and no tool has proven superior to another. The most appropriate methodological framework for a given study will likely depend on stakeholder needs, as each employs different methodologies to assess research impact [ 4 , 37 , 41 ]. This review allows researchers to select individual existing methodological framework components to create a bespoke tool with which to facilitate optimal study design and maximise the potential for impact depending on the characteristic of their study ( Fig 2 and Fig 3 ). For instance, if researchers are interested in assessing how influential their research is on policy making, perhaps considering a suite of the appropriate metrics drawn from multiple methodological frameworks may provide a more comprehensive method than adopting a single methodological framework. In addition, research teams may wish to use a multidimensional approach to methodological framework development, adopting existing narratives and quantitative metrics, as well as elements from contribution frameworks. This approach would arguably present a more comprehensive method of impact assessment; however, further research is warranted to determine its effectiveness [ 4 , 69 , 72 , 73 ].

Finally, it became clear during this review that the included methodological frameworks had been constructed using varied methodological processes. At present, there are no guidelines or consensus around the optimal pathway that should be followed to develop a robust methodological framework. The authors believe this is an area that should be addressed by the research community, to ensure future frameworks are developed using best-practice methodology.

For instance, the Payback Framework drew upon a literature review and was refined through a case study approach. Arguably, this approach could be considered inferior to other methods that involved extensive stakeholder involvement, such as the CIHR framework [ 8 ]. Nonetheless, 7 methodological frameworks were developed based upon the Payback Framework [ 8 , 29 , 31 – 35 ].

Limitations

The present review is the first to summarise systematically existing impact methodological frameworks and metrics. The main limitation is that 50% of the included publications were found through methods other than bibliographic databases searching, indicating poor indexing. Therefore, some relevant articles may not have been included in this review if they failed to indicate the inclusion of a methodological impact framework in their title/abstract. We did, however, make every effort to try to find these potentially hard-to-reach publications, e.g., through forwards/backwards citation searching, hand searching reference lists, and expert communication. Additionally, this review only extracted information regarding the methodology followed to develop each framework from the main publication source or framework webpage. Therefore, further evaluations may not have been included, as they are beyond the scope of the current paper. A further limitation was that although our search strategy did not include language restrictions, we did not specifically search non-English language databases. Thus, we may have failed to identify potentially relevant methodological frameworks that were developed in a non-English language setting.

In conclusion, the measurement of research impact is an essential exercise to help direct the allocation of limited research resources, to maximise benefit, and to help minimise research waste. This review provides a collective summary of existing methodological impact frameworks and metrics, which funders may use to inform the measurement of research impact and researchers may use to inform study design decisions aimed at maximising the short-, medium-, and long-term impact of their research.

Supporting information

S1 appendix. search strategy..

https://doi.org/10.1371/journal.pmed.1002370.s001

S1 PRISMA Checklist. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist.

https://doi.org/10.1371/journal.pmed.1002370.s002

Acknowledgments

We would also like to thank Mrs Susan Bayliss, Information Specialist, University of Birmingham, and Mrs Karen Biddle, Research Secretary, University of Birmingham.

• View Article
• PubMed/NCBI
• Google Scholar
• 3. HEFCE. REF 2014: Assessment framework and guidance on submissions 2011 [cited 2016 15 Feb]. Available from: http://www.ref.ac.uk/media/ref/content/pub/assessmentframeworkandguidanceonsubmissions/GOS%20including%20addendum.pdf .
• 8. Canadian Institutes of Health Research. Developing a CIHR framework to measure the impact of health research 2005 [cited 2016 26 Feb]. Available from: http://publications.gc.ca/collections/Collection/MR21-65-2005E.pdf .
• 9. HEFCE. HEFCE allocates £3.97 billion to universities and colleges in England for 2015–1 2015. Available from: http://www.hefce.ac.uk/news/newsarchive/2015/Name,103785,en.html .
• 10. Stern N. Building on Success and Learning from Experience—An Independent Review of the Research Excellence Framework 2016 [cited 2016 05 Aug]. Available from: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/541338/ind-16-9-ref-stern-review.pdf .
• 11. Matthews D. REF sceptic to lead review into research assessment: Times Higher Education; 2015 [cited 2016 21 Apr]. Available from: https://www.timeshighereducation.com/news/ref-sceptic-lead-review-research-assessment .
• 12. HEFCE. The Metric Tide—Report of the Independent Review of the Role of Metrics in Research Assessment and Management 2015 [cited 2016 11 Aug]. Available from: http://www.hefce.ac.uk/media/HEFCE,2014/Content/Pubs/Independentresearch/2015/The,Metric,Tide/2015_metric_tide.pdf .
• 14. LSE Public Policy Group. Maximizing the impacts of your research: A handbook for social scientists. http://www.lse.ac.uk/government/research/resgroups/LSEPublicPolicy/Docs/LSE_Impact_Handbook_April_2011.pdf . London: LSE; 2011.
• 15. HEFCE. Consultation on the second Research Excellence Framework. 2016.
• 18. Merriam-Webster Dictionary 2017. Available from: https://www.merriam-webster.com/dictionary/methodology .
• 19. Oxford Dictionaries—pathway 2016 [cited 2016 19 June]. Available from: http://www.oxforddictionaries.com/definition/english/pathway .
• 20. Oxford Dictionaries—metric 2016 [cited 2016 15 Sep]. Available from: https://en.oxforddictionaries.com/definition/metric .
• 21. WHO. WHO Ethical and Safety Guidelines for Interviewing Trafficked Women 2003 [cited 2016 29 July]. Available from: http://www.who.int/mip/2003/other_documents/en/Ethical_Safety-GWH.pdf .
• 31. Kalucy L, et al. Primary Health Care Research Impact Project: Final Report Stage 1 Adelaide: Primary Health Care Research & Information Service; 2007 [cited 2016 26 Feb]. Available from: http://www.phcris.org.au/phplib/filedownload.php?file=/elib/lib/downloaded_files/publications/pdfs/phcris_pub_3338.pdf .
• 33. Canadian Academy of Health Sciences. Making an impact—A preferred framework and indicators to measure returns on investment in health research 2009 [cited 2016 26 Feb]. Available from: http://www.cahs-acss.ca/wp-content/uploads/2011/09/ROI_FullReport.pdf .
• 39. HEFCE. RAE 2008—Guidance in submissions 2005 [cited 2016 15 Feb]. Available from: http://www.rae.ac.uk/pubs/2005/03/rae0305.pdf .
• 41. Royal Netherlands Academy of Arts and Sciences. The societal impact of applied health research—Towards a quality assessment system 2002 [cited 2016 29 Feb]. Available from: https://www.knaw.nl/en/news/publications/the-societal-impact-of-applied-health-research/@@download/pdf_file/20021098.pdf .
• 48. Weiss CH. Using social research in public policy making: Lexington Books; 1977.
• 50. Kogan M, Henkel M. Government and research: the Rothschild experiment in a government department: Heinemann Educational Books; 1983.
• 51. Thomas P. The Aims and Outcomes of Social Policy Research. Croom Helm; 1985.
• 52. Bulmer M. Social Science Research and Government: Comparative Essays on Britain and the United States: Cambridge University Press; 2010.
• 53. Booth T. Developing Policy Research. Aldershot, Gower1988.
• 55. Kalucy L, et al Exploring the impact of primary health care research Stage 2 Primary Health Care Research Impact Project Adelaide: Primary Health Care Research & Information Service (PHCRIS); 2009 [cited 2016 26 Feb]. Available from: http://www.phcris.org.au/phplib/filedownload.php?file=/elib/lib/downloaded_files/publications/pdfs/phcris_pub_8108.pdf .
• 56. CHSRF. Canadian Health Services Research Foundation 2000. Health Services Research and Evidence-based Decision Making [cited 2016 February]. Available from: http://www.cfhi-fcass.ca/migrated/pdf/mythbusters/EBDM_e.pdf .
• 58. W.K. Kellogg Foundation. Logic Model Development Guide 2004 [cited 2016 19 July]. Available from: http://www.smartgivers.org/uploads/logicmodelguidepdf.pdf .
• 59. United Way of America. Measuring Program Outcomes: A Practical Approach 1996 [cited 2016 19 July]. Available from: https://www.bttop.org/sites/default/files/public/W.K.%20Kellogg%20LogicModel.pdf .
• 60. Nutley S, Percy-Smith J and Solesbury W. Models of research impact: a cross sector review of literature and practice. London: Learning and Skills Research Centre 2003.
• 61. Spaapen J, van Drooge L. SIAMPI final report [cited 2017 Jan]. Available from: http://www.siampi.eu/Content/SIAMPI_Final%20report.pdf .
• 63. LSHTM. The Health Risks and Consequences of Trafficking in Women and Adolescents—Findings from a European Study 2003 [cited 2016 29 July]. Available from: http://www.oas.org/atip/global%20reports/zimmerman%20tip%20health.pdf .
• 70. Russell G. Response to second HEFCE consultation on the Research Excellence Framework 2009 [cited 2016 04 Apr]. Available from: http://russellgroup.ac.uk/media/5262/ref-consultation-response-final-dec09.pdf .

Health Care Policy Essays

Development of health care policy in great britain.

The growth of healthcare policy in the last century has been shaped by numerous factors. These aspects include social, economic, and political elements: poverty, de-industrialization, and various political ideologies. Social attitudes changing over the nineteenth and twentieth centuries were the major driving force for the advancement of healthcare policies. In the early 1900s, attitudes were changing and people were becoming more knowledgeable about social issues within the country. The Boer War and both World Wars had shown politicians that the […]

A Study and Implementation of a New Health Care Policy in Logan County

Introduction Community health care is a crucial component for all communities, particularly those that are underprivileged. I am keen on reviewing a new healthcare plan for Logan County. The CDC defines a "plan" as a rule, regulation, treatment, administrative activity, incentive, or volunteer method of governments and other organizations" (CDC, 2015). I propose an incentive plan for the community. This plan involves a membership fee instead of traditional insurance coverage. According to the most recent census, Logan County has approximately […]

The Complicated Healthcare Policy in the United States

Nowadays, healthcare policy is more difficult than ever before, with many policies and regulations by federal government and health insurance firms. These concerns pose great challenges and obstacles in healthcare, making nurses' jobs much more demanding. Unfortunately, most of the time, patients and nurses are the ones caught between cost restraints and access to high-quality care (Premji & Hatfield, 2016). America is arguably one of the countries with the highest quality of care, but these policies negatively impact patient outcomes. […]

The Need for a Reform of the American Health Care Policy

Many leaders of our fantastic nation have tried to develop a plan that can care for Americans, particularly when it involves the rising rates of health care and insurance premiums. "Virtually one in every six Americans has no medical insurance, health care costs are escalating quickly, management costs are too high, and medical mistakes are widespread" (Fuchs, Emmanuel). Nevertheless, many Americans have disagreed over the nature of the Affordable Care Act and whether it will help or harm Americans, creating […]

A Report on the Personal Experience with the Best Guide to Meditation and Health Care Policy

Through reading "The Best Guide to Meditation," I was able to expand both my knowledge and experience with meditation. The two aspects of this book that I appreciated the most were the instructions on how to effectively meditate, and the description of how meditation is an integral part of many religions and lifestyles in some shape or form. Although I found the first part of the book somewhat helpful in helping me set myself up to successfully meditate, what I […]

We will write an essay sample crafted to your needs.

An Analysis of the Healthcare Policy

Healthcare policy evaluation is an activity or approach created to attain a specific purpose in society. A policy outlines a vision, priorities, and the roles of different groups in its implementation. Additionally, it can be used to curtail diseases that affect individuals, such as obesity. Obesity is a health issue that affects a significant number of Americans, particularly the younger generation (Marmor, 1994). Maryland, a state in America, has developed a strategy to combat obesity by implementing a healthcare policy […]

A Study on the Best Approaches to Public Health Care Policy

The healthcare industry continues to be impacted and evolve based on advances in technology, as well as new approaches to healthcare treatment shaped by outside influences, such as the federal government, HMOs and insurance provider policies. The rapid changes emerging have presented challenges and great opportunities for growth and innovation for healthcare policy and practitioners in the United States, as well as those abroad in Europe and Canada (McArthur, 1997). From these locations, medical practitioners, academics, and adjunct professionals have […]

Additional Example Essays

• Childhood obesity parents are the blame
• Arguments For and Against Euthanasia
• Importance of Mental Health
• Diagnosing Bipolar Disorder
• Substance Abuse and Mental Illnesses
• Drug Abuse Resistance Education for Drug-Free Future
• Social Media and Eating Disorders: Unveiling the Impact
• Economic Benefits Of Euthanasia
• Teenage Drug Abuse
• Does Stress Cause Illness: Unveiling the Link
• Poverty and Drug Abuse Addiction
• Why Abortion Should be Illegal

1. Tell Us Your Requirements

2. Pick your perfect writer

3. Get Your Paper and Pay

short deadlines

100% Plagiarism-Free

Certified writers

Health Care as an Essential Public Policy Research Paper

Introduction, health care public policy problem: the scope and nature, public policy evolution, actors in evaluation, the intergovernmental structure and political concerns, the approaches to policy setting, the suggested policy direction that is supported by research.

We will write a custom Research Paper on Health Care as an Essential Public Policy specifically for you for only 9.35/page

808 certified writers online

Public policy is the actions taken by the government and the goals that influence those actions. Public policies affect individuals in many ways, ranging from health, economic, environmental, and educational factors (Stewart, Hedge, & Lister, 2007). Health care is seen as an essential public policy.

Health care is evaluated or assessed on the aspects of publicly provided health care to the citizens of a given country. The welfare herein comprises of both curative and preventive measures, both of which are tailored towards achieving the set policies that concern the general public.

This is done by analyzing the combination of local level data and information from the public health and their welfare; individual levels of data and information are also used in the analysis. The individual data in this case is based on the how satisfactory life is, the main interest being on the health care policy.

On the broader spectrum, huge expenditures on health care systems are directly related to the life’s satisfaction derived by individuals and the general public, the generational effects being the baseline of the benefits of the public policy adopted for the variant groups and the diverse needs that need to be met in the health care sector.

The combination of the fundamental aspect of health policy can be used to ascertain the theoretical hypotheses generated from welfare effects on public health provision and how these effects differ across the different groups of population.

It is important to note that health care policy evaluation is dependent on the individuals’ political orientation, which consequently yields differences in the opinion of assessment of the problems in the public health care system policies. This research paper seeks “to address the operation ability of the health care welfare policy.

It further considers the problems associated with it as a public policy, with the evolution and evaluation of the policy being of the main focus.

These interests are assessed on the basis of how the health policy is structured to deal with emerging issues in the sector, alongside the policies and measures put in place to ensure its ability to perform, and approaches and recommendations that oversee its long term sustainability with research incorporated”.

The issue of health care affects everyone, ranging from families worrying about their children to government officials being worried about the increasing cost of health care. Workers, doctors, and hospitals are also concerned with the responsibility of delivering proper health care.

The value of Health care services determines the welfare state associated with them. Health care policy is considered a public policy since it is by greater extent provided by the government through the relevant agencies due to the externalities associated with it, if it is provided through the normal market model.

It is therefore non-rival and non-excludable from any individual in the population. Most of these services are mostly offered for free or at highly subsidized prices by the government (Williams & Torrens, 2007).

The welfare associated with the provision of medical care and services constitute public policy problem in this concept. An attempt to value public goods is more or less complex, and consequently requires special treatment of variables considered.

The welfare measure of any health system is followed by preference methodology from the participants in that particular package. Assessing the welfare herein is based on the individuals’ life satisfaction and health status derived from health care.

It is important to note that health is a derived demand rather than a direct demand. Health is not directly purchased, but it is rather achieved through consumption of health care services (Frey and Stutzer, 2005).

The use of life satisfaction to analyze how well a given health policy is also useful in the assessment of the contribution of private sector in the health system, thereby presenting the applicability of the private goods in the health system.

In both public and private health concerns, the bottom line is that the happiness or satisfaction derived from the activities of both parties constitutes the objective that the public policies for health care purport to play.

For the challenges faced therein, counter measures are formulated and implemented based on the already available data on public health care services and the expected achievements for the sector, right from the goals and mission of such policies.

The major problem in the assessment of the welfare of health care services and the general public policies developed for such purposes is that the value to assign with the general feeling of the individuals is difficult to ascertain.

It has been evident in other studies that the Haw-Thorne effect makes it difficult for individuals to respond to stimulus, especially when they realize the data is meant to achieve some results for the health sector (Bjornskoy, Dreher, and Fisher, 2007). Therefore, they determine how policies are to be structures, either positively or negatively.

Health care policy formulation and implementation has been characterized by government’s interests since mid-1970s. These concerns were tailored by the objective of the governments to improve the welfare of the larger population in a country.

Health care systems have been viewed as primary legal and objective tools that effectively communicate needs and achievements of both the government and the population for whom these policies are meant to serve. On the same note, health care professionals have played an important role in the determination of end-of-life interests for the population since that time (Reeve & Peerbhoy, 2007).

The interaction of all parties involved in the process spell out the goals, objectives and proper instructions to be followed in the development of a health care system.

Further, a proxy decision maker is identified by the rules and regulations that govern the system, especially in times of incapacity, so as to ensure the coherence in the general interest of pursuing these policies. Over the years, improvement and reforms have been considered the fundamentals of health care policy.

End-of-life legal landscape evolvement and the advance directives laws have provided continuity in the evolution of policies that focus on health care systems and their welfare to the society. Paradigm shifts have also tailored change for the betterment of health sector, alongside statutory backup that traces its roots back in history and further relates that to the present.

Research and development in the health care and health system welfare has led to the emergence of strategies that are tailored towards improving the usefulness and evaluation of usability in the health sector.

The effectiveness and efficiency of the evaluations are dependent on the specific frameworks adopted by the government on the implementation of the health care services and the control over the personnel charged with the responsibility of overseeing the success of the system (Reeve & Peerbhoy, 2007).

Furthermore, evaluation is mainly based on the experimental procedures in the sector, where each stage of the experiment provides an evaluation model of the associated results at that particular stage. Pilot studies can be done before the actual study in to determine the variables that better fit the experimentation and further evaluation of the policies.

Cost s – the cost of evaluating a policy should not exceed the general benefit associated with it to the public and its long term welfare should be based on relatively to the next several generations.

Roles – the evaluation procedure should be tailored towards ascertaining if the policy will actually meet its purpose and how it is sustainable.

Variable relations – public policy evaluation should incorporate all the aspects of the health care system that it purports to serve, determining the relevant relationship among the variables, and consequently outlining how the variables affect each other under different factor treatments that are likely to occur in the health sector.

Health policy is essentially a member states competence. However, the European Union has presently raised some alarm and some uncertainties concerning the way activities are being carried out in both the pharmaceutical industries and public health interests.

An indispensable aspect in the health care policy in the European Union is the balance between the public health and the health care on one hand and industrial policy on the other hand. The public policy approach tries to take great interest on the problems, the actors involved, the resources used, and also on the patterns on interaction in EU’s health policy (Reeve & Peerbhoy, 2007).

The government is implicated to ascertain on the way the decisions are made and implemented, and the impacts the policies within the health care welfare will affect the community. In enhancing better health care to the entire community, it is the role of the government to analyze and select the actors involved in the health sector.

In addition, the government should oversee how different responsibilities and roles have been assigned to different interest groups and whether the requirements are met. It is also in this aspect that the role of national governments and EU institutions is determined and how well they interact within the laid down health care policies (Weible, 2007).

Policies formulated and implemented within health care takes place as a result of the interactive process that happens between numerous key players or actors guided by their own interests and strategies.

Basing on the case of EU and its related health care issues, it is import to note that this is one of the sectors that is composed of different interests in opposition: public health and health care and the industrial policy.

To better understand the EU policy making process and the intergovernmental relations that exist within the health care policy, the interested groups or members have to apply for an advocacy coalition framework (ACF). As specified, this is only within the European Union context.

ACF gives a theoretical understanding of the interaction that subsists between the policy making process and intergovernmental relations within the European Union health care sector. In enhancing an effective and efficient health care, there is a need to have policy subsystem that should be dynamic and has multiple actors who structure their relationship into the advocacy coalition.

The actors involved are also moved by the policy beliefs and to an extent they may try to influence the policies by use of multiple resources and various venues. According to the views provided by ACF, healthy care policies may be perceived as a process that involves competition between a coalition of actors who advocate beliefs about the policy problems and solutions (Gask et al, 2005).

The competition that takes place is essential as it will help in maintaining the social security of the communities within the region that receives its services. Such competition must be placed within policy subsystems to remain effective in rendering services to the communities.

In essence, the policy subsystem may be defined as a set of actors who are actively concerned with implementing an issue and therefore seek to influence the public policy that is directly related to it. However, the pharmaceutical subsystem within the health care system may be polarized between a pro-industry advocacy coalition and an anti-industry advocacy coalition.

The division between these two coalitions is mainly due to their policy preferences: one of the coalitions is mainly aimed at increasing and protecting the pharmaceutical interests while the other coalition is aimed at overseeing that public health provided superimposes the industrial interests.

However, in the process of ensuring that the two coalitions work in conjunction with one another, all in the common goal of providing effective health care services, conflicts may arise.

The conflicts may be driven by normative beliefs and this may make even the implementation of the policies to be difficult. Such a problem may not persist for long, considering that the policies made in such a scenario are EU related and they are therefore established on the bases of consensus. Another advantage is that the political process involved in their formation and implementation is not usually a zero-sum game.

In such a case negotiations are required in the policies made. The basis of making negotiations will depend on the features of the political system and also on particular context factors. For instance, the higher the extent of consensus used in making the policies, the higher the rate of compromise created for incentives for broker’s action across the coalition (Reeve & Peerbhoy, 2005).

In the policy making process, a combination of both the intergovernmental negotiations and supranational centralization is necessary. The commission involved in making policies has a duty to draw up the proposal required, and then a decision on the efficiency of the proposal is passed on by the council members.

The commission is also responsible for the conflicts that may arise out of the decisions that they may have initiated which violate the rights of the council members. In making sure that the rights of the council members are not violated, the commission is compelled to involve the consensus in coming up with quality decisions regarding the policies.

If it is discovered that the policy proposals were reached upon without the involvement of the consensus, they can be blocked by intergovernmental haggling (Scharpf, 2000).

According to this research, it would be essential if the members involved in the health care could be in a position to entirely change the whole system used in rendering services to the patients.

It would also be the responsibility of the commission to strategically ensure that all resources and venues essential for the quality decisions are available to avoid the deadlock.

For quality and effective policies, the commission should also suggest and encourages exchange of information and opinions among the stakeholders, supportive networks, from the public among others (Reeve & Peerbhoy, 2005).

Such changes would be very imperative in enhancing better health care for the interest of the whole public. Therefore, an adequate health care system should have an objective of enabling citizens to access quality health care in a cost effective way. Proper health care can be achieved when there are enough finances to support the costly diagnostic tests and processes, and lengthy stays for inpatients.

It is evident from the above discussion and concepts that investment in health is expensive. In this regard, increasing expenditures are directly proportional to the life satisfaction of the general public. However, differences across the population groups are evident, with the willingness to pay or invest in health varying across the groups.

These differences occur due to the fact that the willingness to pay for publicly provided private services like health is mainly non-monotonic in the level of income of the population. In essence this research paper has addressed “the operation ability of the health care policy.

It further considered the problems associated with it as a public policy, with the evolution and evaluation of the policy being of fundamental interest.

These interests were assessed on the basis of how the health policy is structured to deal with emerging issues in the sector, alongside the policies and measures put in place to ensure its functionality, and approaches and recommendations that oversee its long term sustainability with research incorporated”. In this regard, it is evident that devotion of monetary resources to public service and provision of health care is positively related to the well being of the population.

Bjornskov, C., Dreher, A., and Fischer, J. A. V. (2007). The Bigger the Better? Evidence of the exact of Government Size on Life Satisfaction around the World. Public Choice,130 , 267-292.

Frey, B. S. & Stutzer, A. (2005). Happiness Research: State and Prospects. Review of Social Economy, 62 , 207-228.

Gask, L., Rogers A. D., Oliver, D., May, C., & Roland, M. (2005) A qualitative Study Exploring how General Practitioners Prescribe Antidepressants. British Journal of General Practice, 53, 278-283.

Reeve, J., & Peerbhoy, D. (2007). Evaluating the Evaluation: Understanding the Utility and Limitation of Evaluation as a Tool for Organizational Learning. Health Education Journal, 66 (2),120–131.

Scharpf, F. (2000). Institutions in Comparative Policy Research, Comparative Political Studies, 33 , 762-790.

Stewart, J., Hedge, D. M., & Lester, J. P. (2007). Public Policy: An Evolutionary Approach (3rd ed.). Boston, MA: Thomson Wordsworth.

Weible, C. M. (2007). An Advocacy Coalition Framework Approach to Stakeholder Analysis: Understanding the Political Context of California, Marine Protected Area Policy. Journal of Public Administration Research and Theory, 17 (1), 95-117.

Williams, J., & Torrens, P. (2007). Introduction to Health Services , (7th ed.). Clinton Park, NY: Delmar Thomson Learning.

Need a custom research paper sample written from scratch by professional specifically for you?

807 certified writers online

• Chicago (N-B)
• Chicago (A-D)

IvyPanda. (2020, January 20). Health Care as an Essential Public Policy. https://ivypanda.com/essays/health-care-policy/

IvyPanda. (2020, January 20). Health Care as an Essential Public Policy. Retrieved from https://ivypanda.com/essays/health-care-policy/

"Health Care as an Essential Public Policy." IvyPanda , 20 Jan. 2020, ivypanda.com/essays/health-care-policy/.

1. IvyPanda . "Health Care as an Essential Public Policy." January 20, 2020. https://ivypanda.com/essays/health-care-policy/.

Bibliography

IvyPanda . "Health Care as an Essential Public Policy." January 20, 2020. https://ivypanda.com/essays/health-care-policy/.

IvyPanda . 2020. "Health Care as an Essential Public Policy." January 20, 2020. https://ivypanda.com/essays/health-care-policy/.

IvyPanda . (2020) 'Health Care as an Essential Public Policy'. 20 January.

• Clinical Trial of Tailored Activity and Eating Newsletters with Older Rural Women
• Derived Demand: Productive Factor
• Algae Derived Fuels in the Aviation Industry
• The University of Michigan Cases: Grutter v. Bollinger
• Principal Ways of Financing the Welfare State
• Air France Company's Internet Marketing
• Health Promotion Program Tactics
• Canadian Child Welfare System Evolution
• Commercial Package Policies: Categories, Property Coverage
• The Welfare System
• Legal Concepts in Healthcare: The Fundamental Rights of Clients
• Abortions Legal in the U.S.A
• Legal Aspects of Healthcare Administration
• The Older Americans Act Of 1965
• Health Insurance and Mandatory Requirements

68 Healthcare Policy Essay Topics

🏆 best essay topics on healthcare policy, 👍 good healthcare policy research topics & essay examples, 🎓 most interesting healthcare policy research titles.

• American Healthcare Policies and Nursing Role As the present case demonstrates, it is not always evident for nurses how the process of policy-making develops and correlates with public health stakeholders’ consideration.
• Childhood Vaccination as Healthcare Priority Policy Issue This essay presents the controversial issue of childhood vaccination as a healthcare priority policy issue that requires the immediate attention of legislators.
• Nurses and New Health Care Policy Nursing roles have been already increased and developed considerably, and each new function is the possibility to improve health care for patients and speed up care delivery.
• Medicaid and Michigan Healthcare Policy Medicaid is a program for medical insurance for all ages Americans with a low income funded not only by the federal but also a state government.
• Malnutrition and Patient Safety Healthcare Policy The paper considers patient safety as the health care policy issue of high priority. Especially, it focuses on poor nutrition as the neglected aspect of patient safety.
• Health Care System: Cost Control Policy The main essence of the Michigan policy is that traditional payments for standard medical services are taken into account.
• Long-Term Care Facilities and Healthcare Policy The services included in long-term care are very diverse and involve such forms of care as assisted living, ADC (adult day health care), homemaker services, and nursing home care.
• Health Care Policy in Mercy Miami Hospital This work is an interview with the employees at Mercy Miami Hospital, where underlines the importance of cultural differences as one of the main strengths of the organization.

• High-Quality Healthcare Access: Policy Change The selected policy change revolves around reinforcing the role of nurses as leaders to support the delivery of high-quality medical services to patients.
• Healthcare Reform Policies in the United States Health care reform is an ongoing process whose aim is to transform or improve the quality of services available to different populations.
• Healthcare Policy and Pfizer’s Nigeria Scandal The case of Pfizer’s scandal in Nigeria raises numerous ethical questions. The company was engaged in a number of research malpractices.
• Patient Good Nutrition as a Healthcare Policy The paper identifies patient healthy nutrition as prioritized healthcare policy and defines an approach for communicating with a policymaker regarding this policy.
• Health Technologies in Healthcare Policy The selected public policy for this discussion is the use of health technologies in healthcare. Medical technologies and informatics are currently impacting the quality of medical care.
• Healthcare Policy, Leadership and Performance The paper identifies the healthcare policy priority, approach for communicating with a policymaker, and discusses leadership and performance of healthcare systems.
• Health Care Policy: Florida House Bill 1277 The purpose of this paper is to discuss and analyze the data related to HB 1277 as a healthcare policy-priority issue for Florida and conclude regarding its importance for nursing.
• Healthcare Policy Effects on Individual: Affordable Care Act This paper considers the effects of healthcare policy on individuals and policymaking implications using the example of the Affordable Care Act.
• Nurse Activist: Healthcare Policy and Advocacy Nursing professionals have become empowered to make decisions and question decisions of other healthcare professionals as well as policymakers.
• Advocacy in Nursing: The Process of Healthcare Policymaking Nurses spend most of their time with patients, and thus they understand strengths and limitations of the healthcare system from a broad perspective based on firsthand experience.
• Healthcare Policy Issues: Health Equity One of the main healthcare policy issues that are currently in need of addressing is health equity (HE) (American Public Health Association).
• Home-Based Healthcare Policy and Clinical Practice The analysis of home-based healthcare service can help to consider this approach in detail and identify potential gaps with the goal of eliminating and avoiding them.
• First Steps on Becoming a Grassroots Lobbyist or Advocate for Health Care Policy The Affordable Care Act extended coverage to over 20 million people, introduced new standards, and boosted public health funding.
• Healthcare Policy and Nursing: Affordable Care Act Patient Protection and Affordable Care Act as a healthcare improvement initiative addresses multiple steps aimed at increased insurance and promotion of self-care
• US Healthcare Policy: Obama’s Healthcare Reform President Barak Obama has a hard task ahead in making sure that the health situation of the country is addressed.
• Health Care Policy and Procedure Development Despite the new technologies implementation hospitals face the issue of elaborating on the process of patient transition from one care setting to another manually.
• Health Care Policy and Nurse Practitioner Practice Thus, this paper aims at explaining the meaning of health care policy and how it can impact the nurse practitioner practice.
• Competing Interests in a Health Care Policy The selected issue is in the area of health care policy, as competing interests play a major role in the formulation of a health care policy.
• The Healthcare Policy: Bill H.R. 3340 The bill will contribute to developing nurses’ ability to demonstrate cultural competence towards patients with different values, beliefs, and feelings.
• Healthcare Dashboards: Potential Policies The function of dashboards has been expanding in the well-being area. They need to balance the visual viewpoints and the contained data to be essential for choice help.
• Summary of My Health Care Policy Healthcare is a vital constituent in society. My healthcare policy entails the infusion of quality and affordability through increasing the availability of care processes.
• America’s Healthcare Policy and Obamacare While the Patient Protection and Affordable Care Act does not consolidate America’s healthcare system, it plays a role in addressing inequalities and expanding public coverage.
• Healthcare Policy: Quality vs. Restrained Costs Trying to balance the healthcare budget while at the same time providing high-quality health services is a huge and challenging task for the US government.
• Impact of Healthcare Policy Changes on Health Delivery Medical care systems are formed in order to meet medical. This paper will focus on the impact of the healthcare changes in the past and current health care delivery.
• The Healthcare Policy in the United States This essay looks at the current state of healthcare policies and the suitability of the Patient Protection and Affordable Care Act (PPACA).
• Are Nurses Becoming Influential in Health Care Policymaking? Many people associate politics with the government and political aspirants. However, politics exists in the healthcare systems.
• Media in Healthcare Sector and Policy Speaking about the role of media in the relations between the healthcare sector and policy, one could say that it tends to revolve around various drawbacks peculiar to the given sector.
• Healthcare Policy and Law Discussion Recap This paper is a revisit of the health care law to respond to certain raising issues regarding medical policies and legal regulations.
• National Dialogue on Healthcare Policies The national dialogue on healthcare policy provides a forum for physician-industry collaboration and discussion of critical issues to provide a way forward on emerging issues.
• Health Care: Public Policy Decisions As far as the value of human life is concerned, no dollar value can be placed on it. This can be attributed to an increase in the cost of health care.
• Healthcare Policy Change Implementation Plan The health care system should be continuously evolving. Nevertheless, in the USA, there are several legislation pieces that may provoke potential barriers.
• The Importance of Health Care Policy in Society Health law, policies, and constitutional law are essential to society but when a conflict arises between the systems, it may cause complications in a patient’s health.
• Healthcare System Financing Policy Systems for financing healthcare are critical towards attaining health coverage universally. Raising funds can finance healthcare while focusing on significant barriers reduction.
• Bush, Obama, and Trump: Healthcare Policy The following reflection will discuss how Bush, Obama, and Trump addressed the issues connected to AIDS and HIV.
• “The Importance of Healthcare Policy and Procedures”: The Significance of Policy “The Importance of Healthcare Policy and Procedures” explains the significance of policy in setting the action plan used in guiding decision-making and desired outcomes.
• PPACA: Healthcare Policy Analysis This paper explores and analyses the health care policy under the provisions of the Patient Protection and Affordable Care Act (PPACA).
• ABC Hospital: Health Care Policy This is the policy of the ABC Hospital’s radiology department to provide safe conditions for the patients and personnel connected to radiological procedures within the facility.
• Healthcare Policy: Affordable Healthcare Act In 2010, President Barack Obama implemented the Affordable Care Act, which strived to provide access to medical services for most Americans.
• Advice for Affordable Healthcare Policymakers There is a need for reforms that will make healthcare more affordable, yet not many solutions that have long-term effects on the issue are being implemented.
• Healthcare Policy Influences: COVID-19 Pandemic The research indicates that the impactful aspect of the economy of a nation became the most prominent during the COVID-19 pandemic.
• Healthcare Advocacy and Its Impact on Healthcare Policy
• Congressional Committees and Healthcare Policy
• Healthcare Policy Affecting Access, Cost, and Quality
• What Is Health Policy and What Role Does It Play in Nursing?
• Defining Health and Identifying Influences on Healthcare Policy
• What Is the Current Healthcare Policy in the US?
• The Current Trends and Challenges Within the Healthcare Systems
• Healthcare Policy and Improve Patient Care
• What Is an Example of a Health Policy?
• Healthcare Policy and Complications in the United States
• Population-level Intervention and Information Collection in Dynamic Healthcare Policy
• Healthcare Policy, Finance, and Regulatory Environments
• Market Competition: Implications for Healthcare Policy in the United States
• The Importance of Healthcare Policy and Procedures
• Healthcare Policy: What Is It and Why Is It Important?
• What Is the Most Effective Healthcare System?
• Healthcare Policy Bill and Changes to the Medicare
• What Is the Purpose of a Health Policy?
• Factors Influencing Nurse’s Participation in the Health Policy-making Process
• Healthcare Policy and Economics in the Field of Nursing
• Title generator
• Research question maker

Cite this post

• Chicago (N-B)
• Chicago (A-D)

StudyCorgi. (2023, August 25). 68 Healthcare Policy Essay Topics. Retrieved from https://studycorgi.com/ideas/healthcare-policy-essay-topics/

StudyCorgi. (2023, August 25). 68 Healthcare Policy Essay Topics. https://studycorgi.com/ideas/healthcare-policy-essay-topics/

"68 Healthcare Policy Essay Topics." StudyCorgi , 25 Aug. 2023, studycorgi.com/ideas/healthcare-policy-essay-topics/.

1. StudyCorgi . "68 Healthcare Policy Essay Topics." August 25, 2023. https://studycorgi.com/ideas/healthcare-policy-essay-topics/.

Bibliography

StudyCorgi . "68 Healthcare Policy Essay Topics." August 25, 2023. https://studycorgi.com/ideas/healthcare-policy-essay-topics/.

StudyCorgi . 2023. "68 Healthcare Policy Essay Topics." August 25, 2023. https://studycorgi.com/ideas/healthcare-policy-essay-topics/.

StudyCorgi . (2023) '68 Healthcare Policy Essay Topics'. 25 August.

Health Care Policy Research Paper Topics & Ideas

Published 14 July 2021

Medical students have to deal with a number of research paper topics during their degree in college. Writing research papers on healthcare policy is one of these subjects and students require the best research topics on healthcare to complete such assignments. That is the reason why My Research Topics experts have provided this free list of the latest topics for research papers on healthcare. You will be able to find argumentative research paper topics as well as persuasive and many other types of topics on healthcare policy. These topics can also be used as nursing research paper topics without any issue. So write your university and college research paper by starting with the  research paper proposal   on time.

Looking For Custom Research Topics & Ideas

Argumentative research topics on healthcare policy for graduates.

• Generic drugs and medicine should be provided to poor people by the government.
• Healthcare policies of the developing and developed countries should be reformed every year to check the loopholes.
• Government should provide financial support to the poor people through social welfare through healthcare policy.
• We cannot bring a country out of the diseases if the health treatment is too high.
• The number of drugs in medicines should be reduced to save the human brain from the effect of these medicinal drugs.

College persuasive research paper topics on healthcare

• Public opinion should be taken before making a healthcare policy.
• The healthcare policies must be framed by keeping the different age groups in mind.
• Healthcare insurance should be compulsory for every individual in the country.
• Good healthcare policies can help to reduce the mortality rate of a country easily.
• How to approach the level of diseases free nation with a future-oriented healthcare policy?
• Healthcare policies and rules are framed by the world health organization.
• Sanitation and personal hygiene policies are required at the suburban and village level.
• World financial organizations play a significant role in the successful achievement of goals set by the healthcare policies of the government.

Simple healthcare topics for compare and contrast research paper

• How developed nations are more cautious about their healthcare policies as compared to developing nations?
• The difference in the fund devoted to healthcare policies in the budget of various countries.
• How the health care system cannot be improved only by making rules and the involvement of people is important.
• Importance of free distribution of the basic medicines and healthcare facilities to the marginal sections in poor nations.
• How the World Bank can focus on the health-related policies by financing the countries based on their health policies improvement every year.
• What are the reasons for failure in the healthcare policies and their proper implementation in society?

See Also: Health Policy Research Paper topics & Ideas for Students

Free ideas on healthcare topics for critical research paper

• What should be the major highlights of a healthcare policy in a country like the USA?
• Change in the healthcare policies with the changing scenario of new interesting diseases that are coming into the spotlight.
• Healthcare policies at the world level by keeping the future scenario in mind.
• What are the statistical records regarding the poor health of people in the different countries due to improper healthcare policies of that specific nation?
• Can we bring a globe which is free from all sorts of diseases by making it compulsory to work out on daily basis for every person in the world?

Read Also: Interesting Diseases Research Paper Ideas 2023

Science students who are unable to write their research papers can take help in writing healthcare research papers from experienced helpers. My Research Topics experts are having ten long years of experience in writing different types of research papers . All types of research papers on healthcare policy are written by professional research paper writers. So you can take round-the-clock research paper writing services by placing your order online. The cost that will be charged in return for the quality research paper help is very nominal and can be neglected as graduates can pay it with personal expenses. Online research paper help is thus very easy for college students from all streams. Argumentative, persuasive, and compare and contrast essay help is given to the students by My Research Topics experts.

Stuck During Your Dissertation

Our top dissertation writing experts are waiting 24/7 to assist you with your university project,from critical literature reviews to a complete PhD dissertation.

Other Related Topics

• Business Research Proposal Topics For College Students
• Latest Exploratory Research Paper Topics & Ideas 2023
• Interesting Research Ideas For College Students 2023
• Interesting Presentation Ideas 2023

Research Paper Topics & Ideas about Diseases

Latest human sexuality research paper ideas 2023.

• Human Rights Research Paper Ideas for USA Students
• Hospitality Industry Research Paper Topics & Ideas 2023
• History Research Paper Topics & Ideas 2023
• Trending Research Paper Ideas for High School Students 2023

Recent Research Topic Idea for 2023

Healthcare Research Paper Topics & Ideas 2023

Healthcare Management Research Paper Topics & Ideas 2023

Health Policy Research Paper Topics & Ideas 2023

Research Paper Topics & Ideas On Health And Social Care

Get 15% off your first order with my research topics.

Connect with a professional writer within minutes by placing your first order. No matter the subject, difficulty, academic level or document type, our writers have the skills to complete it.

UP TO 25 % DISCOUNT

Get Your Research Paper Completed At Lower Prices

My Research Topics is provides assistance since 2004 to Research Students Globally. We help PhD, Psyd, MD, Mphil, Undergrad, High school, College, Masters students to compete their research paper & Dissertations. Our Step by step mentorship helps students to understand the research paper making process.

Research Topics & Ideas

• Criminology Research Paper Topics & Ideas 2023
• World History Research Paper Topics & Ideas 2023
• Child Development Research Paper Topics & Ideas 2023
• Medical Research Paper Topics & Ideas For Students 2023
• Nursing Ethics Research Topics & Ideas 2023
• Experimental Research Paper Topics & Ideas 2023
• Fashion Research Paper Topics & Ideas 2023 for Students

Research Guide

• Descriptive Research Design – Overview
• Write a Research Proposal
• What are Graduate Teaching Assistants?
• Textual Analysis in Research / Methods of Analyzing Text
• Research Project Questions

Disclaimer: The Reference papers provided by the Myresearchtopics.com serve as model and sample papers for students and are not to be submitted as it is. These papers are intended to be used for reference and research purposes only.

This paper is in the following e-collection/theme issue:

Published on 30.8.2023 in Vol 25 (2023)

Trust and Health Information Exchanges: Qualitative Analysis of the Intent to Share Personal Health Information

Authors of this article:

Original Paper

• Julia Busch-Casler * , Dr   ; 
• Marija Radic * , Dr  

Fraunhofer Center for International Management and Knowledge Economy IMW, Leipzig, Germany

*all authors contributed equally

Corresponding Author:

Julia Busch-Casler, Dr

Fraunhofer Center for International Management and Knowledge Economy IMW

Neumarkt 9-19

Leipzig, 04109

Phone: 49 341231039249

Email: [email protected]

Background: Digital health has the potential to improve the quality of care, reduce health care costs, and increase patient satisfaction. Patient acceptance and consent are a prerequisite for effective sharing of personal health information (PHI) through health information exchanges (HIEs). Patients need to form and retain trust in the system(s) they use to leverage the full potential of digital health. Germany is at the forefront of approving digital treatment options with cost coverage through statutory health insurance. However, the German population has a high level of technology skepticism and a low level of trust, providing a good basis to illuminate various facets of eHealth trust formation.

Objective: In a German setting, we aimed to answer the question, How does an individual form a behavioral intent to share PHI with an HIE platform? We discussed trust and informed consent through (1) synthesizing the main influence factor models into a complex model of trust in HIE, (2) providing initial validation of influence factors based on a qualitative study with patient interviews, and (3) developing a model of trust formation for digital health apps.

Methods: We developed a complex model of the formation of trust and the intent to share PHI. We provided initial validation of the influence factors through 20 qualitative, semistructured interviews in the German health care setting and used a deductive coding approach to analyze the data.

Results: We found that German patients show a positive intent to share their PHI with HIEs under certain conditions. These include (perceived) information security and a noncommercial organization as the recipient of the PHI. Technology experience, age, policy and regulation, and a disposition to trust play an important role in an individual’s privacy concern, which, combined with social influence, affects trust formation on a cognitive and emotional level. We found a high level of cognitive trust in health care and noncommercial research institutions but distrust in commercial entities. We further found that in-person interactions with physicians increase trust in digital health apps and PHI sharing. Patients’ emotional trust depends on disposition and social influences. To form their intent to share, patients undergo a privacy calculus. Hereby, the individual’s benefit (eg, convenience), benefits for the individual’s own health, and the benefits for public welfare often outweigh the perceived risks of sharing PHI.

Conclusions: With the higher demand for timely PHI, HIE providers will need to clearly communicate the benefits of their solutions and their information security measures to health care providers (physicians, nursing and administrative staff) and patients and include them as key partners to increase trust. Offering easy access and educational measures as well as the option for specific consent may increase patients’ trust and their intention to share PHI.

Introduction

Data-driven medicine promises better care and more efficient health care processes. Digital health information exchanges (HIEs), electronic health records (EHRs), and eHealth and mobile health (mHealth) apps have become increasingly relevant for sharing personal health information (PHI) in the past years. Countries aim to adopt and implement HIEs to improve the quality of care, reduce health care costs, und increase patient outcomes and satisfaction [ 1 ]. Germany is no exception. In 2019, Germany passed a law approving the prescription of mHealth apps by doctors whereby the costs are covered by the German statutory health insurance. All insured people are eligible to use registered mHealth apps as part of standard care [ 2 ]. However, uptake has been slow because of restraints from both patients and providers [ 3 , 4 ]. A recent study among German citizens [ 5 ] found that almost 25% of the respondents believe that technology creates more problems than it solves, thus indicating that Germans are highly skeptical toward technology overall. This is in line with prior research on country-specific trust levels [ 6 , 7 ], where Germany is associated with rather low levels of trust compared to other countries.

Patient acceptance and opt-in are crucial for efficient use of HIEs (we subsume EHRs, mHealth apps, and eHealth apps under the term “HIEs” for purposes of readability). Patients need to trust that the information security measures and privacy policies of the HIE provider are sufficient to protect their PHI [ 8 , 9 ]. Providers must explain these policies to the patient and show that they are upheld. Several studies have found that most patients have a positive attitude toward EHRs for reasons of convenience, completeness, and ease of communication [ 4 , 10 - 13 ]. However, PHI is considered highly sensitive. Data breaches can potentially have significant negative consequences for the patients involved [ 14 ]. Patients, although excited about the possibilities of EHRs [ 10 , 15 - 17 ], might not fully understand the impact their sharing decisions may have. They may even be reluctant to share their PHI digitally after witnessing data breaches [ 18 ]. Privacy concerns are the largest barrier to sharing PHI [ 16 , 19 ]. Trust in the safety and soundness of technological solutions has a strong impact on user opt-in [ 9 , 19 - 21 ]. Backhaus [ 22 ] described the trust of a user in a technical system as the expectation that the system will perform certain tasks based on the user’s wishes and assumptions without misusing their vulnerability caused by the execution of the process. Trust in digital health apps is strongly linked to trust in the respective health care provider [ 23 ]. Buhr et al [ 23 ], for example, found that Germans trust governmental institutions, such as the statutory health insurance, more than private institutions. Dhopeshwarkar et al [ 20 ] found that patients trust physicians regarding accessing health care files. Considering these developments, patients need to become the sovereign of their own PHI [ 24 ]. They need to be able to provide informed consent on what should be shared through HIEs and who can use PHI stored in their EHRs.

There have been multiple calls for more research on the subject, followed by an upswing in recent years [ 25 ]. Looking at the specific case of Germany in the context of regulatory initiatives [ 26 ] and a comparatively low trust level [ 27 ], however, may provide additional insight into patients’ behavioral intentions [ 28 , 29 ] and measures that HIE providers can undertake to increase the level of trust in their solutions and processes. Our research aimed to answer the following research question: How does an individual form a behavioral intent to share PHI with an HIE platform? We contributed to the discussion of trust and informed consent in digital health in the following ways: (1) We derived a complex model of trust in an eHealth app and intent formation to share PHI based on the belief-attitude-intention framework, (2) provided initial exploratory validation of influence factors through a qualitative analysis process with interviews of German patients, and (3) developed a model of trust formation for eHealth apps.

Initial Model

Trust in and acceptance of eHealth apps have become a more prevalent research area in recent years due to the increasing uptake of HIEs and the rise in virtual interactions in the COVID-19 pandemic years [ 23 , 25 , 28 ]. Different approaches try to assess trust in and user acceptance of (health) information technology and the sharing of PHI. Consumer acceptance and use of technology is often assessed based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and its extensions and adaptations [ 4 , 30 , 31 ]. The model has been applied to the health care context [ 4 , 12 , 13 , 21 ] and has also been enhanced with health behavior theories, such as the Health Belief Model, protection motivation theory, and social cognitive theory [ 24 ]. Abdelhamid [ 31 ], for example, adapted the UTAUT model to PHI sharing with HIEs and used privacy concerns, social influence, trust in health care professionals, health concerns, and perceived usefulness as the main variables for his quantitative study. He found that all factors except for privacy concerns have a positive impact on the sharing intention. More customized sharing choices may mitigate the negative effect of privacy concerns on PHI-sharing intention.

Privacy concerns are often stated as the main barrier to sharing of PHI. They are, however, not always part of the (adapted) Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) models. The Antecedent-Privacy Concern-Outcome (APCO) model presents 1 approach for the analysis of privacy concerns [ 32 - 35 ]. Shen et al [ 35 ], for example, developed an eHealth trust model based on the APCO approach and suggested personality, tech-savviness, eHealth awareness, health care perception, privacy experience, demographics, and culture as antecedents of privacy concerns. The authors described trusting belief as well as policy and regulation as moderating factors. In the outcome stage, they distinguished between a privacy calculus and the final behavioral reaction.

Privacy concerns are often associated with the privacy calculus model [ 16 , 35 - 38 ]. Abdelhamid et al [ 16 ], for example, presented a model with the following variables: patient activation, issue involvement, privacy concerns, trust in providers, and patient-physician relationship. They found that privacy concerns negatively affect the intention to share PHI. This can only partially be mitigated by the other variables.

Trust is another factor in assessing the acceptance of sharing PHI, which is sometimes covered in the UTAUT2 adaptions [ 21 ] but also analyzed separately [ 39 ]. Trust is often distinguished into a personal disposition, cognitive trust (in systems, people, etc) and emotional trust [ 19 , 39 ]. Esmaeilzadeh [ 8 ], for example, examined the acceptance of HIEs using a complex model of trust formation. The main variables analyzed included trust in health care providers and perceived transparency of the HIE privacy policy, leading to cognitive trust in, first, the integrity of the HIEs and, second, the competency of the HIEs. The latter factors influence emotional trust, which then translates into opt-in and willingness to disclose information.

Given the multifaceted nature of the concepts presented, in this study, we aimed to integrate the previous findings into a comprehensive model.

Scientific Basis of the Initial Model

Our initial model is depicted in Figure 1 . An overall definition of the constructs used in the initial model can be found in Multimedia Appendix 1 . We transferred the common belief-attitude-intention framework based on the theory of reasoned action [ 8 , 40 ] to a PHI-sharing setting. We divided our model into 3 stages: (1) belief formation, (2) attitude formation, and (3) information-sharing intent. We defined privacy concern as a belief referring to “the information the individual has about the object,” in this case the HIE [ 41 ]. We defined trust as an attitude, that is, the “favorable or unfavorable evaluation of an attitude object” [ 41 ]. We defined intent as “the subjective probability that the person will behave in a particular way vis-à-vis the attitude object” [ 41 ]. Beliefs are formed based on preconditions and previous experiences [ 40 , 41 ], which are sometimes referred to as values [ 41 ] or antecedents [ 32 , 35 ]. The antecedents of privacy concerns are depicted in the APCO model [ 32 , 35 , 42 ]. We added the antecedent component to the belief-attitude-intention framework to enhance the understanding of the belief formation. Behavioral intentions are influenced not only by trust but also by an individual’s privacy calculus [ 32 , 36 , 37 ], defined as the “cost-benefit analysis” of disclosing information [ 32 , 43 ]. We defined privacy calculus as an attitude, following the attitude definition of Stone et al [ 41 ].

Stage 1: Belief Formation

In the belief formation stage , an individual forms a belief about privacy and related risks of sharing PHI (privacy concern) based on antecedents. An individual has certain previous experiences with sharing information and (eHealth) technology, which we subsumed under technology experience [ 4 ]. We included an individual’s general experience with technology in the variable tech-savviness [ 35 ]. Since eHealth is a comparatively new topic for most individuals, we can only assess the awareness of eHealth of an individual [ 35 ]. We synthesized Shen et al’s [ 35 ] privacy perspective and related findings of Abdelhamid [ 31 ] and Hassandoust et al [ 37 ] into the item information security knowledge to cover potential experiences with data breaches and measures taken to protect an individual’s PHI in the light of the discussions of data sovereignty. We followed the following definition of information security: “Information security is the protection of information from a wide range of threats. This is achieved by managing a suitable set of security controls, policies and procedures within an Information Security Management System. The goal of general InfoSec is the ‘preservation of confidentiality, integrity and availability of information’ and includes such terms as the accountability of users, authentication, non-repudiation and reliability” [ 44 ]. Esmailzadeh [ 8 ] and Shen et al [ 35 ] have shown that an individual’s perception of policy and regulation influences their privacy beliefs. We included demographic factors as antecedents because studies have shown clear differences between the privacy beliefs of diverse demographic groups [ 4 , 5 , 45 , 46 ]. Finally, an individual has personality traits and dispositions, particularly a disposition to trust, that influence all interactions with the individual’s environment [ 19 , 47 , 48 ], including privacy concerns, attitudes, and the intent to share or withhold PHI [ 32 , 49 ]. In the eHealth setting, we argued in line with Abdelhamid et al [ 16 , 31 ] and added health concerns and patient activation into the initial dispositions. All the aforementioned factors lead to the formation of privacy concerns related to sharing an individual’s PHI. Individuals continuously interact in their specific social environment. Studies [ 31 , 37 , 50 ] have shown that social influence affects the intent to share via trust formation. We included social influence as an additional antecedent to trust and the privacy calculus, influencing the perceived utility of sharing PHI [ 31 , 37 ], and the emotional trust of an individual in an HIE.

Stage 2: Attitude Formation

In the attitude formation stage , an individual forms attitudes toward sharing PHI. These attitudes can be divided into the privacy calculus (see the previous section) and trust. The concept of trust has a composite definition [ 49 , 51 , 52 ]. The thoughts and decisions of an individual include both cognition and emotion [ 52 ], leading to a distinction between cognitive trust and emotional trust [ 52 , 53 ]. Cognitive trust in eHealth has different dimensions: First, patients develop a level of cognitive trust in their health care providers, which is necessary for the initial treatment. Based on trust transfer theory, individuals may transfer this established trust to the HIE [ 23 , 49 , 54 ]. To form a sharing intent through an HIE, however, individuals not only need to trust the health care institution but also have thoughts about the expertise and integrity of the HIE provider [ 8 ]. This is often not directly associated with the health care provider. Research shows that an individual’s privacy concern influences the risk associated with sharing PHI and well as the cognitive judgment whether to trust an entity in a digital setting [ 32 , 37 ]. The privacy calculus assesses the perceived utility of the sharing decision and compares it to the perceived risks associated with this decision [ 32 , 37 ]. Individuals value sharing data if they have a perceived benefit. In the case of PHI, patients may, for example, experience better or faster treatment. They may perceive a benefit because a certain health topic has personal relevance due to a particular health concern, which we captured as issue involvement [ 31 ]. The perceived risk refers to the loss or misuse of PHI because of, for example, data breaches and the associated perceived damages the individual incurs because of the data incident [ 35 ].

Stage 3: Information-Sharing Intent

Finally, in the information-sharing intent stage , the individual forms a behavioral intent to share PHI with the HIE. Contrary to Esmaeilzadeh [ 8 , 53 ], we did not differentiate between the opt-in intention and the willingness-to-share intention. Patients often do not actually have an option to opt in or out of an HIE [ 8 ], but rather, they have choices on what to share with an HIE. We regarded the willingness to share information with an HIE as the outcome of the trust formation model. We defined the willingness to share (health) information as the intention to voluntarily disclose information about one’s (health) status to others [ 55 ]. The complete theoretical model is depicted in Figure 1 .

Methodology

We described the methodology along the Consolidated Criteria for Reporting Qualitative Research (COREQ) domains ( Multimedia Appendix 2 ) [ 56 ].

Domain 1: Research Team and Reflexivity

Personal characteristics.

Interviews were conducted by 3 different interviewers who were part of the joint research project funding this research. All researchers had postgraduate degrees, while 1 also had a PhD; 1 of the researchers was female, while 2 were male. All interviewers had received prior training in conducting qualitative interviews, and all were employed at a research institution or university when conducting the interviews.

Relationship With Participants

The researchers conducting the interviews had no previous relationship with the interviewees. The participants received a 1-page introduction of the research project and its goals before agreeing to take part in the interviews. They did not have any further knowledge of the researchers other than project involvement. The researchers were involved in a common research project with the objective of developing a virtual consent assistant for informed and sovereign patient consent.

Domain 2: Study Design

Theoretical framework.

The study was based on a qualitative content analysis and followed a deductive category application [ 57 , 58 ]. Due to the exploratory nature of our study for the German system, we performed qualitative, semistructured interviews [ 59 ] to provide a starting point for our empirical assessment.

Participant Selection

Due to the COVID19 pandemic and associated contact restrictions, we were unable to proceed with our initial plan to recruit a variety of participants onsite at a large German university clinic. We evaluated different data-gathering strategies for their viability. We eventually recruited targeted interview candidates using a combination of purposive and convenience sampling. We selected candidates who (1) had signed a consent form for a medical procedure in the past 6 months and (2) met the rough replication of the demographics of potential app users from the existing personal networks of the researchers. The participants were approached via phone calls. Overall, we approached 25 people, of which 20 (80%) agreed to be interviewed. All participants were offered a small financial compensation (€25, or US $27) for their time. One person asked for the compensation to be donated to a worthy cause.

The interviews were conducted in German language and over the phone, whereby the participants answered the phone in their own homes. We could not assess whether there was anyone else present with them. The researchers worked out of their own offices and were by themselves. Overall, we conducted 20 qualitative user interviews. Table 1 shows the details of the participants.

Data Collection

We developed a questionnaire for the semistructured interviews, focusing on experiences with PHI consent, digital and consent literacy, trust, and individual data-sharing preferences. The translated questionnaire can be found in Multimedia Appendix 3 . The questionnaire was developed by the researchers conducting the interviews and discussed in the project consortium. As shown in the provided questionnaire, we added a vignette as a final question in order to elicit the participants’ intent on sharing PHI based on a specific situation in line with Barter and Renold [ 60 ]. Before the interview, the participants were asked to fill out a short questionnaire for demographic data. No repeat interviews were carried out. One interview had to be paused because the participant had to take a call, and was continued soon after. All interviews were audio-recorded, and the research team took limited field notes during the interviews. The average interview time was about 60 minutes.

Metathemes, as defined by Guest [ 61 ], presented themselves after coding about half the interviews, and we could assume data saturation after analyzing all 20 interviews. The transcripts were not returned to the participants for comment.

Domain 3: Analysis and Findings

Data analysis.

The interviews were transcribed using a transcription service via commissioned data processing following all stipulated information security measures. The transcripts were imported into MAXQDA [ 62 ] for coding. Coding was performed independently by 2 researchers with postgraduate degrees, 1 of whom had a PhD. We revised the coding agenda and coding rules before final coding and then compared results after final coding using Cohen κ. We reached a Cohen κ value of 0.88, indicating solid interrater agreement [ 63 ]. An overview of the constructs and definitions of the coding agenda, key illustrative quotations per code, and the number of statements coded per interview can be found in Multimedia Appendix 1 .

In this paper, we presented quotations to illustrate our findings. All interview quotations presented in the results were translated from German to English. The interviews were numbered for identification, and the position (denoted as “pos.” in the quotations) of each quotation in the transcript was marked accordingly. We presented major and minor themes in the results, and we adapted our initial model according to our exploratory findings.

Ethical Considerations

We obtained a positive ethics vote from the University of Cologne (review number: 21-1271). The survey was conducted in accordance with the applicable provisions of the Data Protection Act (Art.9 para.2 letter b DSGVO). The interviewers are subject to the obligation of secrecy and are also bound to data secrecy.

Prior to conducting the interviews, the participants obtained information about study participation and a consent form. The signed consent forms are kept separately from the short questionnaire and interview results in the university clinic so that no connection can be made between the information in the short questionnaire and the consent forms. The interviews were recorded with the help of a recorder. The recorded interviews were transcribed and pseudonymized. They were processed in written and pseudonymized form only so that it is no longer possible to draw conclusions about the person or third parties. In contrast to the transcripts, the audio files created could not be sufficiently pseudonymized for technical reasons, which is why they were not further processed after the interviews. They will, however, be stored until the end of the project in October 2023 and then deleted.

The participants were thoroughly informed that their participation in the study is completely voluntary. This means that at any time and without giving reasons, they had the right to refuse to answer individual questions. They could also terminate participation in the study or withdraw their consent to participate at any time without incurring any disadvantages. In this case, all data collected up to that point (questionnaires, transcripts, audio recordings) were completely deleted. All data collected in the context of the interview study were treated confidentially, stored exclusively for scientific purposes, and used exclusively by the scientists in the project team.

Participant Details

The average age of the participants was 48.5 (median 43.0) years. The youngest participant was 26 years old, and the oldest was 83 years old. About 70% (n=14) of the participants were women. About 80% (n=16) had an academic degree. The sample was skewed and may have overrepresented women with higher education. We did, however, postulate that the gained insights were relevant, given the articulated need to improve the understanding of female health perceptions and behaviors [ 64 , 65 ]. Of the 20 participants, 12 (60%; n=10, 83%, female) suffered from chronic illnesses and were more frequently in contact with health care institutions. Most participants dealt with 2-5 medical consent forms annually. In addition, 5 (42%) participants, who all reported 1 or more chronic illnesses, stated they would be confronted with 6-11 consent forms, indicating a multitude of interactions with the health care system. All participants said they use technology, mainly smartphones and laptops, for personal communication and information purposes. The most used features are search engines (n=20, 100%), email (n=19, 95%), online shopping (n=19, 95%), and online banking (n=18, 90%). Only 12 (60%) participants reported the usage of social media, and only 10 (83%) participants reported using online education formats. Furthermore, 12 (60%) participants reported their digital aptitude with a 3.5-4 score on a 5-point Likert scale ranging from little to no knowledge to expert knowledge. In contrast, participants over the age of 70 years reported their digital aptitude with an average score of 2.6.

Conceptual Model Validation

To validate the conceptual model of eHealth trust formation in Figure 1 , we analyzed our results along 3 stages: belief formation, attitude formation, and information-sharing intent. Generally, we found that most people show a behavioral intent to share their PHI with health care professionals digitally. One participant stated:

I am 100% convinced that the pros outweigh the cons. [Interview 2, pos. 121]

Another stated:

If you can judge the risk [associated with data breaches when sharing], then, generally yes, I would share it. [Interview 20, pos. 201]

Given the fulfillment of certain conditions, such as anonymity, participants would be willing to share their PHI with (noncommercial) medical research institutions for advancement in medical science. One participant stated:

And I think it is very important that everything that is related to [human health] is made available to science. [Interview 11, pos. 11]

Technology Experience

In the belief formation stage, we found that an individual’s privacy concern is indeed influenced by previous experiences with technology (tech-savviness) and their knowledge on information security. As previously mentioned, all participants used digital technology, mainly smartphones and laptops. The median self-reported tech-savviness was 3.5 on a 5-point Likert-Scale, with 1 being low and 5 being high. A notable statement was:

I would check the possibilities suggested on my computer or phone, and then I would check settings to see what I want and don’t want, and if I don’t understand it, then [the app] I would delete it. [Interview 16, pos. 77]

People with low tech-savviness (mostly over the age of 70 years in our sample) adopt strategies to help interact with digital technology. This was indicated in this statement:

If I need a new app or want to delete one, then someone has to do this for me. [Interview 11, pos. 55]

The overall knowledge on information security can be classified as low to medium and heavily relies on what has been communicated by the provider and preinstalled in the used system. One participant mentioned:

Something like this is already on my phone, an antivirus program. [Interview 10, pos. 67]

Often, people do not seem to be aware of or interested in the subject, as indicated by, for example, participant 2 (pos. 53), who “never looked into it.” People seem to assume that:

As soon as you are digital or you are transferring information, then you can’t control where it ends up and who uses it. [Interview 12, pos. 71]

Participants with a higher level of digital competency stated:

Not every app gets a right to access things where I don’t think the app needs them. [Interview 1, pos. 71]

There is no security measure that cannot be hacked…Because otherwise you would not be able to operate it, if it was completely secure. [Interview 14, pos. 107]

eHealth awareness does not seem to play a predominant role.

Policy and Regulation

Information security policies and the regulatory framework for data sharing pose another antecedent to privacy concerns. Participants statements included “if it is encrypted […] then I don’t see a problem” (interview 9, pos. 137), “always using the latest standard of anonymization […] and ensure transparency” (interview 14, pos. 171), and “so that no third party can access the data, but only the person that one has consented to” (interview 16, pos. 47). When sharing data for medical research, most participants wanted to stay completely anonymous. One participant, however, stated:

I would share my data with the condition that I get informed when they find something. That would be useful for me as a prophylactic measure. [Interview 12, pos. 145]

This indicates that complete anonymity may not always be beneficial for the data owner. We analyzed data from a German health care system, implying strict regulation on information sharing and information usage, which aids participants in feeling secure when sharing PHI. A notable statement was made by a participant who is an immigrant:

If you are here in Germany and know that everything is checked and done meticulously, then I don’t have a problem [with sharing my data]. In [the country] where I am from, you don’t know what they do with the [data]. There, I would think twice about it. [Interview 2, pos. 17]

Participants said they are comfortable sharing PHI within Germany or the European Union (EU) but are wary about sharing PHI with institutions outside the EU, as indicated, for example, by participant 16:

I would trust [institutions] within Europe. [Interview 16, pos. 173]

Demographics

Considering demographics, age was found to be the most predominant factor influencing privacy concerns. Participants stated:

So if I was 75, then I would say, I don’t care, take my data. Because I think, ok, then hackers have my data, but what are they going to do with it? But not in my current age. [Interview 7, pos. 133]

If you would ask someone who is 20, 30, or 40, they would give a different answer because everything happens digitally for them. [Interview 12, pos. 39]

All other factors were barely found in the interviews.

Personality and Disposition

The final antecedent was personality and disposition. In our sample, we found evidence for the importance of disposition to trust when sharing PHI. Most participants exhibited a tendency to trust and mentioned that a base level of trust is needed in all social and digital interactions. This was indicated by statements such as:

You need to have a level of trust these days, both in technology and in relation to the digital possibilities we have today. [Interview 15, pos. 105]

Then I have to give them the benefit of the doubt, that the information is important, and that’s what you need to have in general towards a doctor and a hospital. [Interview 3, pos. 23]

One participant, however, stated:

This is difficult. I trust myself...I don’t trust anyone. This is based on my experience. [Interview 10, pos. 81]

Participants were aware of the benefits of actively pursuing a healthy lifestyle (patient activation), and most stated that they try to do so, succeeding to a varying extent. Some participants mentioned a (brief) use of step counters or sleep trackers. They did not relate these statements to privacy concerns. We found evidence that showed an influence of patient activation on privacy concern formation, as indicated by the statement:

Yes, you see. Then we have a yes if I am affected myself. [Interview 10, pos. 149]

Regarding the impact of health status on privacy concerns, we found ambivalent results. Some people with chronic illnesses were skeptical about sharing their PHI or believed it is not important, while others said they would happily share their PHI. There was no evidence that health concerns such as chronic illnesses have an influence on privacy concerns.

Privacy Concerns

All participants expressed some level of privacy concern. Participants had “the feeling, that my data already is everywhere anyway” (interview 5, pos. 51) and a feeling of “overstimulation due to too much information” (interview 17, pos. 105) and being unable to control it in the first place. This was fittingly expressed by participant 13:

Yes, because I always have this remaining risk that the data could be misused. [Interview 13, pos. 143]

This was often mentioned in relation to a level of acceptance of the matter. Most participants stated the risk of “sensitive data in the wrong hands” (interview 3, pos. 151) through data leaks or hacking. Some worried about leaking illness-related PHI to employers and the resulting discrimination due to health concerns, as mentioned by participant 7:

If someone has an illness and she applies somewhere, [then] the potential employer could find that [the person] has an illness and not hire her. [Interview 7, pos. 13]

Other participants mentioned unwanted targeted ads or discrimination.

Social Influence

In addition to privacy concerns, social influence also affects trust formation. Particularly, older participants actively rely on their children and grandchildren for support in IT and sharing decisions and involve them in their decision process. Participant 12, for example, stated:

Then I would ask the younger generation. [Interview 12, pos. 57]

In the attitude formation stage, we differentiated between cognitive and emotional trust as well as the privacy calculus calculation.

Cognitive Trust

Overall, there was a high level of cognitive trust in medical institutions, such as hospitals, and other health care and health insurance providers:

You are willing to share your data as long as you trust the institution. [Interview 3, pos. 117]

Because I have a base level of trust in our health care system. [Interview 8, pos. 21]

We also found that a base level of trust is created through an in-person interaction with the treating physician or the health insurance provider, as indicated by participant 2:

If my family doctors said you need to monitor your blood pressure and I would like you to use this [app]…then I would use it. [Interview 2, pos. 79]

However, trust in Big Pharma and the general intentions of companies using health-related data was low. Participants used large platforms, such as Facebook and Google, but tended to have reservations about their data collection and usage policies. One participant stated:

The motivation of the companies to get data is high…They surely get more information than they deserve. [Interview 1, pos. 89]

This statement displays the influence of the person’s privacy concern on trust formation. Participants did, however, trust the expertise and integrity of, for example, the apps provided by their health insurance providers, as indicated by the following statements:

If you talk about expertise, they are all competent. Generally, I would say that everything related to health insurances and sport universities would have the highest level of expertise. [Interview 4, pos. 107]

The health insurance app is competent because I can upload my bills. [Interview 6, pos. 151]

Emotional Trust

Participants based their emotional trust in HIEs on their general disposition to trust and previous experiences expressed within privacy concerns, as indicated by this statement:

When the health insurance said we have this app and we would like you to use it…I thought I can do that for them…I have blind faith that the [health insurance] makes sure it is safe. [Interview 2, pos. 71]

Depending on their dispositions and experiences, some participants showed an emotional mistrust in HIEs, such as 1 participant:

I would have a feeling, I don’t know, what types of data go where, what they can tell someone about me…I think this is too risky. [Interview 7, pos. 149]

Privacy Calculus

In addition to forming a trust attitude at this stage, participants underwent a privacy calculus, comparing the utility and associated risks of sharing PHI. Participants were more likely to opt into sharing PHI if they perceived it to be beneficial (1) for their own convenience and usability of the app, (2) for their own health, or (3) if it aids a common good of advancing medical diagnosis and treatment. One participant stated clearly, “Yes, if I benefit from it,” (interview 5, pos. 123), while mentioning the common good, “So if I share this data for research purposes, then I definitely see the benefit that you can perform research with it. And that is somehow a priority for me” (interview 5, pos. 173).

Another one said:

[I’d] have a good feeling [that] things will be a bit easier…if the data is already saved. [Interview 8, pos. 117]

… Because then you have your whole health history and all the relevant information in one spot…I believe this has a lot of potential. [Interview 8, pos. 41]

Yet another participant stated:

I think it is very important that data is shared between the [medical] professionals. [Interview 11, pos. 23]

Perceived risk is mainly associated with misuse of data by third parties, as indicated by participant 3:

…Sensitive data gets into the wrong hands…That would be bad for the user. [Interview 3, pos. 151]

Stage 3: Intent Formation

In the information-sharing intent stage, participants formed their final intent toward sharing their PHI with an HIE. To assess intent, participants received a vignette (see Multimedia Appendix 1 ) and were asked for their recommendation. Most participants (n=19, 95%) displayed a positive intent to share their PHI, even given the special circumstances:

Because it will be beneficial for research on this illness […] I think you should do it, even if data is stolen. [Interview 6, pos. 227]

Additional Themes

In addition to the deductive themes from the model, we found that participants preferred apps that are easy to use in daily life. Further, participants preferred a specific consent solution [ 66 ] compared to a broad consent solution.

Figure 2 shows the updated eHealth trust formation model based on our interview results. The figure shows which constructs are supported by evidence within our data set and which ones are currently not supported. These results should certainly be validated with further qualitative and quantitative cross-country studies.

Principal Findings

The objective of our study was to gain deeper insight into the issue of trust in HIEs and answer the following question: How does an individual form a behavioral intent to share PHI with an HIE platform? We contributed to the discussion of trust and informed consent in digital health in the following ways: First, we synthesized the main influence factors into a complex model of trust in HIEs. Next, we verified the influence factors through a qualitative analysis using patient interviews in the German health care setting. We showed which constructs are supported by evidence within our data set and which ones are not. Since this was an exploratory study, we did not adapt the model based on our current findings.

Our results showed that most patients generally have a positive attitude toward sharing their PHI digitally through an HIE. Our model provides a new point of view on the formation of a behavioral intention to share PHI by combining key concepts of the APCO model with a belief-attitude-intention framework and research on trust and the privacy calculus. Based on the interviews, we found that patients form a privacy concern in the belief formation stage based on antecedents, which can be divided into 4 categories: (1) demographics, (2) policy and regulation, (3) previous experiences with technology and information security, and (4) an individual’s own personality and disposition to trust. We also highlighted which factors appear more important in influencing the information-sharing intent. All participants in our sample use technology and gather their own experiences with it.

In the attitude formation stage, privacy concerns and social influence lead to the formation of trust in both cognitive and emotional terms. A base level of trust is created through in-person interactions with the treating physician or the health insurance provider. Trust is then transferred to the suggested HIE for sharing PHI. This is a crucial difference compared to trust formation in an e-commerce setting, for example, without contact with a physical party in the process. In the German health care setting, patients can choose their health care provider (within time and location restrictions). They can already develop a level of cognitive trust in the health care provider before interacting with the HIE. In addition to trust, the privacy calculus influences the intent to (not) share PHI with an HIE.

Limitations

We based our model on previous empirical and theoretical research. Regarding the representativeness of our results, our sample was slightly skewed and may have overrepresented women with higher education. This may be due to increased digital health literacy [ 67 , 68 ] and an increased interest shown by this demographic in the topic [ 23 ]. The insights gained are relevant, given the articulated need to improve the understanding of female health perceptions and behaviors [ 64 , 65 ].

We did not interview people under the age of 25 years, which may have impacted the results. We did, however, capture some secondary insights into their attitudes through conversations with a younger age group mentioned by the participants. All participants displayed some level of tech-savviness, which may be due to low interest of non-tech-savvy people in the research and an unwillingness to participate.

The study did not capture real-life PHI-sharing decisions but, rather, analyzed the behavioral intent. Participants may have provided socially desirable answers, which may not be in line with their final action of sharing PHI. We did, however, assume that a positive intent will eventually lead to a positive action, that is, sharing PHI for the majority of participants [ 69 ].

The validation was conducted based on the results of 20 interviews with patients in Germany. To generalize the results, further qualitative and quantitative cross-country validations of the model are needed.

Comparison With Prior Work

Our model provides a new point of view on the formation of a behavioral intention to share PHI by combining key concepts of research on privacy, user acceptance, and trust. With this, we address calls for a more nuanced view on the patient perspectives concerning privacy and trust [ 42 ]. We collected data from a country that is a front-runner for approving digital treatment options with cost coverage through statutory health insurance but at the same time has a comparatively rather low level of trust and high level of technology skepticism [ 4 ].

With our data, we confirmed previous findings [ 46 , 68 ] that most patients generally have a positive attitude toward sharing their PHI digitally through an HIE, even in the German health care setting [ 23 , 70 ]. Our data indicate that age is a predictor of privacy concerns [ 4 ]. Older participants stated that they are happy to share their PHI, which is in line with previous findings [ 71 ]. This could relate to a lack of understanding of what the shared PHI could be used for, which is in line with studies on digital (health) literacy [ 5 , 72 , 73 ]. However, it could also reflect the need to share information in order to enable a better understanding of the information for oneself [ 71 ]. The middle-aged participants in our study exhibited a higher level of privacy concerns. Studies [ 45 , 74 ] have found that adolescents and young adults exhibit fewer privacy concerns, possibly due to a limited understanding of the consequences as well. Further studies are needed to better understand the impact of age on privacy concerns, particularly for the older generation.

Our results further indicated that knowledge of and previous experiences with information security and technology might play an ambivalent role in forming privacy concerns: A higher level of knowledge could, on the one hand, decrease privacy concerns, as the individual knows which measures to take to mitigate the risk of a data breach. On the other hand, it may increase the level of privacy concerns, as the individual understands how easily data breaches can occur, even with measures in place. The latter is in line with the findings of Baruh et al [ 75 ].

In addition, a base level of trust is created through in-person interaction with the treating physician or the health insurance provider, which is in line with previous studies [ 8 , 31 , 50 , 76 ] and poses a stark difference to non-health-related information sharing, where there is rarely an in-person interaction required.

Sharing PHI through or with HIEs has the potential to significantly improve the quality of care, patient outcomes, and satisfaction and to raise efficiencies in the health care sector. Privacy concerns and trust formation are a main pillar of successful and patient-centered introduction and usage of HIEs and EHRs. In terms of the practical implications of our study, patients generally have a high level of trust toward medical institutions and tend to be willing to share their PHI, given the fulfillment of certain antecedent conditions by HIEs providers, such as information security, risk mitigation, transparency, anonymity, and a defined group of (noncommercial) users.

Offering educational measures as well as the option for specific consent [ 66 ] may increase patients’ trust and their intention to share PHI. Increasing patients’ knowledge appears essential in facilitating empowerment and awareness of data sovereignty, despite the potential effect on privacy concerns. Developers of HIE solutions should, along the lines of General Data Protection Regulation (GDPR) requirements, aim to educate users (both medical and nonmedical staff as well as patients) on the implications of their choices. They should enable patients to choose sharing options based on their personal knowledge and preferences. Arguably, however, implementing privacy by design and security by design in old implementations of systems proves to be more difficult compared to new applications.

HIE providers need to clearly communicate the benefits of their solutions and information security measures to both health care providers (physicians, nursing and administrative staff) and patients in terms of convenience, health benefits, and public welfare. Health care providers are key partners of HIE developers with regard to sharing PHI. This entails that creating trusting relationships with physicians and health care staff, as well as national health organizations, is essential to increase patients’ PHI sharing. Medical professionals need to be convinced that the technology provides benefits, not only for the patient and related care activities, but also for internal service provision processes entailing time and cost savings for the practitioners. Implementing digital services must facilitate care delivery rather than producing additional work for the care provider. HIE developers should integrate care providers into their service development to better adapt their product to user needs. Another strategy may be to aim for a national rollout through a governmental organization to create a base level of trust.

In terms of usability, HIE providers should aim at making it easy for health care providers and patients to access, use, and navigate their apps. This could be done by, for example, performing early usability testing and offering access through multiple operating systems. Offering (non)monetary compensation for sharing certain types of PHI with commercial parties could create an additional incentive for partaking in commercial research, which is needed to bring medication and treatments to market.

Acknowledgments

This research was funded by the German Federal Ministry of Education and Research (BMBF) within the scope of the research project Virtual Consent Assistant for Informed and Data-Sovereign Patient Consent (ViCon; funding reference number 16SV8497). We thank Ms Carla Riese, Mr Peter Haberland, and Mr Patrick Casler for their support for this paper.

Conflicts of Interest

None declared.

Overview of constructs, definitions, illustrative quotes, and frequencies.

Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist.

Questionaire (translated).

• Payne TH, Lovis C, Gutteridge C, Pagliari C, Natarajan S, Yong C, et al. Status of health information exchange: a comparison of six countries. J Glob Health 2019 Dec;9(2):0204279 [ https://europepmc.org/abstract/MED/31673351 ] [ CrossRef ] [ Medline ]
• Frey S, Kerkemeyer L. Acceptance of digital health applications in non-pharmacological therapies in German statutory healthcare system: results of an online survey. Digit Health 2022;8:20552076221131142 [ https://journals.sagepub.com/doi/10.1177/20552076221131142?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub 0pubmed ] [ CrossRef ] [ Medline ]
• Dahlhausen F, Zinner M, Bieske L, Ehlers JP, Boehme P, Fehring L. Physicians' attitudes toward prescribable mHealth apps and implications for adoption in Germany: mixed methods study. JMIR Mhealth Uhealth 2021 Nov 23;9(11):e33012 [ https://mhealth.jmir.org/2021/11/e33012/ ] [ CrossRef ] [ Medline ]
• Uncovska M, Freitag B, Meister S, Fehring L. Patient acceptance of prescribed and fully reimbursed mhealth apps in Germany: an UTAUT2-based online survey study. J Med Syst 2023 Jan 27;47(1):14 [ https://europepmc.org/abstract/MED/36705853 ] [ CrossRef ] [ Medline ]
• TechnikRadar 2022: Was die Deutschen über Technik denken. acatech – Deutsche Akademie der Technikwissenschaften. 2022. URL: https://www.acatech.de/publikation/technikradar-2022/ [accessed 2023-08-08]
• Gaskell G, Gottweis H, Starkbaum J, Gerber MM, Broerse J, Gottweis U, et al. Publics and biobanks: pan-European diversity and the challenge of responsible innovation. Eur J Hum Genet 2013 Jan;21(1):14-20 [ https://europepmc.org/abstract/MED/22669414 ] [ CrossRef ] [ Medline ]
• Alaqra AS, Fischer-Hübner S, Framner E. Enhancing privacy controls for patients via a selective authentic electronic health record exchange service: qualitative study of perspectives by medical professionals and patients. J Med Internet Res 2018 Dec 21;20(12):e10954 [ http://www.jmir.org/2018/12/e10954/ ] [ CrossRef ] [ Medline ]
• Esmaeilzadeh P. The impacts of the perceived transparency of privacy policies and trust in providers for building trust in health information exchange: empirical study. JMIR Med Inform 2019 Nov 26;7(4):e14050 [ https://medinform.jmir.org/2019/4/e14050/ ] [ CrossRef ] [ Medline ]
• Schomakers E, Lidynia C, Ziefle M. Listen to my heart? How privacy concerns shape users’ acceptance of e-Health technologies. 2019 Presented at: 2019 International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob); October 21-23, 2019; Barcelona, Spain p. 306-311 [ CrossRef ]
• Griebel L, Kolominsky-Rabas P, Schaller S, Siudyka J, Sierpinski R, Papapavlou D, et al. Acceptance by laypersons and medical professionals of the personalized eHealth platform, eHealthMonitor. Inform Health Soc Care 2017 Sep;42(3):232-249 [ CrossRef ] [ Medline ]
• Hassol A, Walker JM, Kidder D, Rokita K, Young D, Pierdon S, et al. Patient experiences and attitudes about access to a patient electronic health care record and linked web messaging. J Am Med Inform Assoc 2004;11(6):505-513 [ http://jamia.oxfordjournals.org/cgi/pmidlookup?view=long&pmid=15299001 ] [ CrossRef ] [ Medline ]
• Bile Hassan I, Murad MAA, El-Shekeil I, Liu J. Extending the UTAUT2 model with a privacy calculus model to enhance the adoption of a health information application in Malaysia. Informatics 2022 Mar 28;9(2):31 [ CrossRef ]
• Schomakers E, Lidynia C, Vervier LS, Calero Valdez A, Ziefle M. Applying an extended UTAUT2 model to explain user acceptance of lifestyle and therapy mobile health apps: survey study. JMIR Mhealth Uhealth 2022 Jan 18;10(1):e27095 [ https://mhealth.jmir.org/2022/1/e27095/ ] [ CrossRef ] [ Medline ]
• Pool JK, Akhlaghpour S, Fatehi F, Burton-Jones A. Causes and impacts of personal health information (PHI) breaches: a scoping review and thematic analysis. 2019 Presented at: PACIS 2019: 23rd Pacific Asia Conference on Information Systems; July 8-12, 2019; X'ian, China [ CrossRef ]
• Simon SR, Evans JS, Benjamin A, Delano D, Bates DW. Patients' attitudes toward electronic health information exchange: qualitative study. J Med Internet Res 2009 Aug 06;11(3):e30 [ https://www.jmir.org/2009/3/e30/ ] [ CrossRef ] [ Medline ]
• Abdelhamid M, Gaia J, Sanders GL. Putting the focus back on the patient: how privacy concerns affect personal health information sharing intentions. J Med Internet Res 2017 Sep 13;19(9):e169 [ http://www.jmir.org/2017/9/e169/ ] [ CrossRef ] [ Medline ]
• De Santis KK, Jahnel T, Sina E, Wienert J, Zeeb H. Digitization and health in Germany: cross-sectional nationwide survey. JMIR Public Health Surveill 2021 Nov 22;7(11):e32951 [ https://publichealth.jmir.org/2021/11/e32951/ ] [ CrossRef ] [ Medline ]
• Bhuyan SS, Bailey-DeLeeuw S, Wyant DK, Chang CF. Too much or too little? How much control should patients have over EHR data. J Med Syst 2016 Jul;40(7):174 [ CrossRef ] [ Medline ]
• Ruotsalainen P, Blobel B, Pohjolainen S. Privacy and trust in eHealth: a fuzzy linguistic solution for calculating the merit of service. J Pers Med 2022 Apr 19;12(5):657 [ https://www.mdpi.com/resolver?pii=jpm12050657 ] [ CrossRef ] [ Medline ]
• Dhopeshwarkar RV, Kern LM, O'Donnell HC, Edwards AM, Kaushal R. Health care consumers' preferences around health information exchange. Ann Fam Med 2012;10(5):428-434 [ http://www.annfammed.org/cgi/pmidlookup?view=long&pmid=22966106 ] [ CrossRef ] [ Medline ]
• Arfi WB, Nasr IB, Kondrateva G, Hikkerova L. The role of trust in intention to use the IoT in eHealth: application of the modified UTAUT in a consumer context. Technol Forecast Soc Change 2021 Jun;167:120688 [ CrossRef ]
• Backhaus N. Nutzervertrauen und –erleben im Kontext technischer Systeme: Empirische Untersuchungen am Beispiel von Webseiten und Cloudspeicherdiensten. Deutsche Nationalbibliothek. 2017. URL: https://d-nb.info/1156183804/34 [accessed 2023-08-08]
• Buhr L, Schicktanz S, Nordmeyer E. Attitudes toward mobile apps for pandemic research among smartphone users in Germany: national survey. JMIR Mhealth Uhealth 2022 Jan 24;10(1):e31857 [ https://mhealth.jmir.org/2022/1/e31857/ ] [ CrossRef ] [ Medline ]
• Koivumäki T, Pekkarinen S, Lappi M, Väisänen J, Juntunen J, Pikkarainen M. Consumer adoption of future mydata-based preventive eHealth services: an acceptance model and survey study. J Med Internet Res 2017 Dec 22;19(12):e429 [ http://www.jmir.org/2017/12/e429/ ] [ CrossRef ] [ Medline ]
• Hutchings E, Loomes M, Butow P, Boyle FM. A systematic literature review of health consumer attitudes towards secondary use and sharing of health administrative and clinical trial data: a focus on privacy, trust, and transparency. Syst Rev 2020 Oct 09;9(1):235 [ https://systematicreviewsjournal.biomedcentral.com/articles/10.1186/s13643-020-01481-9 ] [ CrossRef ] [ Medline ]
• German Federal Ministry of Health. Gesetz für eine bessere Versorgung durch Digitalisierung und Innovation: Digitale-Versorgung-Gesetz (DVG). Digital Healthcare Act – DVG. 2019. URL: https://www.bundesgesundheitsministerium.de/digitale-versorgung-gesetz.html [accessed 2023-08-19]
• Zimmermann BM, Fiske A, Prainsack B, Hangel N, McLennan S, Buyx A. Early perceptions of COVID-19 contact tracing apps in German-speaking countries: comparative mixed methods study. J Med Internet Res 2021 Feb 08;23(2):e25525 [ https://www.jmir.org/2021/2/e25525/ ] [ CrossRef ] [ Medline ]
• Sbaffi L, Rowley J. Trust and credibility in web-based health information: a review and agenda for future research. J Med Internet Res 2017 Jun 19;19(6):e218 [ https://www.jmir.org/2017/6/e218/ ] [ CrossRef ] [ Medline ]
• S. Bhuyan S, Kim H, Isehunwa OO, Kumar N, Bhatt J, Wyant DK, et al. Privacy and security issues in mobile health: current research and future directions. Health Policy Technol 2017 Jun;6(2):188-191 [ CrossRef ]
• Venkatesh, Thong, Xu. Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly 2012 Mar;36(1):157-178 [ CrossRef ]
• Abdelhamid M. Greater patient health information control to improve the sustainability of health information exchanges. J Biomed Inform 2018 Jul;83:150-158 [ https://linkinghub.elsevier.com/retrieve/pii/S1532-0464(18)30108-4 ] [ CrossRef ] [ Medline ]
• Smith, Dinev, Xu. Information privacy research: an interdisciplinary review. MIS Quarterly 2011;35(4):989 [ CrossRef ]
• Shen N, Sequeira L, Silver MP, Carter-Langford A, Strauss J, Wiljer D. Patient privacy perspectives on health information exchange in a mental health context: qualitative study. JMIR Ment Health 2019 Nov 13;6(11):e13306 [ https://mental.jmir.org/2019/11/e13306/ ] [ CrossRef ] [ Medline ]
• Zhang X, Liu S, Chen X, Wang L, Gao B, Zhu Q. Health information privacy concerns, antecedents, and information disclosure intention in online health communities. Inf Manag 2018 Jun;55(4):482-493 [ CrossRef ] [ Medline ]
• Shen N, Strauss J, Silver M, Carter-Langford A, Wiljer D. The eHealth trust model: a patient privacy research framework. Stud Health Technol Inform 2019;257:382-387 [ Medline ]
• Dinev T, Hart P. An extended privacy calculus model for e-commerce transactions. Inf Syst Res 2006 Mar;17(1):61-80 [ CrossRef ]
• Hassandoust F, Akhlaghpour S, Johnston AC. Individuals' privacy concerns and adoption of contact tracing mobile applications in a pandemic: a situational privacy calculus perspective. J Am Med Inform Assoc 2021 Mar 01;28(3):463-471 [ https://europepmc.org/abstract/MED/33164077 ] [ CrossRef ] [ Medline ]
• Dinev T, Albano V, Xu H, D'Atri A, Hart P. Individuals’ attitudes towards electronic health records: a privacy calculus perspective. In: Gupta A, Patel VL, Greenes RA, editors. Advances in Healthcare Informatics and Analytics. New York, NY: Springer; 2016:19-50
• Hasselgren A, Hanssen Rensaa J, Kralevska K, Gligoroski D, Faxvaag A. Blockchain for increased trust in virtual health care: proof-of-concept study. J Med Internet Res 2021 Jul 30;23(7):e28496 [ https://www.jmir.org/2021/7/e28496/ ] [ CrossRef ] [ Medline ]
• Hill RJ, Fishbein M, Ajzen I. Belief, attitude, intention and behavior: an introduction to theory and research. Contemp Sociol 1977 Mar;6(2):244 [ CrossRef ]
• Stone EF, Gueutal HG, Gardner DG, McClure S. A field experiment comparing information-privacy values, beliefs, and attitudes across several types of organizations. J Appl Psychol 1983 Aug;68(3):459-468 [ CrossRef ]
• Shen N, Bernier T, Sequeira L, Strauss J, Silver MP, Carter-Langford A, et al. Understanding the patient privacy perspective on health information exchange: a systematic review. Int J Med Inform 2019 May;125:1-12 [ CrossRef ] [ Medline ]
• Culnan MJ, Bies RJ. Consumer privacy: balancing economic and justice considerations. J Soc Issues 2023 Jul;59(2):323-342 [ CrossRef ] [ Medline ]
• Box D, Pottas D. A model for information security compliant behaviour in the healthcare context. Procedia Technol 2014;16:1462-1470 [ CrossRef ]
• Steijn WMP, Schouten AP, Vedder AH. Why concern regarding privacy differs: the influence of age and (non-)participation on Facebook. Cyberpsychology 2016 May 01;10(1):Article 3 [ CrossRef ]
• Karampela M, Ouhbi S, Isomursu M. Connected health user willingness to share personal health data: questionnaire study. J Med Internet Res 2019 Nov 27;21(11):e14537 [ https://www.jmir.org/2019/11/e14537/ ] [ CrossRef ] [ Medline ]
• Bansal G, Zahedi FM, Gefen D. Do context and personality matter? Trust and privacy concerns in disclosing private information online. Inf Manag 2016 Jan;53(1):1-21 [ CrossRef ]
• Ruotsalainen P, Blobel B. Health information systems in the digital health ecosystem-problems and solutions for ethics, trust and privacy. Int J Environ Res Public Health 2020 Apr 26;17(9):3006 [ https://www.mdpi.com/resolver?pii=ijerph17093006 ] [ CrossRef ] [ Medline ]
• McKnight DH, Choudhury V, Kacmar C. Developing and validating trust measures for e-commerce: an integrative typology. Inf Syst Res 2002 Sep;13(3):334-359 [ CrossRef ]
• Wirtz BW, Mory L, Ullrich S. eHealth in the public sector: an empirical analysis of the acceptance of Germany's electronic health card. Public Admin 2012;90(3):642-663 [ CrossRef ]
• Kee HW, Knox RE. Conceptual and methodological considerations in the study of trust and suspicion. J Confl Resolut 2016 Jul 01;14(3):357-366 [ CrossRef ]
• Komiak SX, Benbasat I. Understanding customer trust in agent-mediated electronic commerce, web-mediated electronic commerce, and traditional commerce. Inf Technol Manag 2004 Jan;5(1/2):181-207 [ CrossRef ]
• Esmaeilzadeh P. The impacts of the privacy policy on individual trust in health information exchanges (HIEs). INTR 2020 Feb 24;30(3):811-843 [ CrossRef ]
• Lu Y, Yang S, Chau PY, Cao Y. Dynamics between the trust transfer process and intention to use mobile payment services: a cross-environment perspective. Inf Manag 2011 Dec;48(8):393-403 [ CrossRef ]
• Lowry PB, Cao J, Everard A. Privacy concerns versus desire for interpersonal awareness in driving the use of self-disclosure technologies: the case of instant messaging in two cultures. J Manag Inf Syst 2014 Dec 08;27(4):163-200 [ CrossRef ]
• Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care 2007 Dec;19(6):349-357 [ http://intqhc.oxfordjournals.org/cgi/pmidlookup?view=long&pmid=17872937 ] [ CrossRef ] [ Medline ]
• Elo S, Kyngäs H. The qualitative content analysis process. J Adv Nurs 2008 Apr;62(1):107-115 [ CrossRef ] [ Medline ]
• Mayring P. Qualitative content analysis. Forum Qual Soc Res 2000 Jun;1(2):Article 20 [ CrossRef ]
• Flick U. An Introduction to Qualitative Research. 6th Edition. Los Angeles, CA: Sage; 2018.
• Barter C, Renold E. The use of vignettes in qualitative research. Soc Res Update 1999;25(9):1-6
• Guest G, Bunce A, Johnson L. How many interviews are enough? Field Methods 2016 Jul 21;18(1):59-82 [ CrossRef ]
• Kuckartz U, Rädiker S. Analyzing Qualitative Data with MAXQDA. Cham: Springer International Publishing; 2019.
• McHugh ML. Interrater reliability: the kappa statistic. Biochem Med 2012:276-282 [ CrossRef ]
• Bird CE, Rieker PP. Gender matters: an integrated model for understanding men's and women's health. Soc Sci Med 1999 Mar;48(6):745-755 [ CrossRef ] [ Medline ]
• Mauvais-Jarvis F, Bairey Merz N, Barnes PJ, Brinton RD, Carrero J, DeMeo DL, et al. Sex and gender: modifiers of health, disease, and medicine. Lancet 2020 Aug;396(10250):565-582 [ CrossRef ]
• Ploug T, Holm S. Meta consent: a flexible and autonomous way of obtaining informed consent for secondary research. BMJ 2015 May 07;350:h2146 [ CrossRef ] [ Medline ]
• Umfrage: TK-Meinungs­puls - so sieht Deutsch­land sein Gesund­heits­system. Techniker Krankenkasse. 2021. URL: https://www.tk.de/presse/themen/gesundheitssystem/meinungspuls-2021-2105216?tkcm=aaus [accessed 2023-08-08]
• Muller SHA, van Thiel GJMW, Vrana M, Mostert M, van Delden JJM. Patients' and publics' preferences for data-intensive health research governance: survey study. JMIR Hum Factors 2022 Sep 07;9(3):e36797 [ https://humanfactors.jmir.org/2022/3/e36797/ ] [ CrossRef ] [ Medline ]
• Barth S, de Jong MD. The privacy paradox – investigating discrepancies between expressed privacy concerns and actual online behavior – a systematic literature review. Telemat Inform 2017 Nov;34(7):1038-1058 [ CrossRef ]
• Lesch W, Richter G, Semler S. Daten teilen für die Forschunginstellungen und Perspektiven zur Datenspende in Deutschland. In: Richter G, Loh W, Buyx A, Graf von Kielmansegg S, editors. Datenreiche Medizin und das Problem der Einwilligung. Berlin, Heidelberg: Springer; 2022.
• Nurgalieva L, Cajander, Moll J, Åhlfeldt R, Huvila I, Marchese M. 'I do not share it with others. No, it's for me, it's my care': on sharing of patient accessible electronic health records. Health Inform J 2020 Dec;26(4):2554-2567 [ https://journals.sagepub.com/doi/10.1177/1460458220912559?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%3dpubmed ] [ CrossRef ] [ Medline ]
• Park YJ. Digital literacy and privacy behavior online. Commun Res 2011 Aug 23;40(2):215-236 [ CrossRef ]
• Chang YS, Zhang Y, Gwizdka J. The effects of information source and eHealth literacy on consumer health information credibility evaluation behavior. Comput Hum Behav 2021 Feb;115:106629 [ CrossRef ]
• Adorjan M, Ricciardelli R. A new privacy paradox? Youth agentic practices of privacy management despite "nothing to hide" online. Can Rev Sociol 2019 Feb;56(1):8-29 [ CrossRef ] [ Medline ]
• Baruh L, Secinti E, Cemalcilar Z. Online privacy concerns and privacy management: a meta-analytical review. J Commun 2017 Jan 17;67(1):26-53 [ CrossRef ]
• Stiftung Gesundheitswissen. Trendmonitor: Wie informieren sich die Deutschen zu Gesundheitsthemen? Erste Ergebnisse der HINTS Germany-Studie. 2019. URL: https://www.stiftung-gesundheitswissen.de/sites/default/files/pdf/trendmonitor_01.pdf [accessed 2023-08-19]

Abbreviations

Edited by T Leung; submitted 03.08.22; peer-reviewed by N Shen, R Cochran, AS Alaqra, RM Åhlfeldt; comments to author 19.12.22; revised version received 12.02.23; accepted 31.07.23; published 30.08.23

©Julia Busch-Casler, Marija Radic. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 30.08.2023.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

REVIEW article

This article is part of the research topic.

Integrating Digital Health Technologies in Clinical Practice and Everyday Life: Unfolding Innovative Communication Practices

Understanding acceptability of digital health technologies among francophone-speaking communities across the world: A metaethnographic study

• 1 University of Ottawa, Canada

The final, formatted version of the article will be published soon.

Introduction: Increasingly, people are turning towards digital health technologies (DHT) to support care management, communication with health professionals, and performing activities of daily living. DHT may be well implemented in clinical practices in several jurisdictions, but the influence of sociocultural factors may sometimes be neglected. To increase use and sustainability of these innovative solutions in health care, we need to understand acceptability among diverse groups of the population such as linguistically diverse populations. Francophone-speaking populations in Canada, for example, are known to endure challenges with income, health and difficulties associated with living in rural areas which impede on their likelihood to use DHT. As part of the University of Ottawa International Francophonie Research Chair on Digital Health Technologies, this study aimed to understand the conditions that make DHT acceptable among francophone-speaking communities. Methods: Using a meta-ethnography methodology, this study synthesizes international qualitative research on social acceptability of DHT among francophone-speaking communities. We focused on four types of DHT. Using Noblit and Hare's approach t, we were able to get a comprehensive synthesis and understanding of the research landscape on the issue. Studies published between 2010 and 2020 were included and synthesized using NVivo, excel and a mind mapping technique. Results: Our coding revealed that factors of social acceptability for DHT could be grouped into the following categories: care organization, self-care support, communication with care team, relational and technical risks, organizational factors, social and ethical values. Our paper discusses the themes evoked in each category and their relevance for the included DHT. Discussion: In discussing the results, we present social acceptability factors of the different DHT. In addition, we demonstrate the importance of considering sociocultural diversity in the study of social acceptability for DHT. Implications: The results of this study have implications for practitioners who are the instigators of DHT implementation with healthcare service users. By understanding factors of social acceptability among francophone-speaking communities, practitioners will be better suited to propose and support the implementation of technologies in ways that are suitable for these individuals. For policymakers, this knowledge could be used for developing policy actions based on consideration for diversity.

Keywords: Digital health technologies, Social acceptability, francophone, Meta-ethnography, Sociocultural diversity

Received: 27 May 2023; Accepted: 31 Aug 2023.

Copyright: © 2023 Gauthier-Beaupré and Grosjean. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Sylvie Grosjean, University of Ottawa, Ottawa, Canada

People also looked at