The politics of universal health coverage
- 1 Department of Political Science, University of Guelph, Guelph, ON, Canada.
- 2 Seattle, WA, USA.
- 3 Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
- 4 Department of Political Science, University of Toronto, Toronto, ON, Canada. Electronic address: [email protected].
- PMID: 35594878
- DOI: 10.1016/S0140-6736(22)00585-2
The UN has declared universal health coverage an urgent global goal. Efforts to achieve this goal have been supported by rigorous research on the scientific, technical, and administrative aspects of health systems design. Yet a substantial portion of the world's population does not have access to essential health services. There is growing recognition that achieving universal health coverage is a political challenge. However, fundamental concepts from the political science discipline are often overlooked in the health literature. This Series paper draws on political science research to highlight the ways in which politics can facilitate, or stymie, policy reform. Specifically, we present a framework of analysis that explores how interests, ideas, and institutions shape universal health coverage. We then examine key considerations relating to the implementation of relevant policies. This Series paper shows that a political understanding of universal health coverage is needed to achieve health for all.
Copyright © 2022 Elsevier Ltd. All rights reserved.
- Health Care Reform*
- Universal Health Insurance*
- Open access
- Published: 10 October 2014
Achieving equity within universal health coverage: a narrative review of progress and resources for measuring success
- Anna M Rodney 1 &
- Peter S Hill 2
International Journal for Equity in Health volume 13 , Article number: 72 ( 2014 ) Cite this article
Equity should be implicit within universal health coverage (UHC) however, emerging evidence is showing that without adequate focus on measurement of equity, vulnerable populations may continue to receive inadequate or inferior health care. This study undertakes a narrative review which aims to: (i) elucidate how equity is contextualised and measured within UHC, and (ii) describe tools, resources and lessons which will assist decision makers to plan and implement UHC programmes which ensure equity for all.
A narrative review of peer-reviewed literature published in English between 2005 and 2013, retrieved from PubMed via the search words, `universal health coverage/care’ and `equity/inequity’ was performed. Websites of key global health organizations were also searched for relevant grey literature. Papers were excluded if they failed to focus on equity (of access, financial risk protection or health outcomes) as well as focusing on one of the following: (i) the impact of UHC programmes, policies or interventions on equity (ii) indicators, measurement, monitoring and/or evaluation of equity within UHC, or (iii) tools or resources to assist with measurement.
Eighteen journal articles consisting mostly of secondary analysis of country data and qualitative case studies in the form of commentaries/reviews, and 13 items of grey literature, consisting largely of reports from working groups and expert meetings focusing on defining, understanding and measuring inequity in UHC (including recent drafts of global/country monitoring frameworks) were included.
The literature advocates for progressive universalism addressing monetary and non-monetary barriers to access and strengthening existing health systems. This however relies on countries being effectively able to identify and reach disadvantaged populations and estimate unmet need. Countries should assess the new WHO/WB-proposed framework for its ability to adequately track the progress of disadvantaged populations in terms of achieving equitable access, effective coverage and financial risk protection within their own settings.
Recently published resources contextualise equity as a measurable component of UHC and propose several useful indicators and frameworks. Country case-studies also provide useful lessons and recommendations for planning and implementing equitable UHC which will assist other countries to consider their own requirements for UHC monitoring and evaluation.
Universal health coverage (UHC), defined by the 2005 World Health Assembly as “ access to key promotive, preventive, curative and rehabilitative health interventions for all at an affordable cost, thereby achieving equity in access ”, [ 1 ] has become a rallying call for global health. By 2012, over 90 countries had formally endorsed the United Nations Resolution to make UHC a key global health objective [ 2 ] and to date, more than 70 countries have requested technical assistance from the World Health Organization (WHO) in implementing UHC [ 3 ]. Recently, UHC has been heralded as `the third global health transition’ [ 4 ] and has featured prominently in discourse around the post-2015 Sustainable Development Goals (SDGs). With health likely to receive only one goal, UHC has been strongly advocated for its ability to provide an umbrella goal, incorporating both the unfinished infectious, maternal and child health (MCH) focus of the millennium development goals (MDGs) as well as the emerging non-communicable disease (NCD) agenda [ 5 ].
As the end of the MDGs draws near and discussions converge on the future of global health, now is a critical time to stop and take stock. Failure to address equity was deemed the most serious shortcoming of the MDGs [ 6 ] with many countries neglecting the most vulnerable populations by focusing instead on quantified targets which did not, for the most part, promote universal cover [ 7 ]. While equitable access and financing should be integral outcomes of UHC, evidence emerging from country case studies is however showing that in spite of gains in health coverage, and/or the overall level of population health, inequities can persist or even widen when there is insufficient focus on equity [ 8 ]-[ 12 ]. To ensure that the push towards UHC does not make the same mistakes and leave the same disadvantaged populations behind, countries and development partners must make equity an explicit priority within UHC design and ongoing monitoring and evaluation plans. Care should also be taken not to embark on the path to UHC with undue haste and inadequate planning, or risk creating a scenario where the `inverse equity hypothesis’ [ 8 ] holds true (i.e. whereby interventions reach the most privileged groups first and then `trickle down’ to the poor and marginalised), effectively widening the disparity gap and undermining the true meaning and intent of UHC.
With UHC having been criticised for being too broad a goal, open to different interpretations, and disaccord around the meanings of its component parts (i.e., `universal’, `access’, `effective coverage’ and `need’) [ 13 ], it can be difficult for countries to best decide how to turn the idealistic goal of UHC into practical measures. This is particularly the case for low to middle income countries (LMICs) which are often following UHC models which have arisen in developed nations such as the United Kingdom and Japan. In practice, most countries tend to fall short of full universality - whether it be in the breadth (reaching all population groups), depth (the inclusion of all needed services) or height (the proportion of costs covered) [ 13 ]. While most countries aim for 100% breadth, they settle for depth that is either `limited’ (i.e. a minimum package of cost-effective interventions) or `strategic’ (i.e. scaling up of selected programmes which are especially important for disadvantaged groups such as MCH services) [ 13 ]. Too often, equity of access to effective coverage, comprised of utilisation, need and quality, is not prioritised or measured and as D’Ambruoso [ 14 ] points out, `incomplete analysis of equity can inadvertently maintain disadvantage and exclusion’. This paper thus sets out to assist policy and decision makers to understand how to prioritise and measure equity within universal health care systems. It does this by elucidating how equity is currently contextualised and measured within UHC and describing useful tools and resources which will assist decision makers to successfully plan and implement universal health coverage programmes which inherently ensure equity for all.
The methodology for the study is a narrative review [ 15 ]. This was chosen in favour of a conventional systematic review for its strength in constructing a critical analysis of a complex body of predominantly qualitative literature [ 16 ] and for allowing the delineation of equitable achievement of UHC to emerge from our analysis of the literature rather than being defined a priori [ 17 ]. The goal of the review was to identify seminal and empirical literature on the conceptual issues, theoretical debates and empirical evidence around the measurement and attainment of equity within universal health coverage programmes.
The authors retrieved peer-reviewed scientific literature published in English between 2005 and 2013 from PubMed database using the keywords `universal health coverage’ OR `universal health care’ OR `UHC’ combined with the derivations of the terms `equity’ OR `inequity’ (i.e. equity/equitable/equitably/equities/equitability, with the same derivations for inequity). These search terms however retrieved an unwieldy number of approximately 9,000 papers and hence the search terms were limited to the above-mentioned UHC derivations plus the simplified terms `equity’ and `inequity’. This search returned 66 results of which the titles and abstracts were reviewed to determine relevance to the research objectives. Papers were excluded if they did not focus on equity (of access, financial risk protection or health outcomes) within UHC in addition to focusing on one or more of the following: (i) the impact of UHC programmes, policies or interventions on equity (ii) describe indicators, measurement, monitoring and/or evaluation of equity within UHC, or (iii) describe tools or resources to assist with such measurement. One article which was identified for inclusion based on the title and abstract was excluded because it was not available from either the scholarly databases or publisher. A total of 18 peer-reviewed articles were included. Additionally, as similar studies [ 18 ],[ 19 ] have shown that for reviews of complex evidence, formal protocol driven search strategies may fail to identify important resources, the authors also used the informal approach of referencing chaining to ensure that secondary research and non-research articles of theoretical importance to the topic were included. Accordingly, the following organisational websites were also searched for grey literature: WHO, World Bank (WB), UHC Forward and the Rockefeller Foundation. A purposive search of authors who have a prominent publishing record in equity (for example Gwatkin, Whitehead and Sengupta) was also conducted. The result of these informal mechanisms was the inclusion of an addition 13 items of grey literature including country case studies, reports from working groups and expert meetings, advocacy pieces and measurement tools/resources.
A preliminary review of the literature revealed a lack of empirically based publications. As such, the evidence-grading tools normally applied to a systematic review were not employed as they have been previously shown to exclude important expert information and pertinent empirical experience from published articles of a more conceptual nature [ 20 ]. Key details from the included papers were collated via a data extraction form adapted for the narrative review design which facilitated a simple summary archive of the bibliographic details of each resource, the study type, setting, findings and recommendations (See Additional file 1 : Table S1). Using the data extraction form, thematic analysis was conducted to identify dominant themes which are relevant to the study objectives and which inform a narrative discourse around the evolution of the measurement and attainment of equitable UHC, as presented in the next section.
A large number of papers did not evaluate/measure equity as an outcome of UHC, but rather described it as an integral component of UHC and were thus excluded. Most of the peer-reviewed journal articles consisted of secondary data analysis of medical and administrative records (n = 10) and reviews or commentaries (n = 5). There was also one prospective longitudinal cohort study, one systematic review and one narrative review. The organizational reports consisted of several analytical frameworks for monitoring of UHC at country and global levels, meeting reports describing the discussion of relevant indicators and the conceptualisation of equitable UHC, and several tools for estimating lives saved and economic outcomes of eliminating in-country disparities. Of the papers which did formally evaluate equity within UHC, roughly even proportions were from high-income and low to middle income countries (LMICs). There were several publications from Canada [ 21 ]-[ 24 ] and one each from Australia [ 25 ] and Taiwan [ 26 ]. Papers from LMICs included several from Thailand [ 12 ],[ 27 ],[ 28 ], Mexico [ 29 ], Chile [ 30 ] and Brazil [ 8 ],[ 31 ]. Studies from high-income countries tended to focus on access to specialised services and procedures such as mental health services [ 22 ],[ 23 ], and procedures for circulatory disease [ 22 ],[ 25 ]. They also focused on distinct populations such as children [ 23 ], the elderly [ 24 ] and psychiatric patients [ 22 ] rather than the population as a whole. Two studies showed that despite systems of free universal coverage, there was greater inequity, measured in terms of waiting times and receipt of procedures, for interventions which were non-urgent or elective, or for which there was a lack of clearly defined treatment protocols [ 21 ],[ 25 ]. This reveals a need for further research to determine whether the higher rates of procedures for discretionary care are due to overuse in advantaged individuals or underuse in disadvantaged groups; both having distinctly different policy implications for high-income UHC settings.
In general, studies from LMICs did explore the impact of equitable UHC on access to a basic package of essential services and health outcomes for the entire population, most commonly disaggregated by geographical area, socio-economic status and gender. A finding which was fairly consistent across both developing and developed contexts was that a key area in which inequity may arise within UHC is through disparities in quality of care and access to specialised clinical services. For example, although Thailand witnessed an increase in the access and coverage of primary care following the 2001 introduction of national health insurance, closer inspection of data revealed a disparity in the type of health facilities being accessed by different socioeconomic groups [ 12 ]. While the rich received most of their health care through provincial/general hospitals and private clinics, the poor generally received care from the lowest level facilities, health centres. In effect the poor had less choice of service provider, inadequate referrals and hence a potentially restricted package of benefits. This finding was congruent with a systematic review conducted by Hanratty and colleagues which also documented a pro-rich bias in the use of curative specialist hospital services but reasonably equitable access to primary health care [ 10 ]. The authors concluded that further research focusing on how to more effectively measure and monitor equity in universal health systems, with particular attention on how to define “need” and measure quality is necessary.
The literature also reveals consensus on the fact that measurement and monitoring of UHC, and equity as an implicit component, remains challenging and is an evolving concept. The progressive conceptualisation and means of measuring equitable UHC are described further in several items of grey literature from key global health stakeholders. For example, the 2013 World Health Report: research for universal health coverage [ 32 ] describes UHC as complex and advocates for further research into how quality and equity of access are monitored within UHC. Accepting that the social determinants of health influence the equity of coverage, WHO urges countries to measure UHC via a spectrum ranging from inputs and processes, to outputs, outcomes and impact and that rather than trying to measure the coverage of all national health services, countries should choose a subset of services and associated indicators that are representative of the overall quantity, quality, equity and financing of services, disaggregated by locally appropriate dimensions (i.e. key socio-economic variables such as income, occupation, disability, etc.). Frenz and Vega’s [ 13 ] background paper for the 1st Global Symposium on Health Systems Research, titled, `Universal health coverage with equity: what we know, don’t know and need to know’ also argues that UHC policies must be measured by the effect they have on equity of access across the social gradient. They describe equity of access as `the just distribution of health care according to need’. In a review of the literature they however conclude that very few (n = 12) papers explicitly refer to equity of access relative to UHC goals, and that most research focuses on horizontal equity using equity of utilisation as a proxy indicator for equity of access. This substitution has however driven the research to focus on services and interventions for which there is readily available data and fails to adequately define or address unmet need for the most marginalised and disadvantaged populations who, for a variety of reasons, do not utilise the formal health system. The authors present an analytical framework for assessing equity of access in UHC policies which is based upon access being viewed as a multidimensional, multi-step process influenced by both supply and demand side factors. Within this framework, equitable access is seen as the experiences and interactions of different socioeconomic groups with the health care system, within the broader context of the structural inequities that define social hierarchies and hence determine differential health needs.
The 2008 World Health Report [ 11 ] identified raising the visibility of health inequities in public awareness and policy debates as a key mechanism to address health equity within primary health care. The resource, `Universal health coverage: a commitment to close the gap’ produced by the Rockefeller Foundation in collaboration with Save the Children, UNICEF and WHO [ 3 ] serves to do this within the UHC context. As evidenced by the title, this resource represents an advocacy tool – effectively displaying a highly visible commitment by key global health players to reduce health disparities within UHC. This report presents lessons learned from countries undergoing UHC reforms as well as practical tools to assist countries to prioritise efforts to close the gap in health. The `Lives Saved Tool’ (LiST) can be used to estimate the impact of eliminating in-country wealth inequities in coverage of MCH services and an econometric analysis tool estimates the impact of more equitable health financing on mortality rates. Additionally, the resource also identifies policy options that governments and donors should consider when implementing reforms for UHC and estimates the effect this could have on health outcomes, setting out the implications for the SDGs.
In a review of the impact of universal coverage schemes in the developing world, the World Bank [ 33 ] concludes that a focus on affordability alone is insufficient for improving access and advocates for a more holistic approach to the dimensions of access which must be explicitly incorporated into the design of UHC programmes. The paper by Jacobs and colleagues [ 34 ] is instructive in this area. The authors first analyse all of the monetary and non-monetary barriers to access reported in the literature and classifies them as either demand or supply side barriers. It then describes established interventions that could be implemented in low-income Asian countries at district level by the health sector alone or in collaboration with other government departments, nongovernment or civil-society organizations and through the public and/or private sectors. An analytical framework mapping the identified barriers and interventions against four dimensions of access (geographical access, availability, affordability and acceptability), is then created and applied to two case studies to demonstrate its utility in assisting policy makers and health planners to identify barriers, devise interventions and assess their appropriateness.
Further work to establish useful and comparable indicators to measure UHC and equity has been the focus of several recent high-level meetings. For example, the Health Systems 20/20 meeting in July 2012 focused on `Measuring and monitoring country progress towards universal health coverage: concepts, indicators, and experiences’ [ 35 ]. At this meeting it was agreed that the creation of a conceptual framework for UHC which uses `equity-catalysing’ indicators to measure financial risk protection (FRP) and coverage with good quality health services for all was a priority. The Bellagio Centre of the Rockefeller Foundation responded in September 2012 publishing a report titled, `Measurement of trends and equity in coverage of health interventions in the context of universal health coverage’ [ 36 ], presenting a first draft framework and criteria for the development of an index and tracer indicators for global monitoring. It ascertains that to progress towards UHC, regular measurement of equity is paramount and describes the types of information and indicators needed to monitor the key components of UHC namely; coverage, effective coverage and quality of care, financial hardship, and equity . The report advocates that the absolute performance of the disadvantaged is most critical within UHC and that trends in the least performing groups should receive at least as much, if not more attention, than the whole population (i.e. the progress of the most disadvantaged groups should be compared against pre-intervention levels as well as to relative measures against the most advantaged groups and to pre-determined targets).
This concept of UHC monitoring was further expanded on in the WHO technical meeting in September 2013 as described in the summary report, `Measurement and monitoring of universal health coverage’ [ 37 ]. Discussion around the selection of appropriate indicators for equity analyses saw participants agree that in addition to disaggregation by sex and age group, disaggregation by household wealth and geography (both urban/rural and subnational administrative levels) is essential for countries to monitor internal disparities. Ultimately however, it was seen as the remit of countries to select their own locally appropriate dimensions of inequity and the global research community must create internationally comparable, tracer indicators. More recently, in December 2013, the World Bank Group and WHO published an instructive resource, titled `Monitoring Progress towards Universal Health Coverage at Country and Global Levels: A Framework’ [ 38 ]. This framework sets out likely timelines for UHC achievement aligned with the proposed 2015–2030 focus of the SDG agenda. It is suggested that global monitoring focus on essential health services coverage including a set of interventions related to the MDGs (focusing on communicable diseases, reproductive health, and nutrition for mothers and children) and a set of interventions related to chronic conditions and injuries (CCIs), (addressing NCDs, mental health, and injuries across the life course). Financial risk protection would also be monitored based on the incidence of catastrophic health expenditures and impoverishment due to out-of-pocket health payments. Importantly, the framework proposes explicit `equity goals’ comparing the progress of the poorest 40% of the population against aggregate population levels for the indicators around service coverage and protection from catastrophic payment goals. As impoverishment due to health expenditure is considered of equal importance across all economic groups, only aggregate levels would be measured. It is the mandate of countries to decide on the appropriate indicators to measure their own burden of disease within their own specific context. While the framework encourages truly universal (i.e. 100%) coverage of essential health services, a more realistic `80:40’ target is proposed to ensure that the poorest 40% of the population receives at least 80% coverage for interventions addressing the MDGs and the CCIs. In terms of financial protection, 100% of the population should be protected from both impoverishing and catastrophic health payments. The report presents an illustration of how these targets could be applied using data from world health surveys which effectively confirms that few developing regions currently achieve this 80:40 target for coverage of CCIs, MDGs and FRP. Feedback is currently being sought on this proposed framework and its acceptance as an umbrella goal for the SDGs remains to be seen.
The literature shows that the measurement of universal health coverage and equity, although complex and in a somewhat conceptual stage, has become more definitive of late. It gives rise to a number of common themes which will be discussed below in the context of other research on preventing health inequity across the health system (i.e. not exclusively in UHC programmes).
The current study found that the majority of papers, which, by and large, consist of lessons learned in individual country case studies, were consistent in their findings that UHC programmes should focus first on increasing coverage and decreasing economic barriers to access amongst the most disadvantaged groups. This fits with the term, ` progressive universalism ’ which has more recently been coined by Gwatkin and Ergo [ 9 ], describing affirmative action strategically targeted at the most disadvantaged in the planning of UHC programmes. The authors describe the success of this approach in reducing inequality in coverage in two country examples: Brazil’s Family Health Programme and Mexico’s Popular Insurance initiative. Both of these programmes initially concentrated coverage amongst the most disadvantaged groups and then extended initiatives with declining subsidies to those with higher income levels. In Brazil this was done by first reaching deprived municipalities, whereas the Mexican programme used existing social security mechanisms to extend health insurance to those without cover. As such, the authors advocate that deliberate adoption and scaling up of strategies should be aimed at reaching the poorest first and that equity must be taken into account when assessing overall progress in coverage at country level by using stratified analyses. Victora et al. [ 39 ], similarly describe how by targeting MCH interventions at the poor and disadvantaged from the start of the programme, several `countdown to 2015’ countries circumvented the inverse equity hypothesis. Their analysis showed, for example, that in countries where additional focus was on targeting the poor, the uptake of insecticide treated bed-nets increased rapidly across all wealth quintiles. Conversely, in the absence of a pro-poor focus, the uptake of nets was slower across the whole population and congregated disproportionally in the rich. Additionally, inequality remained static in countries which had reductions or only minimal increases in coverage, highlighting the effectiveness of progressive universalism as an effective means of reducing inequity. It is however essential that countries have accurate mechanisms for determining which populations are poor or disadvantaged. In this respect, it is recommended that the ministry of health collaborate with key stakeholders such as the ministry of social welfare or donor and development partners involved in poverty reduction initiatives who may have pertinent experience in identifying and reaching such populations [ 40 ].
While the literature advocates for UHC interventions which increase financial risk protection, it is important for countries and global stakeholders to take a broad view of what equitable financing actually means. For example, Sengupta [ 41 ] questions what he describes as the `dominant universal insurance model’ in many LMICs which promotes public provision of high-demand primary care but privatisation of more profitable tertiary services. He claims that this approach weakens already fragile public health systems, and declares that the aforementioned UHC programmes in Mexico and Brazil, as well as those of Chile, Colombia, India and Thailand (which are usually based on pooling of funds through insurance and through increased private provision of services), have actually increased inequity by decreasing the efficiency of the publicly funded health system. For example, although the Mexican UHC scheme rapidly expanded insurance to a large portion of the population and led to reductions in catastrophic and impoverishing health expenditure [ 29 ], various insurers now provide different packages of benefits, resulting in fragmentation of the health system and associated reductions in efficiency [ 41 ]. The current review also revealed similar findings in the research describing inequities in receipt of specialised health care in Canada and Australia in spite of universal insurance systems. Furthermore, Sengupta criticises the growing private sector for drawing crucial health work-force and resources away from the public sector and weakening its capacity to provide quality services. He concludes that a single, publicly-funded health system is better placed to offer equitable health outcomes and is more affordable for LMICs as it limits market-driven price setting by private providers and insurance companies. It thus becomes apparent from both country case studies and expert commentary, that achieving equity within UHC requires a holistic approach focused on creating and strengthening networks of accessible and high quality primary, secondary and tertiary health care. However, systems that work to strengthen health systems across the continuum are more likely to reduce inequity in the long run and the design of UHC financing mechanisms should consider the equity implications for both individuals, key populations, and the health system itself.
The abovementioned resources have been included as useful references for countries as they plan UHC programmes and monitoring and evaluation frameworks for UHC. The articles provide an understanding of key principles for measurement of equity within UHC, documenting the evolution of a draft framework and indicators. It is important that countries assess the relevance of resources to their own context being mindful of the type of indicators and data they can reasonably collect and use within current resources. Most importantly, they should analyse the equity impact of their selected indicators in effectively protecting the most disadvantaged populations. For example, if countries are to adopt the newly-proposed `80:40’ targets created by the WHO and WB (which focus on wealth quintiles and do not explicitly cover other dimensions of inequity such as gender, race, disability etc.) this could actually serve to hide or even increase in-country disparities. As such, this proposed monitoring framework should be given careful consideration by both countries and global stakeholders.
UHC has already located itself as a likely key to the transition from the MDGs to the post-2015 SDGs and must ensure that disadvantaged groups benefit as much as privileged ones by having an explicit focus on the measurement of equity. This review elucidates the changing position of equity within the UHC agenda, from being viewed as an integral component and implied outcome of UHC, to more recently being seen as a complex but measurable indicator of UHC success. This progressive contextualisation of UHC has led to a recent proliferation of tools and resources such as indicators and frameworks which aim to stimulate better definition and measurement of equity and UHC itself. Several lessons which have been learnt from countries implementing UHC regarding equitable access to a high quality range of health services provide valuable recommendations for other countries on the path to UHC. These resources and the discourse around their evolution will assist countries to consider their own requirements for monitoring and evaluating equity within their systems of universal health care and not falsely assume that equity is an inevitable outcome of UHC.
AR was responsible for carrying out the background research and writing of the article. PH provided editorial review. Both authors read and approved the final manuscript.
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This analysis was undertaken as part of Go4Health, a research project funded by the European Union’s Seventh Framework Program, grant HEALTH-F1-2012-305240, and by the Australian Government’s NH&MRC-European Union Collaborative Research Grants, grant 1055138.
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Rodney, A.M., Hill, P.S. Achieving equity within universal health coverage: a narrative review of progress and resources for measuring success. Int J Equity Health 13 , 72 (2014). https://doi.org/10.1186/s12939-014-0072-8
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Published : 10 October 2014
DOI : https://doi.org/10.1186/s12939-014-0072-8
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The Possibility of Universal Health Coverage in the United States
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This research paper intends to examine the ways in which universal healthcare coverage can potentially benefit the United States population, as well as investigate the challenges of implementing it. This paper found that there are many problems within the current U.S. healthcare system that can be improved by the implementation of Universal Health Coverage (UHC). Additionally, this paper includes evidence that UHC could have many economic and public health benefits in the United States. The paper then mentions the clear plans for implementing UHC in the U.S. and that there are other countries which have successfully implemented it. Finally, the paper ends by highlighting the certain difficulties that come with implementation as well as underscoring their possible solutions.
Keywords: universal healthcare coverage, United States healthcare, health insurance
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Healthcare Expenditure and Economic Performance: Insights From the United States Data
1 Koppelman School of Business, Brooklyn College of the City University of New York, Brooklyn, NY, United States
2 Gabelli School of Business, Fordham University, New York, NY, United States
Publicly available datasets were analyzed in this study. These can be found here: CMS; BEA; BLS; https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData ; https://www.bea.gov/iTable/iTable.cfm?reqid=70&step=1&isuri=1&acrdn=2#reqid=70&step=1&isuri=1 ; https://www.bls.gov/lpc/data.htm ; https://www.bls.gov/webapps/legacy/tusa_1tab1.htm .
This research explores the association of public health expenditure with economic performance across the United States. Healthcare expenditure can result in better provision of health opportunities, which can strengthen human capital and improve the productivity, thereby contributing to economic performance. It is therefore important to assess the phenomenon of healthcare spending in a country. Using visual analytics, we collected economic and health data from the Bureau of Economic Analysis and the Bureau of Labor Statistics for the years 2003–2014. The overall results strongly suggest a positive correlation between healthcare expenditure and the economic indicators of income, GDP, and labor productivity. While healthcare expenditure is negatively associated with multi-factor productivity, it is positively associated with the indicators of labor productivity, personal spending, and GDP. The study shows that an increase in healthcare expenditure has a positive relationship with economic performance. There are also variations across states that justify further research. Building on this and prior research, policy implications include that the good health of citizens indeed results in overall better economy. Therefore, investing carefully in various healthcare aspects would boost income, GDP, and productivity, and alleviate poverty. In light of these potential benefits, universal access to healthcare is something that warrants further research. Also, research can be done in countries with single-payer systems to see if a link to productivity exists there. The results support arguments against our current healthcare system's structure in a limited way.
Introduction and Background
Healthcare spending and the impact that it has on economic performance are important considerations in an economy. Some studies have shown that improvements in health can lead to an increase in Gross Domestic Product (GDP) and vice versa ( 1 – 3 ). Healthcare holds a significant place in the quality of human capital. The increased expenditure in healthcare increases the productivity of human capital, thus making a positive contribution to economic growth ( 4 , 5 ). However, there is ongoing debate on what kinds of healthcare spending and what level of optimal spending is beneficial for economic development ( 6 – 8 ).
The theory of welfare economics is relevant to the current research. Welfare economics is a branch that deals with economic and social welfare by analyzing how the resources of the economy are allocated among the social agents ( 9 , 10 ). Here, we analyze the allocation of resources in terms of spending within the healthcare sector and assess its influence on economic welfare. In addition to this, we draw from several related studies in laying a strong foundation for our research. The relationship between health and economic growth has been examined extensively across multiple studies ( 11 – 16 ). Based on a study that examined the impact of health on economic growth in developing countries, it was evident that a decrease in birth rates positively affected economic growth ( 17 ). During the period of study, health expenditures rose threefold, from $83M to $286M, and outpaced growth in GDP. The study showed that health and income mutually affected each other and concluded that problems affecting healthcare delivery caused negative impact on economic growth ( 18 ). Arora ( 19 ) investigated the effects of health on economic growth for industrialized countries and found a strong association. In a study of the impact of health indicators for the period 1965–1990 for developed and developing countries, economic performance in developing countries increased significantly with an improvement in public health ( 20 ). Studies have proposed that an annual improvement of 1 year in life expectancy increases economic growth by 4% ( 1 , 21 ). Similarly, another study in 2001 emphasized that the existence of a healthy population may be more important than education, for human capital in the long term ( 22 ). Examining 21 African countries for the 1961–1995 period and 23 Organization for Economic Cooperation and Development (OECD) countries for the 1975–1994 period with the extended Solow growth model, authors found that 23 OECD health stocks affect growth rate of per capita income ( 23 ). Muysken ( 24 ) also investigated whether health is one of the determinants of economic growth and concluded that an iterative relationship exists between economic growth and health—high economic growth leads to investments in human capital and to health advancement, and good population health leads to more labor productivity and economic growth. Aghion et al. ( 25 ) utilized the Schumpeterian growth theory to analyze channels associated with the influence of national health on economic growth. The theory emphasizes the importance of maternal and child health on the critical dimensions of human capital. Another element that has been shown to be a critical element for sustainable economic growth is high life expectancy ( 26 ). Aghion et al. ( 27 ) applied the endogenous growth theory, which proposes that a better life expectancy enhances growth, to analyze the relationship between health and economic growth. The study examined life expectancy for various ages in OECD countries and concluded that a decline in mortality rates for the age groups below 40 has the effect of increasing economic growth Aghion et al. ( 27 ).
Based on the above-mentioned studies, we surmise that higher income per capita is associated not only with life expectancy, but also with numerous other measures of health status. While health is not the only indicator of economic development—indeed, we need to consider the impact of other factors, such as education, political freedom, gender, and many other social attributes ( 1 , 3 , 28 )—health is definitely an integral non-income component that should be considered in a measure of economic development. People generally give high priority and value to a long and healthy life ( 2 , 25 ). Secondly, the rate of achievement of this goal to aspire for a long and healthy life differs widely across countries ( 11 , 13 , 29 ). The Human Development Index, in addition to suggesting a correlation between income and health, also expresses a strong correlation between an individual's place in the income distribution and his or her health outcomes within a country ( 2 , 30 ). This within-country correlation is particularly strong in developing countries. In comparing the growth of income with improvements in health outcomes, it is common to account for simultaneous causation. As an example, people who are healthy have the ability to be more productive in school and at work, reflecting that good health can be a precursor for better economic development ( 4 ). Additionally, a higher income allows individuals or governments to make investments that yield better health ( 28 ). Finally, differences in the quality of education, government, health, and other institutions across countries, in human capital, or in the level of technology can induce correlated movements in health and income ( 16 ). One also needs to account for the dynamic effects built into many of the potential causal outlets. For example, improvements in health may only result in increased worker productivity after a lag of several decades. Similarly, when life expectancy rises, there can be increases in population growth that may temporarily reduce income per capita ( 31 ).
The per capita health expenditures of countries vary in terms of economic development.
Whereas, high-income countries spend, on average on healthcare, $3,000 on each citizen, low-income countries only spend up to $30 per capita. It is also important to consider healthcare expenditure expressed as a percentage of GDP ( 5 , 14 ). While some countries spend higher than 12% of GDP on healthcare, others spend as little as 3% ( 32 ). There are at least two methods that can explain the association between a country's healthcare expenditure and economic performance. In the first scenario, healthcare expenditure is considered an investment in human capital. Human capital accumulation is then perceived to be a source of economic growth (e.g., via increased productivity). Therefore, an increase in healthcare expenditure is likely to be associated with a higher GDP ( 30 , 33 ). In the second scenario, an increase in healthcare expenditure can lead to regular health interventions (e.g., annual medical-checkups, preventive screening, etc.), which are likely to improve labor and productivity; this, in turn, will increase the GDP ( 34 ). Both these mechanisms reflect an iterative phenomenon between healthcare and GDP. Nevertheless, the relationship needs to be checked for endogeneity—which we aim to study in this research.
An important dimension in the relationship between health expenditure and economic performance is the factor of the productivity of workers. In developed countries, labor is scarce, and capital is abundant as a factor of production ( 2 , 31 , 35 ). But this situation is reversed in developing countries where economic growth and economies are based on labor. Here, an increase in individuals' poor health will likely lead to a loss in labor workforce and productivity ( 4 , 16 ). Therefore, addressing public health and health expenditures, though important for both developed and developing countries, is more critical for the latter ( 3 , 4 , 11 , 13 , 16 , 36 ). It is generally assumed from common knowledge that individuals who are healthier are able to work more effectively, in terms of physical and mental workload. Also, adults who were healthier as children will have acquired more human capital in the form of education, which is explained by the proximate effect of health on the level of income ( 37 ). Simultaneously, the impact of individual income on health is also important ( 38 , 39 ). Higher income can result in better health by facilitating access to better nutrition, preventative treatment, good sanitation, safe water, and affordable quality healthcare. Additionally, health can also be a cause of high income, by allowing individuals to work more, be more productive and earn higher income during the lifetime ( 35 ).
The impact of health on education is an important factor that plays a role in healthcare expenditure and economic performance ( 30 , 33 ). Children who enjoy good health can attend school regularly and have the potential of high learning ability and cognitive development. Also, if good health continues through adulthood, it will enable the population to recover the investments in education ( 30 , 33 , 39 ).
Another significant dimension in the relationship that healthcare spending has with economic development is the impact of health on savings. Good health can increase the life expectancy and encourage an individual's motivation to have savings (such as for retirement) and to make more business investments, both of which are beneficial activities for economic performance ( 1 ). Population health is an important healthcare component whose impact should be considered. A healthy population can reduce the expense on national healthcare and increase the potential for earnings. In this manner, the economic impact of population health can occur at the micro and macro levels ( 1 , 2 , 4 , 5 ). It is no surprise that some countries assign a higher value to gains from health than gains from income ( 36 , 40 – 43 ). Additionally, most countries have witnessed an increase in life expectancy despite a persistent income gap over the last 50 years ( 44 ), reflecting the monetary benefits that can accrue from investing in healthcare ( 2 , 44 ).
In this research, we acknowledge the significance of healthcare expenditure and analyze its association with the economic performance. We conduct the analysis at a national level for the United States using the data from the Bureau of Economic Analysis (BEA) and the Bureau of Labor Statistics (BLS). We incorporate the techniques of visual and descriptive analytics ( 45 – 47 ). Our findings provide insight on the differences in health spending and economic performance across the various states of the U.S. The research offers implications for governments 2008; and national policy makers to identify dimensions of healthcare that contribute to national economic performance. It is especially important for policy that addresses population health issues of a nation.
The rest of the paper is organized as follows: section Research 2 describes the methodology; section 3 presents the analyses and results; section 4 contains a discussion of results with implications; section 5 offers the scope and limitations of the research; and finally, section 6 presents the conclusions.
Data collection and variables.
We analyze state-level data and ascertain patterns that offer insight into the healthcare spending and economic performance of various states in the United States. Our methodology includes the stages of data collection and variable selection, data preparation, analytics platform and tool selection, and analytics implementation. We collected economic and health data from the Centers for Medicare and Medicaid Services (CMS) ( https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData ), Bureau of Economic Analysis (BEA) ( https://www.bea.gov/iTable/iTable.cfm?reqid=70&step=1&isuri=1&acrdn=2#reqid=70&step=1&isuri=1 ), and the Bureau of Labor Statistics (BLS) ( https://www.bls.gov/lpc/data.htm ; https://www.bls.gov/webapps/legacy/tusa_1tab1.htm ) for a period of 12 years (2003–2014). The variables relate to various economic performance and healthcare spending indicators. Table 1 shows the variables in the research.
List of variables.
The data was analyzed using the business intelligence tool Tableau for visualization, R programming language for regression analysis, and SPSS Modeler for neural network analysis.
Visual Analytics Method
We utilize visual analytics to analyze healthcare spending and economic performance data. With visual analytics, one can discover patterns and relationships that are unexpected, and get timely and rational assessments of the phenomenon that is being analyzed ( 46 , 48 ). Descriptive analytics, as a technique in visual analytics, helps one understand past and current trends and make informed decisions in a domain ( 48 ). By deploying this approach, we take a more data-driven approach to understanding the trends and associations between healthcare expenditure and economic performance scenario.
The technology of analytics is used increasingly in the domain of healthcare. As a business intelligence component, analytics allows statistical and quantitative analyses of large data repositories, enabling evidenced-based decision making ( 49 ). Specifically, in the domain of healthcare, analytics offers timely, relevant and quality information that can help healthcare entities and governments optimize health resource allocation goals effectively ( 50 ).
We deploy visual analytics based on the belief that it offers an effective tool to comprehend healthcare expenditure at a national level and analyze its impact on economic performance. We now discuss the results of our analyses in the following section.
Analyses and Results
We analyzed the data for patterns and relationships between the indicators of healthcare spending and economic performance. Healthcare expenditure refers to aggregate healthcare spending in an economy, including expenditure relating to hospitals, home health agencies, prescription drugs, nursing facilities, and personal healthcare.
Distribution of Hospital Expenditure Per Capita by Hospitals
To get an idea of the state of hospital expenditure we looked at the distribution of expenditure by hospitals in the country ( Figure 1 ). Hospital expenditure includes all service provided to patients, including room, ancillary charges, physician services, in-patient pharmacy services, and nursing home and home care. In Figure 1 , the intensity of color of the bars depicts the number of hospitals such that the darker the color, the higher the number of hospitals with the expenditure. Clearly, the distribution is right-skewed. While the majority of the hospital expenditures per capita rank between $1,600 and $3,500, there are several outliers on the right side. Additionally, even though per capita hospital expenditure on average is within $3,500, there are still some hospitals where the average cost is higher.
Per capita hospital expenditure distribution.
Hospital Expenditure Per Capita and GDP Per Capita by State
We now looked to see if there was any association between the hospital expenditure per capita and the GDP rank of the state ( Figure 2 ). The figure depicts the per capita hospital expenditures by the intensity of the color (the darker the color, the higher the expenditures), and the state rank in terms of GDP per capita as a label in the state. We see that progressive states such as California with a high GDP rank have lower per person hospital expenditure; Nevada has a higher GDP rank than South Dakota but has a lower per capita hospital expenditure. In fact, the hospital expenditure in South Dakota is almost double that of Nevada. This suggests that the states that have higher economic performance (GDP) have legislative and innovative measures that support healthcare research, thereby resulting in lowered costs to the patients.
Per capita hospital expenditures and per capita GDP rank by state.
Population and Per Capita Healthcare Expenditure
Having compared the healthcare expenditure of a state with its GDP, we now wanted to see if there was any association with the population of a state ( Figure 3 ). In the bubble chart the size depicts the population of the state and the color depicts the healthcare expenditure (darker colors represent higher expenditures). Interestingly, we see that sparsely populated states such as District of Columbia (DC) have higher healthcare spending than densely populated states like Texas. On the other hand, states like New York have high population and high expenditure. Therefore, there appears to be no correlation between population size and total average per capita expenditure, proving that population qualifies as a control variable in our dataset.
Overview of population size and total per capita healthcare expenditure.
Association of Hospital Expenditure With GDP Per Capita and Changes in Multifactor Productivity Over Time
We wanted to study the pattern of growth of hospital expenditure with GDP and with changes in multifactor productivity, from 2003 to 2014 ( Figure 4 ). Both associations are shown side by side in Figure 4 .
Relationship of hospital expenditures with per capita GDP, and changes in multifactor productivity.
In Figure 4 , the circles represent the performance for a year, with the intensity of the color indicating the recency of the year. In terms of the graph showing average per capita GDP and average per capita hospital expenditure, we see that since 2003, as the average per capita GDP increases, so does the per capita hospital expenditure. The positive correlation between the average per capita GDP and average per capita hospital expenditure implies that, by proxy, healthcare has a positive effect on GDP (economic performance).
The other graph in Figure 4 shows the relationship of Multifactor Productivity (MFP) with hospital expenditure. MFP is a measure of economic performance that reflects the overall efficiency with which inputs are used to produce outputs. Figure 4 shows that since 2003, the average per capita hospital expenditure has been increasing, but there is no obvious pattern in association with the changes in multifactor productivity. Also, it is worth noting that the trend line shows that there is a slight negative correlation between the changes in multifactor productivity and average per capita hospital expenditure.
Association of Personal Healthcare Costs With Average Hours Per Day Spent on Purchasing Goods and Services, and With Changes in Multifactor Productivity (MFP)
Personal healthcare expenditure determines the out-of-pocket costs incurred by the population. Figure 5 represents two associations of hospital expenditure side by side—with general purchases of the population, and with changes in MFP. In the association of hospital expenditure with general purchases of the population, we estimated the purchasing power of the population using the average hours spent per day on purchasing goods and services. The figure shows a negative relationship such that as personal healthcare costs increase, the average time spent on purchases declines. This is because as personal healthcare costs increase, the amount of available money for spending decreases, affecting the time spent on buying goods and services. Figure 5 also shows the association between hospital expenditure and changes in MFP. The line chart/trend line in the figure indicates that there is no obvious correlation between personal healthcare costs and percent change in MFP. This is consistent with the analysis of hospital expenditure which also had no association with MFP. One can infer that that a change in healthcare costs does not affect the economic cycle.
Relationship of personal healthcare costs with average hours per day spent on purchasing goods and services, and changes in multifactor productivity.
Association of Healthcare Expenditure With Per Capita Personal Income
In looking for associations between healthcare expenditure and personal income ( Figure 6 ) we see that between 2003 and 2014, personal income mostly increased while total healthcare spending has increased as a percentage of income. This confirms two trends—Americans spend more on healthcare over time; and personal income increases faster than that of healthcare expenditure in terms of dollar amount.
Association between per capita healthcare spending and personal income.
Association of Hospital and Physician Expenditures With Labor Productivity
Physician expenditure and hospital expenditure are components of overall healthcare costs of a state. We wanted to analyze if there was any association of labor productivity with physician expenditure and hospital expenditure ( Figure 7 ). The scatterplot in the figure shows that spending in physician or hospital costs is positively correlated with an increase in labor productivity. It appears that healthcare spending has a positive relationship with labor productivity in the United States.
Correlation between labor productivity and hospital and physician expenditures.
Association of Per Capita Healthcare Expenditure With Labor Productivity and With GDP
In terms of healthcare expenditure, the above analysis revealed that physician and hospital expenditure were positively associated with labor productivity. We next explored if total healthcare expenditure which is an aggregate of all components is also associated with labor productivity, and with per capita GDP, both shown side by side ( Figure 8 ). The figure shows that as the total healthcare expenditure increases, labor productivity also increases. There is a positive correlation between total per capita healthcare expenditure and labor productivity. Thus, by increasing healthcare expenditure, the health status of Americans will improve, increasing labor productivity. Figure 8 also shows the association of total healthcare expenditure with an alternate measure of economic performance, namely the GDP. The figure depicts a chart with a trend line that shows that as total healthcare expenditures increase, GDP also increases. Healthcare expenditure of a state has a positive relationship with the GDP of the state.
Relationship between total per capita healthcare expenditures and labor productivity.
Associations Between Personal Healthcare Expenditure, Hospital Expenditure, Nursing Expenditure, and Average Weekly Hours Worked
It is important to see the relationship between average hours worked (weekly) as a measure of economic performance and healthcare expenditure comprising personal healthcare, nursing, and hospital costs ( Figure 9 ). From the figure we can see that as each of the health costs increases, there is no obvious change for average weekly hours. There appears to be no correlation between health costs and average weekly hours, which indicates there is no effect on productivity.
Relationship between personal health, hospital, nursing costs, and average weekly hours.
Association of Personal Healthcare Expenditure With Per Capita GDP
Figure 10 shows the association between personal healthcare expenditure and GDP per capita.
Correlation between per capita personal healthcare expenditure and per capita GDP.
In the figure the bar graph depicts the GDP and the trend line represents the personal healthcare expenditure. The last 2 years, which have a lighter color, represent the forecasted result. The chart shows that personal expenditure costs have steadily risen over the years, while the GDP does not show large fluctuations. A correlation is hard to establish between personal healthcare costs and GDP; it is possible that there may be extraneous types of healthcare expenditure that have an influence on the GDP.
Distribution of Various Types of Healthcare Expenditures Across Years
It is important to explore the different types of healthcare expenditure and their distribution over the years ( Figure 11 ). Personal healthcare expenditure (includes private and public insurance) has the highest average of the types of spending in the years 2003 to 2014. This is followed by hospital and physician expenditure. The rise in personal healthcare expenditure has led to a high demand for reasonably priced private health insurance across the United States. The government needs to increase the affordability of public insurance to increase the reach and benefit more people.
Distribution of various types of healthcare expenditures across years.
Association Between Personal Healthcare Expenditure Per Capita and Total Hours Worked
Figure 12 shows the relationship between personal healthcare expenditure and total hours worked for the years 2003 to 2014. The growth of expenditure costs is not proportional to the rate of change in working hours. There appears to be no correlation between expenditure and working hours; however, from the other analyses, we know that healthcare expenditure has a positive correlation with income.
Relationship between hours worked and per capita personal healthcare expenditure.
Association Between Personal Healthcare Expenditure and Other Personal Expenditure
The relationship between personal healthcare expenditure and other personal expenditure is shown in Figure 13 . The scatterplot shows the personal health expenditure having a positive correlation with the other personal expenditure. The ratio between them basically stays the same, which shows that an increase in personal health care expenditure does not impose a burden, significant enough to cause a reduction in other personal spending.
Relationship between personal health expenditure and other personal expenditure.
Important Healthcare Expenditure Predictors of Per Capita GDP
We wanted to explore which type of healthcare expenditure has the most significant influence on GDP. Figure 14 shows a machine learning based neural network model to analyze which type of healthcare spending affects the per capita GDP the most. The bars indicate to what extent the associated variable is determined by the target variable, namely per capita GDP. Among the different types of healthcare spending, hospital expenditure affects the per capita GDP the most, followed by personal healthcare. It confirms the fact that the effect of healthcare spending in the different care areas will have differential effects on the economy.
Importance of healthcare expenditure predictors for per capita GDP.
Our research offers several important findings that have implications for policy. While healthcare expenditure is negatively associated with multi-factor productivity, it is positively associated with labor productivity, personal spending, and GDP. However, this is not a causal relationship, and our inference is limited. Nevertheless, the research establishes, within the scope of the study, that an increase in healthcare expenditure has a positive relationship with economic performance. There are also variations across states that justify further research. Building on this and prior research, policy implications include that the good health of citizens indeed results in overall better economy. Therefore, investing carefully in various healthcare aspects would boost income, GDP, and productivity, and alleviate poverty. In light of these potential benefits, universal access to healthcare is something that warrants further research. Also, research can be done in countries with single-payer systems to see if a link to productivity exists there. Our results support arguments against our current healthcare system's structure in a limited way.
Scope And Limitations
Our research has a few limitations. First, economic events such as recession may affect the validity of our results. Also, this research uses several proxies for productivity. Ideally, we should also track the hours of time spent being sick, which will affect both attendance and productivity; however due to unavailability of data this was not feasible. This research studies the data at a state level while other studies may drill down further to county and city level. Our research uses secondary data and is therefore subject to the limitations posed by the secondary source in terms of availability and veracity. Finally, the effects of healthcare spending on a different group (such as varying age groups) within a state were not studied. Nevertheless, the study offers a window into the relevance of healthcare expenditure in overall economic performance at a national level.
Our findings suggest that, in general, there is a positive association between healthcare spending and the economic indicators of labor productivity, personal income, per capita GDP, and other spending. Also, personal healthcare spending adversely impacts time spent on purchases of goods and services. There is no association between healthcare spending and change in multi-factor productivity (MFP) or working hours. Different states require varied investment in personal health expenditure, even if they have the same level of labor productivity. Overall, the study contributes to the growing literature on healthcare expenditure and economic performance. It outlines how the government can allocate healthcare expenditure in key dimensions that can stimulate economic growth while also improving the well-being of the population. It is also critical that policy makers implement appropriate policies at the macroeconomic level—targeted at public health expenditure and economic development. Overall, in light of the potential benefits of healthcare to the economy, universal access to healthcare is an area that warrants further research.
Data Availability Statement
Since this study uses aggregated national data, both ethical approval and written informed consent from the participants were not required for this study in accordance with the local legislation and institutional requirements.
VR and WR contributed equally to all parts of manuscript preparation and submission.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Reference this Research Paper (copy & paste below code): Arshiya Mahajan (2023); The Economics of Universal Healthcare: A Comparative Analysis of Healthcare Systems and Their Economic Effects; International Journal of Scientific and Research Publications (IJSRP) 13(08) (ISSN: 2250-3153), DOI: http://dx.doi.org/10.29322/IJSRP.13.08.2023.p14020
This article is part of the research topic.
Organizing and Financing Universal Primary Health Care Systems – Best Practices and Blueprints for Low- and Middle-Income Countries
Collectively achieving primary health care and educational goals through school-based platforms: financing solutions for intersectoral collaboration
- 1 The Palladium Group, United States
The final, formatted version of the article will be published soon.
Despite abundant evidence demonstrating that improvements to health and education are positively correlated, and the importance of school-based platforms to achieve shared impacts, collaboration between ministries of health and education remains limited across low- and middle-income countries. Enhancing this collaboration is essential to realize mutually beneficial results, especially following the COVID-19 pandemic, which severely impacted health and education outcomes globally and highlighted the importance of resilient, domestically funded systems for delivering key social services including primary health care and education. We argue that the lack of an effective joint financing mechanism has hindered adoption of collaborative multisectoral approaches such as the WHO/UNESCO’s Health Promoting Schools (HPS) model. HPS is well-positioned to organize, finance, and deliver primary health care and education services through a school-based platform and strategy. Case studies from several low- and middle-income countries highlight the need to expand limited inter-ministerial collaborations to achieve cross-sectoral benefits and ensure sustainability of HPS beyond the lifecycle of external partners’ support. It is important to identify ways to widen the resource envelope for sector-specific activities and create efficiencies through mutually beneficial outcomes. This paper offers two pragmatic solutions: an inter-ministerial joint financing mechanism that starts with alignment of budgets but matures into a formal system for pooling funds, or a fixed-term co-financing mechanism that uses donor contributions to catalyze inter-ministerial collaborations. Achieving sustainability in these initiatives would require engaging the ministries of health, education, and finance; developing a common administrative, financial, and monitoring mechanism; and securing long-term commitment from all concerned stakeholders.
Keywords: Primary Health Care ( PHC), Education, health-promoting schools, Joint financing, Co-financing, Intersectoral
Received: 11 Jul 2023; Accepted: 14 Nov 2023.
Copyright: © 2023 Schiff, Jha, Walker and Gonzalez-Pier. 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: Miss. Mackenzie Schiff, The Palladium Group, Washington, DC, United States
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Research paper on universal health care.
April 28, 2013 UsefulResearchPapers Research Papers 0
The natural human right to health care in case of its deterioration (or damage) is met through the health care system. Economic aspects, conditions, performance, and prospects of the health care system is largely dependent on the financing system of the sector. Here are three basic sources of the health care system financing: government (budget), social insurance, and private health insurance.
There are no, of course, such pure forms in practice. Therefore, health care financing is usually provided in a mixed form. However, independently of which form of financing is dominant, they call it National Health Service in England, Ireland, Italy, and Scotland, compulsory health insurance in Austria, Belgium, Netherlands, Germany, Sweden, and Japan and universal health care (USA), where about 90% of the population use the services of private insurance companies.
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Germany was one of the first countries where health insurance was introduced in1881.
The German model of health insurance has the following features:
- decentralization, which implies existing in the country more than 1,000 insurance offices: professional, territorial and substitute cash;
- compulsory health insurance;
- the main task of the government is creating optimal conditions for medical care and monitoring their implementation;
- division of responsibility between the government and insurance sickness funds to implement an active policy of restricting prices for medical services. Insurance sickness funds implement strict system of mutual settlements; introduce systems of co-payments to insured for drugs and other services.
The British model is characterized by the following features:
- high level of centralization. Compulsory health insurance covers 1/3 of the population;
- prevalence of budgetary finance system. Less than 10% of the budget of health care is financed by employers and more than 90% – at the expense of tax revenue;
- mandatory medical insurance for all employees. Housewives can benefit from voluntary health insurance program;
- patient pays 10% of the treatment;
- private insurance covers the categories of persons who are not subject to compulsory insurance, distribution of private voluntary insurance for those services that are not provided by the NHS.
The American model of health insurance is characterized by the following features:
- accumulation of funds in the central insurance fund;
- centralized fund allocation based on legally established form of payment. This system covers more than 20% of the population;
- voluntary group insurance at work covers about 60% of the population;
- voluntary insurance not at the place of work covers about 2% of the population;
- 15% of the population has no access to health insurance.
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Universality of universal health coverage: A scoping review
Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing
* E-mail: [email protected]
Affiliations School of Public Health, The University of Queensland, Brisbane, Australia, College of Medicine and Health Sciences, Bahir Dar University, Bahir Dar, Ethiopia
Roles Conceptualization, Supervision
Affiliation College of Medicine and Health Sciences, Bahir Dar University, Bahir Dar, Ethiopia
Affiliation School of Public Health, College of Medicine and Health Sciences, Bahir Dar University, Bahir Dar, Ethiopia
Roles Conceptualization, Methodology, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing
- Aklilu Endalamaw,
- Charles F. Gilks,
- Fentie Ambaw,
- Yibeltal Assefa
- Published: August 22, 2022
- Reader Comments
The progress of Universal health coverage (UHC) is measured using tracer indicators of key interventions, which have been implemented in healthcare system. UHC is about population, comprehensive health services and financial coverage for equitable quality services and health outcome. There is dearth of evidence about the extent of the universality of UHC in terms of types of health services, its integrated definition (dimensions) and tracer indicators utilized in the measurement of UHC. Therefore, we mapped the existing literature to assess universality of UHC and summarize the challenges towards UHC.
The checklist Preferred Reporting Items for Systematic reviews and Meta-analysis extension for Scoping Reviews was used. A systematic search was carried out in the Web of Science and PubMed databases. Hand searches were also conducted to find articles from Google Scholar, the World Bank Library, the World Health Organization Library, the United Nations Digital Library Collections, and Google. Article search date was between 20 October 2021 and 12 November 2021 and the most recent update was done on 03 March 2022. Articles on UHC coverage, financial risk protection, quality of care, and inequity were included. The Population, Concept, and Context framework was used to determine the eligibility of research questions. A stepwise approach was used to identify and select relevant studies, conduct data charting, collation and summarization, as well as report results. Simple descriptive statistics and narrative synthesis were used to present the findings.
Forty-seven papers were included in the final review. One-fourth of the articles (25.5%) were from the African region and 29.8% were from lower-middle-income countries. More than half of the articles (54.1%) followed a quantitative research approach. Of included articles, coverage was assessed by 53.2% of articles; financial risk protection by 27.7%, inequity by 25.5% and quality by 6.4% of the articles as the main research objectives or mentioned in result section. Most (42.5%) of articles investigated health promotion and 2.1% palliation and rehabilitation services. Policy and healthcare level and cross-cutting barriers of UHC were identified. Financing, leadership/governance, inequity, weak regulation and supervision mechanism, and poverty were most repeated policy level barriers. Poor quality health services and inadequate health workforce were the common barriers from health sector challenges. Lack of common understanding on UHC was frequently mentioned as a cross-cutting barrier.
The review showed that majority of the articles were from the African region. Methodologically, quantitative research design was more frequently used to investigate UHC. Palliation and rehabilitation health care services need attention in the monitoring and evaluation of UHC progress. It is also noteworthy to focus on quality and inequity of health services. The study implies that urgent action on the identified policy, health system and cross-cutting barriers is required to achieve UHC.
Citation: Endalamaw A, Gilks CF, Ambaw F, Assefa Y (2022) Universality of universal health coverage: A scoping review. PLoS ONE 17(8): e0269507. https://doi.org/10.1371/journal.pone.0269507
Editor: Wen-Wei Sung, Chung Shan Medical University, TAIWAN
Received: May 27, 2022; Accepted: August 9, 2022; Published: August 22, 2022
Copyright: © 2022 Endalamaw 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 its supporting information files.
Funding: The authors received no specific funding for this work.
Competing interests: Authors declared no conflict of interest.
Abbreviations: ANC, Antenatal Care; AR, Antiretroviral Therapy; CHI, Catastrophic Health Expenditure; FP, Family Planning; GBD2019, Global Burden Disease 2019; HIV/AIDS, Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome; IDs, Infectious diseases; NCDs, Non-communicable diseases; RMNC, Reproductive, Maternal, Neonatal and Child; SCA, Service Capacity and Access; SDGs, Sustainable Development Goals; UN, United Nations; UHC, Universal Health Coverage; WB, World Bank; WHO, World Health Organization
Universal health coverage (UHC) is a multi-dimensional concept that includes population coverage, services coverage and financial protection as its building blocks, as well as equity and quality in its integrated definition [ 1 ]. Health policy and decision makers believe UHC as a foundation to improve population’s health, facilitate economic progress, and achieve social justice [ 2 , 3 ]. It is also essential to minimize disparities, promote effective and comprehensive health governance, and build resilient health systems [ 4 ].
The United Nation’s (UN) post-2015 goals described UHC as the predominant approach to realize the 2030’s sustainable health goals [ 5 ]. It is also taken as an urgent priority in 2020 UHC high-level meeting to address global health crises, through delivering affordable essential quality healthcare services, including the pandemic COVID-19 [ 6 ]. The UN General Assembly further declared, at its 73 rd session, that global institutions and countries make healthcare accessible to one billion more people by 2023 [ 7 ] and 80 percent of the population by 2030 with no catastrophic health expenditures [ 5 ].
WHO and the WB established core tracers of health service coverage to monitor UHC [ 8 ]. These tracers are categorized under the main theme reproductive, maternal, neonatal, and child health (RMNC), infectious diseases (IDs), non-communicable diseases (NCDs), and service capacity and access (SCA). Another dimension of UHC in SDG 3.8.2 is financial risk protection, which is typically measured by catastrophic health expenditure (CHE) and impoverishment due to healthcare costs [ 8 ].
While no prior studies have been conducted to identify and map the available evidence on UHC, other related studies such as “a synthesis of conceptual literature and global debates” [ 1 ] and a scoping review of “implementation research approaches of UHC” [ 9 ] are available. In addition to these literature, another study assessed the hegemonic nature of UHC in health policy described historical background of how UHC emerged, and frequency of UHC mentioned in all fields of articles available in PubMed database [ 10 ]. None of those previous studies addressed the universality of UHC in terms of its building blocks and service types and summarized the findings from each study included in the review.
A scoping review of the studies on UHC and its dimensions is crucial to map and characterize the existing studies towards UHC. This will help to identify key concepts, gaps in the research, and types and sources of evidence to inform practice, policymaking, and research [ 11 ]. The goals of this scoping review towards universality of UHC were, first, to determine the distribution of articles across WHO and WB regions, health service types, and dimensions including major components and tracer indicators, and second, to synthesize barriers of UHC. This review provides insight that is useful in setting strategies, evaluating health service performance, and advancing knowledge on priority research questions for future studies.
Identifying a research question
The protocol of this scoping review is available elsewhere https://doi.org/10.21203/rs.3.rs-1082468/v1 . The overall activities adhered to the Arksey and O’Malley’s (2005) scoping review framework [ 12 ], which was expanded with a methodological enhancement for scoping review projects [ 13 ], and the Joanna Briggs Institute framework [ 14 ]. The review followed five steps: (1) identifying research questions, (2) identifying relevant studies, (3) study selection, (4) data charting, and (5) collation, summarization, and reporting of results. The checklist Preferred Reporting Items for Systematic reviews and Meta-analysis extension for Scoping Reviews were used ( S1 Checklist ) [ 15 ].
The research questions were developed by AE in collaboration with YA. The Population, Concept, and Context framework was used to determine the eligibility of research questions [ 16 ]. According to the framework, the population represented study participants to whom findings infer which includes people at any age or other important characteristics of study participants. Not all UHC expected to have population component, which is non-applicable in some research. The concept was overall UHC or financial risk protection, equity, quality, and coverage. Context includes the study settings or countries and, in this review, the global context.
Identifying relevant studies
Web of Science, PubMed and Google Scholar were used to find literature in the field. Hand search was also used to find articles from WB Library, WHO Library, UN Digital Library Collections, and Google. Using the relevant keywords and/or phrases, a comprehensive search strategy was established. Universal, health, "health care", healthcare, "health service”, quality, access, coverage, equity, disparity, inequity, equality, inequality, expenditure, and cost were search words and/or phrases. “AND” or “OR” Boolean operators were used to broaden and narrow the specific search results. Search strings were formed in accordance with the need for databases ( S1 Table ). Article search date was between 20 October 2021 and 12 November 2021, with the most recent update on 03 March 2022. The articles were imported into EndNote desktop version x7, which was used to perform an automatic duplication check. Manual duplication removal was also performed. The database search strategies are shown in the ( S1 Table ).
In consultation with YA, AE developed and tested study selection forms (inclusion and exclusion criteria) using a random sample from collected references, which were found using search strategy. A second meeting was held to approve the study screening form and process. Then, inclusion and exclusion criteria were applied during the article screening process for all articles. Studies conducted using the English language were included. Articles on overall UHC (UHC effective service coverage and FRP), UHC effective service coverage, UHC without specification with service coverage and FRP, and which reported coverage, quality, inequity, FRP in the outcome of the study or explored UHC research objectives were included. Types of study design included were quantitative, qualitative, mixed-research, and review types. The search was narrowed to include only literature published since 2015 to find studies which addressed the SDG target 3.8 and proceeding years. Non-English language literature, abstracts only, comments or letters to the editor, erratum, corrections, and brief communications were all excluded.
Articles’ titles, abstracts, and full texts were reviewed in stages. After duplicates were removed using EndNote desktop x7 software and manual duplication removal, titles were screened. After that, abstracts were used to screen the literature. Those who passed abstract review were eligible for full-text review. Full-text articles were also screened for data charting purposes. For articles with only an abstract, contact was made with the study’s corresponding authors.
A piloted and refined data extraction tool was initially developed to chart the results of the review from full-text literature. Data was examined, charted, and sorted according to key issues and themes. Author(s), publication year, WHO geographic category, WB group, study approach, studied domain or topic, UHC themes, and health care service types were all extracted.
Collation, summarization, and report of results
Based on years of publication, studied dimensions (interrelated objectives), WHO region, WB group, study approach, and health care service types, available articles were compiled and summarized with frequency and percentage.
A simple descriptive analysis was performed, and the results were presented in the form of tables and figure. The data reporting scheme was adjusted as needed based on the findings.
PubMed (n = 6,230) and Web of Science (n = 832) databases were searched. Google Scholar (n = 21), WB Library (n = 5), WHO Library (n = 7), UN Digital Library Collections (n = 13), and Google (n = 63) were also manually searched. A total of 7,171 records were discovered. Following title and abstract screening, 65 articles were chosen for full-text review. Finally, 47 articles were selected for scoping review ( Fig 1 ).
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Almost one-fourth of articles were from WHO Africa region and another 25.5% were across two or more WHO regions. According to income category, 42.5% were from lower-middle-income countries followed by 29.8% across two or more WB economy groups. More than half of the articles (54.1%) followed a quantitative research approach ( Table 1 ). The countries where each article conducted are available in S2 Table .
Health service types
Twenty articles [ 17 – 36 ] are categorized under health promotion. These articles were focused on pathways and efforts, program evaluation and change, opportunities and challenges, barriers/factors/enablers, community-based health planning and service initiative, perceived effect of health reform on UHC, health-seeking behaviour and knowledge, health security and health promotion activities, the impact of insurance on coverage, and SCA dimensions of UHC. Health promotion encompasses funding and infrastructure, health literacy, the development of healthy public policies, the creation of supportive environments, and the strengthening of community actions and skills, as well as any activities that assist governments, communities, and individuals in dealing with and addressing health challenges.
Six articles discussed treatment aspects of health services, which were access to care for illness, access to treatment for rheumatic heart diseases, neglected tropical diseases (NTDs), mental disorders and hypertension [ 37 – 42 ].
According to GBD-2019, WHO and WB tracers, FP and/or SCA components for promotion, immunization for prevention and other diseases in RMNC, IDs, NCDs for treatment aspects, nineteen articles were a combination of promotion, prevention, and treatment aspects [ 43 – 61 ].
One study looked at both the promotion and treatment of health services [ 62 ].
One study done on the quality of health care for disabled people [ 63 ] was classified as a palliative and rehabilitative care service type despite it did not adhere to palliative care assessment guidelines.
Components and dimensions of UHC
The main four components of UHC are RMNC, IDs, NCDs and SCA. Of included articles, RMNC was reported by 19 articles, 17 assessed NCDs were reported by 17 articles, CDs was assessed by 13 articles, and SCA was assessed by 9 articles. Regarding dimensions, coverage was assessed by 25 of articles; FRP by 13 articles, inequity by 10 articles and quality by 3 articles ( S2 Table ).
Tracer indicators for summary measure of UHC
Of 25 quantitative articles, 19 articles used various tracer indicators to assess UHC quantitatively; the remaining six quantitative articles assessed each empirical analysis of the potential impact of importing health services, access and financial protection of emergency cares, perceived availability and quality of care, the performance of district health systems, crude coverage and financial protection, health-seeking behaviour and OOP health expenditures, and the performance of health system.
Accessibility and affordability in China [ 64 ], as well as curative care and quality of care components in India [ 48 ] were developed as new tracers.
Ten tracers were used in RMNC component of UHC. Five tracers in IDs, seven tracers in SCA and 18 tracers were used NCDs component of UHC. Three tracers were used for FRP estimation. The iteration of tracers under four components of UHC effective service coverage and FRP is shown in Table 2 .
Barriers/challenges of UHC
Policy, health sector and cross-cutting barriers of UHC were identified. Financing, leadership/governance, inequity, regulation and supervision mechanism, and poverty were most repeated policy level barriers. Poor quality health services and inadequate health workforce were the common barriers from health sector challenges. Lack of common understanding on UHC was frequently mentioned cross-cutting barriers ( Table 3 ).
The purpose of this scoping review was to map existing research, and the most researched UHC dimensions, components and summarized main findings. Many articles were found in the African region and in countries with middle-income (lower and upper). Many of the studies followed a quantitative research approach. Palliative and rehabilitative health care types did not be well address in UHC research. The service coverage and financial protection dimensions were most frequently studied, followed by inequity and quality of health care services.
The current evidence found a greater number of articles than a scoping review of African implementation research of UHC [ 65 ]. This is because the former was conducted on a single continent and concentrated on UHC research approaches. Another bibliometric analysis, on the other hand, discovered a greater number of available evidence than the current scoping review [ 66 ]. Because it includes all available evidence as terminology, title, phrases, or words in policy documents, commentaries, editorials, and all frequency counts found in databases by the first search without the conditions of pre-established exclusion criteria. Aside from that, the bibliometric analysis included articles dating back to 1990. UHC is a global agenda that has improved the health of the global population through political support, funding, and active national and international collaborations [ 67 , 68 ]. The number of research output is likely increasing over time though current evidence shows that comparable numbers of articles are available in each year. An earlier bibliometric analysis discovered an increasing trend of UHC research outputs [ 66 ].
Many of the studies in this review used a quantitative approach. A prior scoping review conducted in Africa discovered that qualitative and mixed-methods studies were the commonest method to investigate UHC [ 10 ]. The former study did not consider financial protection research, UHC effective service and crude coverage, service capacity and access. UHC is intended to be quantified numerically as a summary index to track the progress of health care performance. Given the nature of UHC, fewer articles used qualitative research design to investigate its challenges, opportunities, and success of UHC. Various health systems and policies in low, middle, and high-income countries may present different barriers and facilitators to achieve UHC [ 69 – 71 ]. The current review has also identified policy, health system and cross-cutting barriers of UHC that were frequently explored by qualitative research.
Many number of countries are available in the European region and the high-income category [ 72 , 73 ]. In contrast, a substantial amount of UHC research was produced in middle-income countries, most were from African region. Trend analysis in health policy and systems research conducted on the overall research progress discovered that an increasing trend of publications in low-and middle-income countries between 2003 and 2009 [ 74 ]. This could be attributed to the nature of the health problems and the health policy in place regarding health research. Furthermore, health research budgets and clinical trial infrastructures may determine health research activities in each continent. Health budget might not always true in its effect of high research publication. For instance, evidence from a review finding indicated that nations with significant donor investment in health research may not necessarily produce a large number of research [ 75 ]. Articles available across WHO regions were comparable to frequency of articles in WHO African region. This might be due to UHC is a global strategy in monitoring the global process towards universal access to health care. The availability of UHC monitoring framework helps to conduct to conduct research at the multicounty level.
In 2019, the burden of NCDs was 63.8 percent worldwide, followed by IDs, RMNC, and nutritional disease (26.4 percent) [ 76 ]. In the summary measure of the UHC index, RMNC was the most frequently studied component followed by NCDs. This could be because many of the articles in the current review came from Africa and lower-and middle-income countries. In these countries, maternal and child morbidity and mortality were extremely high [ 77 ], making RMNC more likely to be investigated in UHC context. Similarly, a scoping review study on maternal, neonatal, and child health realized a high rate of publication in the most recent period [ 78 ].
This review provides an answer to the question of how much UHC is universal and how much UHC is covered in the current health systems and policy research. UHC tracer indicators are focused on health promotion, disease prevention, treatment, palliative, and rehabilitative health care services at the individual and population level. Promotion aspects of health services were more frequently investigated in the current review. This could be because those articles non-specific to either component of UHC were classified as health promotion. A single study was conducted on disabled population, close to palliative and rehabilitative health care types. Palliative care focuses on the physical, social, psychological, spiritual, and other issues confronting adults and children living with and dying from life-limiting conditions, as well as their families [ 79 ]. Assessment of pain and symptom management, functional status, psychosocial care, caregiver assessment, and quality of life are all part of a palliative care measurement and evaluation domains [ 80 ]. The Worldwide Hospice Palliative Care Alliance recommended research to improve palliative care coverage [ 81 ] in order to ensure equitable health care access for more than 40 million people who require palliative care each year worldwide [ 82 ]. However, UHC effective service coverage measurement indicators are appropriate only for assessing the promotion, prevention and treatment aspects of health care, even though all health care services are theoretically expected to be covered [ 54 ].
In terms of dimensions, coverage was more commonly studied. The framework for monitoring and tracking was initially established for effective service coverage and FRP. UHC’s service coverage is a collection of many individual disease indicators used to assess the performance of the health care system. Therefore, it is not surprising that many articles have been written about the coverage dimension. Aside from the usual trend of calculating the service coverage summary index, a few articles estimated UHC by combining effective service coverage and FRP indicators. In the current review, a few studies assessed the quality of care as a dimension of UHC; a single study developed a distinct quality of care measurement that integrated into the UHC matrix. Effective service coverage is predicated on the assumption that those in need receive high-quality health care services. Effective services coverage and quality are theoretically integrated. However, having a high UHC index value does not imply that high-quality care is provided for each specific disease. For example, in countries with high UHC index value [ 54 ], quality medical care services were found to be inadequate for patients with chronic diseases [ 83 ]. Quality of health care can be assessed using structure, process, and outcome indicators in the healthcare system [ 84 ].Therefore, generally, measuring the quality of care for specific disease is helpful for stakeholders, clinicians, and health policymakers working on specific health problems [ 85 ].
The UHC summary index is also useful in comparing the national and subnational progress of health system performance between countries and within a specific country. One of UHC’s primary functions is to promote health equity [ 3 ], and equity has been identified as a measurable component of UHC [ 86 ]. It is linked to social determinants that should be monitored over time, across or within different settings and populations [ 87 ]. Inequity in UHC service coverage studies was reported broadly. None of the UHC articles examined health disparities based on age, gender, race or ethnicity, residence, education level, or socioeconomic status. Moreover, range, absolute or relative difference, concentration index, and Gini coefficient were not used as equity measurement techniques in the included articles.
As implication to policy/program manager and researcher, more research is needed in settings where UHC has not been thoroughly investigated qualitatively. Future research better focus on the quality and equity dimension of UHC health care services. Given that the distinct nature of UHC tracers may limit UHC’s articles on health promotion, prevention, and treatment aspects, palliative and rehabilitative care services require attention in the future research environment. For specific health problems, additional review may be required to identify research gaps in specific tracer.
Strength and limitation
This is the first scoping review of UHC, and it is accompanied by the most recent articles. Our review identified UHC literature in each category of health service type.
In terms of limitations, this review included only articles conducted in English; articles conducted in other languages may have been missed, and geographical representation of UHC articles may have been over or underestimated for regions. When considering UHC dimensions, they may have a different level of research articles discovered if another mapping review is done for specific disease types.
Most articles were from Africa, across WHO regions and middle-income countries. Quantitative research approach has been frequently used. Equity and quality of services have got little attention in UHC research. Palliation and rehabilitation health services have also got little attention in the UHC research. Tracer indicators other than WHO and WB were developed and utilized in different countries. Policy, health sector and cross-cutting barriers of UHC were identified. Financing, leadership/governance, inequity, regulation and supervision mechanism, and poverty were most repeated policy level barriers. Poor quality health services and inadequate health workforce were the common challenges of the health sector towards UHC. Lack of common understanding on UHC was frequently mentioned as cross-cutting barrier.
S1 checklist. items followed in conducting this review..
S1 Table. Search strategy.
S2 Table. Articles’ country and main findings.
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