Universal Health Coverage and Labor Productivity in ASEAN: A Lagged Panel Analysis of Health Systems as Economic Infrastructure, 2000–2023

Background Life expectancy (LE) is an important metric for overall population health and well-being. The gender gap in LE can be used as a population health metric to capture progress and monitor health inequality in a specific setting. Health inequality is an expression of universal health care coverage and unequal access to health care and the quality of health care - otherwise known as ‘amenable’ mortality. Methods The Global Burden of Disease (GBD) Study- a comprehensive global epidemiologic database has developed and validated two population health metrics across 200+ countries- the Universal Health Coverage (UHC) Index (0-100) and the Healthcare Access and Quality (HAQ) Index (0-100) to monitor progress in these two specific domains for each country. We set out to examine the association of gender gap in LE with UHC and HAQ indices across 27 EU countries and the UK combined for year 2019 employing correlation and linear regression analyses. Results Overall, LE ranged from 73.3 years in Bulgaria to 83.1 years in Italy; UHC index was worst in Bulgaria (62.6), while Luxembourg (91.5) was the best performing nation; HAQ index had the highest score in the Netherlands (91.1), while Bulgaria had the lowest score (64.9). Lithuania had the largest gender gap in LE (9.2 years; M:71.5; F: 80.7), while the Netherlands had the narrowest gender gap (3.4 years; M:80.0; F: 83.4). On multivariable linear regression, gender gaps in LE were significantly associated with both HAQ (beta: -0.17; R2=0.66), and UHC (beta: -0.14; R2=0.52) across 27 EU countries and the UK combined. Conclusions Gender gap in LE can be a proxy measure to monitor progress in health inequality in terms of universal health care coverage, as well as health care access and quality of health care for a specific population setting. The findings suggest that gender gap in LE can be significantly reduced through expansion of universal health care and improving both access and quality of health care in the EU. Key messages • Gender gap in life expectancy can be a good proxy to monitor progress in health inequality for EU countries and the UK combined, which has 5.5 years of gender gap in life expectancy on average in 2019. • A 10% increase in both universal health care coverage and health care access and quality, can reduce gender gap in life expectancy by 1.4 and 1.7 years, respectively, across EU and the UK combined.

To estimate the technical efficiency of health systems toward achieving universal health coverage (UHC) in 191 countries. We applied an output-oriented data envelopment analysis approach to estimate the technical efficiency of the health systems, including the UHC index (a summary measure that captures both service coverage and financial protection) as the output variable and per capita health expenditure, doctors, nurses, and hospital bed density as input variables. We used a Tobit simple-censored regression with bootstrap analysis to observe the socioeconomic and environmental factors associated with efficiency estimates. The global UHC index improved from the 2019 estimates, ranged from 48.4 (Somalia) to 94.8 (Canada), with a mean of 76.9 (std. dev.: ±12.0). Approximately 78.5% (150 of 191) of the studied countries were inefficient (ϕ < 1.0) with respect to using health system resources toward achieving UHC. By improving health system efficiency, low-income, lower-middle-income, upper-middle-income, and high-income countries can improve their UHC indices by 4.6%, 5.5%, 6.8%, and 4.1%, respectively, by using their current resource levels. The percentage of health expenditure spent on primary health care (PHC), governance quality, and the passage of UHC legislation significantly influenced efficiency estimates. Our findings suggests health systems inefficiency toward achieving UHC persists across countries, regardless of their income classifications and WHO regions, as well as indicating that using current level of resources, most countries could boost their progress toward UHC by improving their health system efficiency by increasing investments in PHC, improving health system governance, and where applicable, enacting/implementing UHC legislation.

Universal health coverage in China: a serial national cross-sectional study of surveys from 2003 to 2018

BackgroundSeveral studies have indicated that universal health coverage (UHC) improves health service utilization and outcomes in countries. These studies, however, have primarily assessed UHC’s peacetime impact, limiting our understanding of UHC’s potential protective effects during public health crises such as the Coronavirus Disease 2019 (COVID-19) pandemic. We empirically explored whether countries’ progress toward UHC is associated with differential COVID-19 impacts on childhood immunization coverage.Methods and findingsUsing a quasi-experimental difference-in-difference (DiD) methodology, we quantified the relationship between UHC and childhood immunization coverage before and during the COVID-19 pandemic. The analysis considered 195 World Health Organization (WHO) member states and their ability to provision 12 out of 14 childhood vaccines between 2010 and 2020 as an outcome. We used the 2019 UHC Service Coverage Index (UHC SCI) to divide countries into a “high UHC index” group (UHC SCI ≥80) and the rest. All analyses included potential confounders including the calendar year, countries’ income group per the World Bank classification, countries’ geographical region as defined by WHO, and countries’ preparedness for an epidemic/pandemic as represented by the Global Health Security Index 2019. For robustness, we replicated the analysis using a lower cutoff value of 50 for the UHC index. A total of 20,230 country-year observations were included in the study. The DiD estimators indicated that countries with a high UHC index (UHC SCI ≥80, n = 35) had a 2.70% smaller reduction in childhood immunization coverage during the pandemic year of 2020 as compared to the countries with UHC index less than 80 (DiD coefficient 2.70; 95% CI: 0.75, 4.65; p-value = 0.007). This relationship, however, became statistically nonsignificant at the lower cutoff value of UHC SCI <50 (n = 60). The study’s primary limitation was scarce data availability, which restricted our ability to account for confounders and to test our hypothesis for other relevant outcomes.ConclusionsWe observed that countries with greater progress toward UHC were associated with significantly smaller declines in childhood immunization coverage during the pandemic. This identified association may potentially provide support for the importance of UHC in building health system resilience. Our findings strongly suggest that policymakers should continue to advocate for achieving UHC in coming years.

Several studies have indicated that universal health coverage (UHC) improves health service utilization and outcomes in countries. These studies, however, have primarily assessed UHC's peacetime impact, limiting our understanding of UHC's potential protective effects during public health crises such as the Coronavirus Disease 2019 (COVID-19) pandemic. We empirically explored whether countries' progress toward UHC is associated with differential COVID-19 impacts on childhood immunization coverage. Using a quasi-experimental difference-in-difference (DiD) methodology, we quantified the relationship between UHC and childhood immunization coverage before and during the COVID-19 pandemic. The analysis considered 195 World Health Organization (WHO) member states and their ability to provision 12 out of 14 childhood vaccines between 2010 and 2020 as an outcome. We used the 2019 UHC Service Coverage Index (UHC SCI) to divide countries into a "high UHC index" group (UHC SCI ≥80) and the rest. All analyses included potential confounders including the calendar year, countries' income group per the World Bank classification, countries' geographical region as defined by WHO, and countries' preparedness for an epidemic/pandemic as represented by the Global Health Security Index 2019. For robustness, we replicated the analysis using a lower cutoff value of 50 for the UHC index. A total of 20,230 country-year observations were included in the study. The DiD estimators indicated that countries with a high UHC index (UHC SCI ≥80, n = 35) had a 2.70% smaller reduction in childhood immunization coverage during the pandemic year of 2020 as compared to the countries with UHC index less than 80 (DiD coefficient 2.70; 95% CI: 0.75, 4.65; p-value = 0.007). This relationship, however, became statistically nonsignificant at the lower cutoff value of UHC SCI <50 (n = 60). The study's primary limitation was scarce data availability, which restricted our ability to account for confounders and to test our hypothesis for other relevant outcomes. We observed that countries with greater progress toward UHC were associated with significantly smaller declines in childhood immunization coverage during the pandemic. This identified association may potentially provide support for the importance of UHC in building health system resilience. Our findings strongly suggest that policymakers should continue to advocate for achieving UHC in coming years.

Universal health coverage post-2015: putting people first

The goal of universal health coverage (UHC) requires that everyone receive needed health services, and that families who get needed services do not suffer undue financial hardship. Tracking progress towards UHC requires measurement of both these dimensions, and a way of trading them off against one another. We measured service coverage by a weighted geometric average of four prevention indicators (antenatal care, full immunisation, and screening for breast and cervical cancers) and four treatment indicators (skilled birth attendance, inpatient admission, and treatment for acute respiratory infection and diarrhoea), financial protection by the incidence of catastrophic health expenditures (those exceeding 10% of household consumption or income), and a country's UHC performance as a geometric average of the service coverage index and the complement of the incidence of catastrophic expenditures. Where possible, we adjusted service coverage for inequality, penalising countries with a high level of inequality. The bulk of data used in this study were from the World Bank's Health Equity and Financial Protection Indicators database (2019 version), comprising data from household surveys. Gaps in the data were supplemented with other survey data and (where necessary) non-survey data from other sources (administrative, modelled, and imputed data). A low incidence of catastrophic expenses sometimes reflects low service coverage (often in low-income countries) but sometimes occurs despite high service coverage (often in high-income countries). At a given level of service coverage, financial protection also varies. UHC index scores are generally higher in higher-income countries, but there are variations within income groups. Adjusting the UHC index for inequality in service coverage makes little difference in some countries, but reduces it by more than 10% in others. Seven of the 12 countries for which we were able to produce trend data have increased their UHC index over time (with the greatest average yearly increases seen in Ghana [1·43%], Indonesia [1·85%], and Vietnam [2·26%]), mostly by improving both financial protection and service coverage. Some increased their UHC index, despite reductions in financial protection, by substantially increasing their service coverage. The UHC index decreased in five of 12 countries with trend data, mostly because financial protection worsened with stagnant or declining service coverage. Our UHC indicators (except inpatient admissions) are significantly and positively associated with GDP per capita, and most are correlated with the share of health spending channelled through social health insurance and government schemes. However, associations of our UHC indicators with the share of GDP spent on health and the shares of health spending channelled through non-profit and private insurance are ambiguous. Progress towards UHC can be tracked using an index that captures both service coverage and financial protection. Although per-capita income is a good predictor of a country's UHC index score, some countries perform better than others in the same income group or even in the income group above their own. Strong UHC performance is correlated with the share of a country's health budget that is channelled through government and social health insurance schemes. None.

Dear Editor, We appreciate the authors’ significant contribution to our understanding of the global disparities in healthcare resources and cancer burden. Their study offers valuable insights into the relationship between universal health coverage (UHC), healthcare expenditure, and cancer outcomes across 171 countries[1]. This research is crucial in identifying the role of healthcare resources in shaping cancer survival rates and mortality globally, and it provides a solid foundation for informing policy decisions aimed at reducing healthcare inequities. The study is in compliance with Transparency In the reporting of Artificial Intelligence – The TITAN guideline[2]. However, we believe the manuscript could be further strengthened by a more focused examination of specialized cancer care, particularly in urological oncology. Urological cancers, including prostate and bladder cancer, require highly specialized treatments that are often resource-intensive, involving advanced diagnostic tools and complex surgical procedures[3]. Yet, the study does not delve deeply into how disparities in healthcare resources affect outcomes in these specialized fields. A prospective investigation into how access to specialized urology departments, innovative treatment technologies, and multidisciplinary teams impacts patient outcomes in different regions would be invaluable. For example, the availability of robotic-assisted surgery, early detection programs, and advanced systemic therapies could be more directly linked to both survival and quality of life for urological cancer patients. To illustrate this point, we present in Figure 1 a visualization of the study’s reported associations between healthcare resources (UHC index and health expenditure) and key cancer outcomes. The pattern suggests that improved system-level investment is associated with better survival, supporting the notion that specialized cancer services – such as those required in uro-oncology – may benefit disproportionately from stronger healthcare infrastructure. Figure 1.: Associations between healthcare resources and cancer burden. Forest plot showing incidence rate ratios (IRRs) and 95% confidence intervals for the associations between (1) Universal Health Coverage (UHC) index and cancer incidence (ASIR), (2) UHC index and survival (1 − MIR), (3) current health expenditure as a percentage of GDP (CHE/GDP) and incidence, and (4) CHE/GDP and survival. Data visualized represent the exact IRR estimates reported in the published abstract of the study. Higher UHC and greater national health expenditure are associated with higher incidence (reflecting better detection) and improved survival, emphasizing the potential for system-level investment to support specialized oncology services, including urological cancer care. Building on this, we suggest that future research incorporate longitudinal data to track the evolving impact of healthcare infrastructure improvements over time[4]. This would allow for a better understanding of how investments in healthcare systems, particularly in specialized fields, lead to improved cancer outcomes. Given the rapid advancements in urological cancer care, tracking changes in survival rates as healthcare systems grow and adapt will offer important insights into the effectiveness of resource allocation in the long term. In addition, while the study employs the mortality-to-incidence ratio as a measure of cancer burden, expanding the analysis to include quality-adjusted life years (QALYs) or other patient-centered long-term outcome indicators could further enrich the findings[5,6]. This approach is especially relevant for prostate and bladder cancers, where treatment-related functional and psychological effects can be substantial. Evaluating healthcare resource allocation through these metrics would provide a clearer understanding of how disparities in specialized care affect both survival and overall well-being. We also recognize the importance of addressing gaps in healthcare access in low-resource settings. Future research could examine low-cost interventions such as mobile screening units or affordable diagnostic tools tailored for urological cancers. These targeted strategies may offer scalable opportunities to reduce the global burden of urological malignancies in resource-limited regions. In conclusion, while the study provides a crucial first step in understanding the links between healthcare resources and cancer burden, further research into specialized cancer care – particularly urological oncology – is essential to refine our understanding and improve outcomes. We look forward to seeing how these insights inform future investigations into global cancer care disparities.

Health and wellbeing as one of the Sustainable Development Goals requires all countries to achieve Universal Health Coverage (UHC). That is, all people must have access to healthcare when needed at an affordable price. While several indices were developed recently to assess UHC status, these indices appeared to be difficult for practitioners to apply without statistical knowledge. This paper presents a transparent and step-by-step practical calculation method of such an index using Excel spreadsheets, applied to some Asian and African countries. We also decompose the contribution of socioeconomic groups to UHC index values. We utilized the well known UHC illustration (three-dimensional box, showing population coverage, service coverage and financial protection) to calculate the UHC index. We also broke down the index into socioeconomic groups. For validation, correlation coefficients between our index and other UHC indices were calculated and the relationship of our index with out-of-pocket (OOP) payments was estimated. World Bank data from six Asian and 15 African countries on health-service coverage of people in five socioeconomic quintiles with financial protection were used to calculate our UHC index. Among the Asian countries, indices ranged between 26.0% (Nepal) and 58.7% (Kazakhstan), while in African countries indices ranged between 8.9% (Chad) and 55.3% (Namibia). Decomposition of the UHC index showed a higher contribution to the index by richer socioeconomic groups. The correlation coefficients between our estimated UHC index values and those of others ranged between 0.774 and 0.900. Our index reduced by 1.4% in response to a 1% increase in OOP payments. This spreadsheet approach for calculating the UHC index appeared to be useful, where the interrelation of UHC dimensions was easily observed. Decomposition of the index could be useful for policy-makers to identify the subpopulations and health services with need for further interventions towards UHC achievement.

Machine learning reveals country-specific drivers of global cancer outcomes.

BackgroundThe pandemic situation due to COVID-19 highlighted the importance of global health security preparedness and response. Since the revision of the International Health Regulations (IHR) in 2005, Joint External Evaluation (JEE) and States Parties Self-Assessment Annual Reporting (SPAR) have been adopted to track the IHR implementation stage in each country. While national IHR core capacities support the concept of Universal Health Coverage (UHC), there have been limited studies verifying the relationship between the two concepts. This study aimed to investigate empirically the association between IHR core capacity scores and the UHC service coverage index.MethodJEE score, SPAR score and UHC service coverage index data from 96 countries were collected and analyzed using an ecological study design. The independent variable was IHR core capacity scores, measured by JEE 2016-2019 and SPAR 2019 from the World Health Organization (WHO) and the dependent variable, UHC service coverage index, was extracted from the 2019 UHC monitoring report. For examining the association between IHR core capacities and the UHC service coverage index, Spearman’s correlation analysis was used. The correlation between IHR core capacities and UHC index was demonstrated using a scatter plot between JEE score and UHC service coverage index, and the SPAR score and UHC service coverage index were also presented.ResultWhile the correlation value between JEE and SPAR was 0.92 (p < 0.001), the countries’ external evaluation scores were lower than their self-evaluation scores. Some areas such as available human resources and points of entry were mismatched between JEE and SPAR. JEE was associated with the UHC score (r = 0.85, p < 0.001) and SPAR was also associated with the UHC service coverage index (r = 0.81, p < 0.001). The JEE and SPAR scores showed a significant positive correlation with the UHC service coverage index after adjusting for several confounding variables.ConclusionThe study result supports the premise that strengthening national health security capacities would in turn contribute to the achievement of UHC. With the help of the empirical result, it would further guide each country for better implementation of IHR.

Background:Global disparities in healthcare resources impact diagnosis, treatment, and ongoing supportive care for cancer. As these resource levels can be considered modifiable factors of health inequality on a global scale, we aimed to explore their association with the global cancer burden and quantify the extent of these inequalities.Methods:Healthcare resource capacity was measured using the universal health coverage (UHC) index and current health expenditure as a percentage of gross domestic product [CHE/GDP (%)]. Cancer data were sourced from the GLOBOCAN database. Variables such as age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and a proxy for 5-year survival (1 − mortality to incidence ratio) were calculated. Absolute and relative inequalities in cancer burden were assessed using the slope index of inequality and concentration index. The association between healthcare resources and cancer burden was further explored by negative binomial regression. Counterfactual simulations quantify inequalities based on healthcare resource levels.Results:Marked absolute and relative inequalities were found in the burden of most cancer types related to the UHC index and the CHE/GDP (%) gradient. Both the absolute and relative burdens of cancer were concentrated in areas with high UHC index and CHE/GDP (%) levels. A significant positive association was found between the ASIR [incidence rate ratio (IRR): 1.77, 95% confidence interval (CI): 1.57–2.00] and survival (IRR: 1.60, 95% CI: 1.48–1.73) with the UHC index. A weaker positive association was found for CHE/GDP (%) with ASIR (IRR: 1.37, 95% CI: 1.20–1.56) and survival (IRR: 1.23, 95% CI: 1.13–1.35). No significant association was found between ASMR and either the UHC index or CHE/GDP (%). An estimated 21% of cancer deaths were associated with the potential to be prevented, with survival rates matching the most advanced nations in each region, and over 31% of cancer deaths were associated with the potential to be prevented, with survival rates matching the most advanced nations worldwide.Conclusions:Substantial inequalities in the cancer burden related to healthcare resources are apparent worldwide. Allocating healthcare resources at optimal levels can improve survival and reduce cancer-related deaths. These findings emphasize the need for targeted interventions and policies to address inequalities in healthcare resource allocation and ensure equitable access to cancer treatment.

Monitoring equity in universal health coverage with essential services for neglected tropical diseases: an analysis of data reported for five diseases in 123 countries over 9 years.

Introduction: While the effects of the US government’s sudden pause of foreign aid on the global HIV response have been well documented, little is known about the likely impact on universal health coverage (UHC) in recipient countries. This study assesses the association between PEPFAR funding and the universal health service coverage index. Methods: Using data on PEPFAR investments in 24 countries between 2004 and 2020, the study applied fixed and time effects panel data regression on the main UHC index and its sub-indices for non-communicable diseases (NCDs), reproductive, maternal, newborn and child healthcare (RMNCH); and service capacity and access. Gross domestic product (GDP) per capita, government health expenditure as a percentage of current health expenditure (CHE), private health expenditure as a percentage of CHE, and government efficiency were included as control variables. Results: The UHC index tripled in some countries over the study period, coinciding with PEPFAR investments, which prioritised HIV treatment. However, GDP per capita doubled, government health spending increased marginally, while out-of-pocket payments declined in the same time period. The study found positive associations between PEPFAR funding and the UHC index (0.11, p < 0.01), RMNCH (0.036, p < 0.1), and NCDs (0.038, p < 0.05). GDP per capita, government health expenditure, and government efficiency were also positively associated with UHC indexes. Time effects were established for the main UHC index and the NCDs sub-index. Conclusions: We conclude that PEPFAR funding for HIV was instrumental in driving UHC in recipient countries. The abruptness of the funding cuts was destabilising to HIV programs across the globe and threatened to upend hard-won gains in ending AIDS as a public health threat. Without renewed PEPFAR support, continued global solidarity, and greater domestic financing, health systems risk setbacks threatening the health of current and future generations, as well as global health security. Safeguarding current progress requires PEPFAR funding restoration, host governments’ commitment to growth-oriented policies, efficient use of available resources, integration of HIV into UHC, stronger South-South cooperation to reduce aid reliance, and donor alignment with national health goals.

Global health security (GHS) and universal health coverage (UHC) are key global health agendas which aspire for a healthier and safer world. However, there are tensions between GHS and UHC strategy and implementation. The objective of this study was to assess the relationship between GHS and UHC using two recent quantitative indices. We conducted a macro-analysis to determine the presence of relationship between GHS index (GHSI) and UHC index (UHCI). We calculated Pearson's correlation coefficient and the coefficient of determination. Analyses were performed using IBM SPSS Statistics Version 25 with a 95% level of confidence. There is a moderate and significant relationship between GHSI and UHCI (r = 0.662, p<0.001) and individual indices of UHCI (maternal and child health and infectious diseases: r = 0.623 (p<0.001) and 0.594 (p<0.001), respectively). However, there is no relationship between GHSI and the non-communicable diseases (NCDs) index (r = 0.063, p>0.05). The risk of GHS threats a significant and negative correlation with the capacity for GHS (r = -0.604, p<0.001) and the capacity for UHC (r = -0.792, p<0.001). The aspiration for GHS will not be realized without UHC; hence, the tension between these two global health agendas should be transformed into a synergistic solution. We argue that strengthening the health systems, in tandem with the principles of primary health care, and implementing a "One Health" approach will progressively enable countries to achieve both UHC and GHS towards a healthier and safer world that everyone aspires to live in.