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Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC. Bill & Melinda Gates Foundation.

Background Universal health coverage (UHC) requires strong institutional capacity, equity-oriented policies, sustained political and financial commitment and public trust. However, public confidence in many health systems, including Mexico’s, has been chronically undermined. This study aims to document Mexico’s health coverage trajectory by offering a comprehensive, disaggregated and longitudinal assessment of insurance coverage from 2000 to 2023 – highlighting both achievements and setbacks in the context of UHC2030 goals. Methods This study used nationally representative data from Mexico’s National Household Income and Expenditure Survey (ENIGH) from 2000 to 2022, with projections for 2023. Households were classified into mutually exclusive health insurance categories on the basis of institutional affiliation. National and subnational trends in coverage were analysed, with attention to major reforms and disruptions. A distance-to-frontier metric quantified the gap between 2023 coverage and each state’s historical maximum, enabling assessment of progress toward UHC goals. Results Between 2000 and 2015, Mexico reduced the uninsured population from 55% to 6.2%, largely driven by Seguro Popular (SP) expansion benefiting Indigenous peoples, rural and low-income households in high-deprivation states. Following SP’s dismantling in 2019, the launch of Health Institute for Welfare (INSABI), and the COVID-19 pandemic, uninsured rates rose sharply to 29.1% by 2023. The greatest losses in coverage occurred in southern states and among marginalized groups, deepening territorial and social inequalities. The decline in mixed public coverage further reflects system fragmentation and eroding public trust. The distance-to-frontier analysis revealed that several states need to more than double their coverage to regain previous levels. Conclusions Mexico’s experience highlights that health coverage gains are reversible without strong institutional foundations, political consensus and social legitimacy. Rebuilding and sustaining UHC requires deliberate efforts to address structural inequalities, strengthen institutions and restore public trust. For other low- and middle-income countries, this case emphasizes the urgent need for institutions restructured to foster adaptive capacity alongside equity-focused strategies to achieve and sustain UHC.

The World Health Organization (WHO) states that examining medical financial systems is the most important process in evaluating universal health coverage (UHC). This study used the service coverage index (SCI) as a proxy of the progress toward UHC in eleven Asian countries. We employed a fixed-effects regression model to analyze panel data from 2015 to 2017, to explain the interrelationship between the SCI and major socioeconomic indicators. We also conducted a performance analysis (ratio of achieved SCI level to gross domestic product (GDP) or health expenditure displacement) to examine the balance between the degree of achievements related to UHC and a country’s economic level. The results showed that GDP and health expenditure were significantly positively correlated with the SCI (p < 0.01). The panel data analysis results showed that GDP per capita was a factor that greatly influenced the SCI as well as poverty (partial regression coefficient: 0.0017, 95% CI: 0.0013–0.0021). The results of the performance analysis showed that the Philippines had the highest scores (GDP: 1.84 SCI score/USD per capita, health expenditure: 1.04 SCI score/USD per capita) and South Korea the lowest. We conclude that socioeconomic factors, such as GDP, health expenditure, unemployment, poverty, and population influence the progress of UHC, regardless of system maturity or geographic characteristics.

Since independence, India has struggled to provide its people with universal health coverage. Whether defined in terms of financial protection or access to and effective use of health care, the majority of Indians remain irregularly and incompletely covered. Finally, and most recently, a new generation of Government-Sponsored Health Insurance Schemes (GSHISs) has emerged to provide the poor with financial coverage. Briefly, the main objective of these new GSHISs was to offer financial protection against catastrophic health shocks, defined in terms of an inpatient stay. Between 2007 and 2010, six major schemes have emerged, including one sponsored by the Government of India (GOI) and five state-sponsored schemes. This new wave of schemes provides fully subsidized coverage for a limited package of secondary or tertiary inpatient care, targeting below poverty populations. Similar to the private voluntary insurance products in the country, ambulatory services including drugs are not covered except as part of an episode of illness requiring an inpatient stay. The schemes have organized hospital networks consisting of public and private facilities, and most care funded by these schemes is provided in private hospitals. Ostensibly, the objective of any health insurance scheme is to increase access, utilization, and financial protection, and ultimately improve health status. Due to lack of evaluations and analyses of household data, the authors of this book do not examine the impact of health insurance in terms of these objectives. This book is not meant to highlight problems of the GSHISs, but rather to raise potential challenges and emerging issues that should be addressed to ensure the long-term viability of these schemes and secure their place within the health finance and delivery system.

\"This timely book describes the details of three real case studies of investigative journalism about health care. Stories include journalists exposing wrongdoing by drug companies, neglect of dying patients in by hospice home-care providers, and lead-poisoning from drinking water in Flint, Michigan. Readers will gain an understanding of the research process, the ethical standards journalists must follow, and the perseverance required to confirm a story and affect change\"-- Provided by publisher.

Background: The framework of measuring effective coverage is conceptually straightforward, yet translation into a single metric is quite intractable. An estimation of a metric linking need, access, utilization, and service quality is imperative for measuring the progress towards Universal Health Coverage. A coverage metric obtained from a household survey alone is not succinct as it only captures the service contact which cannot be considered as actual service delivery as it ignores the comprehensive assessment of provider–client interaction. The study was thus conducted to estimate a one-composite metric of effective coverage by linking varied datasets. Methods: The study was conducted in a rural, remote, and fragile setting in India. Tools encompassing a household survey, health facility assessment, and patient exit survey were administered to ascertain measures of contact coverage and quality. A gamut of techniques linking the varied surveys were employed such as (a) exact match linking and (b) ecological linking using GIS approaches via administrative boundaries, Euclidean buffers, travel time grid, and Kernel density estimates. A composite metric of effective coverage was estimated using linked datasets, adjusting for structural and process quality estimates. Further, the horizontal inequities in effective coverage were computed using Erreygers’ concentration index. The concordance between linkage approaches were examined using Wald tests and Lin’s concordance correlation. Results: A significantly steep decline in measurement estimates was found from crude coverage to effective coverage for an entire slew of linking approaches. The drop was more exacerbated for structural-quality-adjusted measures vis-à-vis process-quality-adjusted measures. Overall, the estimates for effective coverage and inequity-adjusted effective coverage were 36.4% and 33.3%, respectively. The composite metric of effective coverage was lowest for postnatal care (10.1%) and highest for immunization care (78.7%). A significant absolute deflection ranging from −2.1 to −5.5 for structural quality and −1.9 to −8.9 for process quality was exhibited between exact match linking and ecological linking. Conclusions: Poor quality of care was divulged as a major factor of decline in coverage. Policy recommendations such as bolstering the quality via the effective implementation of government flagship programs along with initiatives such as integrated incentive schemes to attract and retain workforce and community-based monitoring are suggested.