Abstract (edited by EPW): An array of bottlenecks has ensured that the numerous health insurance schemes introduced over the years have failed to make any significant dent on the health sector. This article tries to assess these problems by using the “insurance cascade,” a framework that traces the steps from enrolling eligible households to ultimately delivering their benefits. The existing evidence suggests substantial bottlenecks across all cascade steps, with especially large gaps in beneficiaries’ awareness of how to enrol in schemes, what the schemes covers, and how to access scheme benefits.
Maternal and newborn care has been a primary focus of performance-based financing (PBF) projects, which have been piloted or implemented in 21 countries in Sub-Saharan Africa since 2007. Several evaluations of PBF have demonstrated improvements to facility delivery or quality of care. However, no studies have measured the impact of PBF programs directly on neonatal health outcomes in Africa, nor compared PBF programs against another. We assess the impact of PBF on early neonatal health outcomes and associated health care utilization and quality in Burundi, Lesotho, Senegal, Zambia and Zimbabwe. We pooled Demographic and Health Surveys and Multiple Indicator Cluster Surveys and apply difference-in-differences analysis to estimate the effect of PBF projects supported by the World Bank on early neonatal mortality and low birthweight. We also assessed the effect of PBF on intermediate outputs that are frequently explicitly incentivized in PBF projects, including facility delivery and antenatal care utilization and quality, and cesarean section. Finally, we examined the impact among births to poor or high-risk women. We found no statistically significant impact of PBF on neonatal health outcomes, health care utilization or quality in a pooled sample. PBF was also not associated with better health outcomes in each country individually, though in some countries PBF improved facility delivery, antenatal care utilization, or antenatal care quality. There was also no improvement on any outcome among poor or high-risk women in the five countries. PBF had no impact on early neonatal health outcomes in the five African countries studied and had limited and variable effects on the utilization and quality of neonatal health care. These findings suggest that there is a need for both a deeper assessment of PBF and for other strategies to make meaningful improvements to neonatal health outcomes.
Performance-based financing (PBF) programs have been introduced in numerous developing countries to increase the provision and quality of health services through financial incentives. Despite growing evidence about short-term impacts of PBF, less is known about medium-run impacts and scale-up effects, and about how PBF compares to other financing approaches. In this paper, we extend the initial evaluation of Rwanda’s PBF program to identify medium-run and scale-up effects of incentives and unconditional financing relative to a new “business as usual” counterfactual. We use data from the Demographic and Health Surveys from Rwanda and several Sub-Saharan African countries from 2001 to 2010, using two control group strategies: all available control regions, and a subset of regions that are similar to Rwanda based on pre-intervention trends in covariates and outcomes. We then use difference-in-differences regressions to measure the Rwandan program’s impacts on four indicators: institutional deliveries, antenatal tetanus prophylaxis, completion of any antenatal visits, and completion of four antenatal visits. The results are similar using the various control groups and in additional robustness checks. In the short-run and relative to no intervention, both performance-based and unconditional financing raised institutional delivery rates and completion of four antenatal visits. In the medium-run, relative to no intervention and in addition to the initial short-run impacts, performance-based incentives resulted in further improvements for institutional deliveries. Program scale-up was effective, with few differences between intervention arms after all areas received performance-based incentives. There were few effects on antenatal tetanus prophylaxis or on completion of any antenatal visits. Together, the results suggest that PBF can have persistent effects for some indicators, but unconditional financing can also be effective. Moreover, the analysis demonstrates how observational research methods and secondary data can generate new insights on completed trials.
Cambodia has developed the health equity fund (HEF) system to improve access to health services for the poor, and this strengthens the health system towards the universal health coverage goal. Given rising healthcare costs, Cambodia has introduced several innovations and accomplished considerable progress in improving access to health services and catastrophic health expenditures for the targeted population groups. Though this is improving in recent years, HEF households remain at the higher risk of catastrophic spending as measured by the higher share of HEF households with catastrophic health expenses being at 6.9% compared to the non-HEF households of 5.5% in 2017. Poverty targeting poses another challenge for the health system. Nevertheless, HEF appeared to be more significantly associated with decreased out-of-pocket expenditure per illness among those who sought care from public providers. Increasing population and cost coverages of the HEF and effectively attracting beneficiaries to the public sector will further enhance the financial protection and pave the pathway towards universal coverage. Our recommendations focus on leveraging the HEF experience for expanding coverage and increasing equitable access, as well as strengthening the quality of healthcare services.
Low quality of care is a significant problem for health systems in low-income and middle-income countries (LMICs). Policymakers are increasingly interested in using performance-based financing (PBF), a system-wide provider payment reform, conditioned on both quantity and quality of performance, to improve quality of care. The health system context influences both the design and the implementation of these programmes and thus their effectiveness. This study analyses how context has influenced the design and implementation of PBF in improving the quality of primary care in one particular setting, Cote d’Ivoire, a lower-middle income country with some of the poorest health outcomes in the world. Based on literature, an analytical framework was developed identifying five pathways through which financial incentives can influence the quality of primary care: earmarking, conditioning, provider behaviour, community involvement and management. Guided by this framework, semistructured interviews were conducted with policymakers and providers to diagnose the context and to assess the links between financing and quality of care at the primary care level. PBF in Cote d’Ivoire was found to have increased data availability and quality, facility-wide and disease-specific inputs, provider motivation and management practices in contracted facilities, but had limited success in improving process and outcome measures of quality, as well as community involvement and the provision of non-incentivised services. These limitations were attributable to a centralised health system structure constraining the decision space of health providers; financing and governance challenges across the health sector; and shortcomings with regard to the design of the PBF quality checklist and incentive structures in Cote d’Ivoire. In order to improve the quality of primary care, health sector reforms such as PBF should incorporate the organisational and service delivery context more broadly into their design and implementation, as is the case in other countries.
Background: Hospital crowding is a major challenge facing US health care systems, but few studies have evaluated the association between inpatient occupancy and patient mortality. Our objective was to determine how increasing hospital occupancy is associated with the likelihood of inpatient and 30-day out-of-hospital mortality using a novel measure of inpatient occupancy.
Methods: We conducted a retrospective, observational study using secondary data from the California Office of Statewide Health Planning and Development including non-federal, acute care facilities from 1998-2012. Using measures of relative hospital occupancy, we ran logistic regressions to assess the relationship between increasing hospital occupancy and inpatient mortality and 30-day out-of-hospital mortality among Medicare patients 65 years and older with myocardial infarction, heart failure or pneumonia.
Results: Higher admission day occupancy (odds ratio [OR] = 0.96, 95% confidence interval [CI]: 0.94–0.99) and higher discharge day occupancy (OR = 0.62, 95% CI: 0.60–0.64) were associated with decreased inpatient mortality. Thirty-day out-of-hospital mortality increased with higher discharge day occupancy (OR=1.28, 95% CI: 1.24-1.32), but was unrelated to admission day occupancy.
Conclusions: We found a counterintuitive relationship between admission and discharge day occupancy and inpatient mortality. Higher discharge day occupancy appears to displace deaths into the outpatient setting. Understanding why higher inpatient occupancy is associated with lower overall mortality merits investigation to inform best practices for inpatient care in busy hospitals.
Policy-makers, implementing organizations, and funders of global health programs aim to improve health care services and health outcomes through specific projects or systemic change. To mitigate the risk of corruption and its harmful effects on those initiatives, health programs often use multiple anti-corruption mechanisms, including codes of conduct, documentation and reporting requirements, and trainings. Unfortunately, the introduction of anti-corruption mechanisms tends to occur without an explicit consideration of how each mechanism will affect health services and health outcomes. This may overlook potentially more effective approaches. In addition, it may result in the introduction of too many controls (thereby stymying service delivery) and a focus on financial or procurement-related issues (at the expense of service delivery objectives). We argue that anti-corruption efforts in health programs can be more effective if they prioritize addressing issues according to their likelihood and level of harm to key program objectives. Recalibrating the anti-corruption formula in this way will require: (i) extending responsibility and ownership over anti-corruption from subject experts to public health and health system specialists, and (ii) enabling those specialists to apply the Fraud Risk Assessment methodology to develop tailored anti-corruption mechanisms. We fill a documented gap in guidance on how to develop anti-corruption mechanisms by walking through the seven analytical steps of the Fraud Risk Assessment methodology as applicable to health programs. We then outline best practices for any anti-corruption mechanism, including a focus on quality health delivery; the alignment of actors’ incentives around the advancement of health objectives; and being minimally corruptible by design.
Deforestation can increase malaria risk factors such as mosquito growth rates and biting rates in some settings. But deforestation affects more than mosquitoes—it is associated with socio-economic changes that affect malaria rates in humans. Most previous studies have found that deforestation is associated with increased malaria prevalence, suggesting that in some cases forest conservation might belong in a portfolio of anti-malarial interventions. However, previous peer-reviewed studies of deforestation and malaria were based on a small number of geographically aggregated observations, mostly from the Brazilian Amazon. Here we combine 14 years of high-resolution satellite data on forest loss with individual-level and nationally representative malaria tests for more than 60,000 rural children in 17 countries in Sub-Saharan Africa, where 88% of malaria cases occur. Adhering to methods that we pre-specified in a pre-analysis plan, we used multiple regression analysis to test ex-ante hypotheses derived from previous literature. Aggregated across countries, we did not find either deforestation or intermediate levels of forest cover to be associated with higher malaria prevalence. In nearly all (n = 78/84) country-year-specific regressions, we also did not find deforestation or intermediate levels of forest cover to be associated with higher malaria prevalence. However, we can not rule out associations at the local scale or beyond the geographic scope of our study region. We speculate that our findings may differ from those of previous studies because deforestation in Sub-Saharan Africa is largely driven by the steady expansion of smallholder agriculture for domestic use by long-time residents in stable socio-economic settings where malaria is already endemic and previous exposure is high, while in much of Latin America and Asia deforestation is driven by rapid clearing for market-driven agricultural exports by new frontier migrants without previous exposure. These differences across regions suggest useful hypotheses to test in future research.
Background:Crowding is a major challenge faced by EDs and is associated with poor outcomes.
Objectives:Determine the effect of high ED occupancy on disposition decisions, return ED visits, and hospitalizations.
Methods:We conducted a retrospective analysis of electronic health records of patients evaluated at an adult, urban, and academic ED over 20 months between the years 2012 and 2014. Using a logistic regression model predicting admission, we obtained estimates of the effect of high occupancy on admission disposition, adjusted for key covariates. We then stratified the analysis based on the presence or absence of high boarder patient counts.
Results:Disposition decisions during a high occupancy hour decreased the odds of admission (OR = 0.93, 95% CI: [0.89, 0.98]). Among those who were not admitted, high occupancy was not associated with increased odds of return in the combined (OR = 0.94, 95% CI: [0.87, 1.02]), with-boarders (OR = 0.96, 95% CI: [0.86, 1.09]), and no-boarders samples (OR = 0.93, 95% CI: [0.83, 1.04]). Among those who were not admitted and who did return within 14 days, disposition during a high occupancy hour on the initial ED visit was not associated with a significant increased odds of hospitalization in the combined (OR = 1.04, 95% CI: [0.87, 1.24]), the with-boarders (OR = 1.12, 95% CI: [0.87, 1.44]), and the no-boarders samples (OR = 0.98, 95% CI: [0.77, 1.24]).
Conclusion:ED crowding was associated with reduced likelihood of hospitalization without increased likelihood of 2-week return ED visit or hospitalization. Furthermore, high occupancy disposition hours with high boarder patient counts were associated with decreased likelihood of hospitalization.
Independent verification is a critical component of performance-based financing (PBF) in health care, in which facilities are offered incentives to increase the volume of specific services but the same incentives may lead them to over-report. We examine alternative strategies for targeted sampling of health clinics for independent verification. Specifically, we empirically compare several methods of random sampling and predictive modeling on data from a Zambian PBF pilot that contains reported and verified performance for quantity indicators of 140 clinics. Our results indicate that machine learning methods, particularly Random Forest, outperform other approaches and can increase the cost-effectiveness of verification activities.
Background: Performance-based financing (PBF) both measures and determines payments based on the quality of care delivered and is emerging as a potential tool to improve quality.
Methods: Comparative case study methodology was used to analyze common challenges and lessons learned in quality of care across seven PBF programs (Democratic Republic of Congo, Kyrgyzstan, Malawi, Mozambique, Nigeria, Senegal and Zambia). The eight case studies, across seven PBF programs, compared were commissioned by the USAID-funded Translating Research into Action (TRAction) project (n = 4), USAID’s Health Finance and Government project (n = 3), and from the Global Delivery Initiative (n = 1).
Results: The programs show similar design features to assess quality, but significant heterogeneity in their application. The seven programs included 18 unique quality checklists, containing over 1400 quality of care indicators, with an average per checklist of 116 indicators (ranging from 26-228). The quality checklists share a focus on structural components of quality (representing 80% of indicators on average, ranging from 38%-91%). Process indicators constituted an average of 20% across all checklists (ranging from 8.4% to 61.5%), with the majority measuring the correct application of care protocols for MCH services including child immunization. The sample included only one example of an outcome indicator from Kyrgyzstan. Performance data demonstrated a modest upward improvement over time in checklist scores across schemes, however, achievements plateaued at 60%-70%, with small or rural clinics reporting difficulty achieving payment thresholds due to limited resources and poor infrastructure. Payment allocations (distribution) and thresholds (for payments), data transparency, and approaches to measuring (verification) of quality differ across schemes.
Conclusions: Similarities exist in the processes that govern the design of PBF mechanisms, yet substantial heterogeneity in the experiences of implementing quality of care components in PBF programs are evident. This comparison suggests tailoring further the quality component of PBF programs to local and country contexts, and a need to better understand how quality is measured in practice. The growing operational experiences with PBF programs in different settings offer opportunities to learn from best practices, improve ongoing and future programs, and inform research to alleviate current challenges.
Governments across low-income and middle-income countries have pledged to achieve universal health coverage by 2030, which comes at a time where healthcare systems are subjected to multiple and persistent pressures, such as poor access to care services and insufficient medical supplies. While the political willingness to provide universal health coverage is a step into the right direction, the benefits of it will depend on the quality of healthcare services provided. In this analysis paper, we ask whether there are any lessons that could be learnt from the English National Health Service, a healthcare system that has been providing comprehensive and high-quality universal health coverage for over 70 years. The key areas identified relate to the development of a coherent strategy to improve quality, to boost public health as a measure to reduce disease burden, to adopt evidence-based priority setting methods that ensure efficient spending of financial resources, to introduce an independent way of inspecting and regulating providers, and to allow for task-shifting, specifically in regions where staff retention is low.
The evidence surrounding the cost-effectiveness of performance-based financing (PBF) is weak, and it is not clear how PBF compares with alternative interventions in terms of its value for money.
It is important to fill this evidence gap as countries transition from aid and face increasing budget constraints and competing priorities for the use of their domestic resources.
In conducting cost-effectiveness analyses of PBF, researchers should be mindful of the identification, measurement and valuation of costs and effects, provide justification for the scope of their studies, and specify appropriate comparators and decision rules.
We also recommend the use of a reference case to lay out the principles, preferred methodological choices and reporting standards, as well as a checklist.
In the wake of the European refugee crisis, Germany has received over a million new applications for asylum in the last two years. The health care system is struggling to provide asylum-seekers with access to essential medical services and facilitate their longer-term integration. In this article, we report on the morbidity, utilization and costs of care for a sample of asylum-seekers as compared to a matched group of regularly insured. Using administrative data, we found that asylum-seekers had more hospital and emergency department admissions, including more admissions that could be avoided through good outpatient care or prevention. Their average expenditures were 10 percent higher than for the regularly insured, mostly because of higher hospital expenditures, although there was substantial variation in expenditures by country of origin. Facilitating access to the health care system, especially outpatient and mental health care, could improve asylum-seekers health status and integration, possibly at lower costs.
Mehr als eine Million Menschen sind in den Jahren 2015 und 2016 vor Krieg, Gewalt und Verfolgung nach Deutschland geflohen. Ihre gesundheitliche Versorgung stellt eine große Herausforderung für das deutsche Gesundheitssystem dar, zumal eine gute physische und psychische Gesundheit Voraussetzung für eine gelingende Integration darstellt. Allerdings ist wenig über die gesundheitliche Situation, den Versorgungsbedarf und das Inanspruchnahmeverhalten von Asylsuchenden bekannt. In der Analyse werden die Abrechnungsdaten der BARMER der elektronischen Gesundheitskarte für Asylsuchende genutzt, um einen ersten Einblick auf Morbidität, Inanspruchnahme und Gesundheitsausgaben dieser Gruppe zu erhalten.
Introduction: Citizen report cards on health care providers have been identified as a potential means to increase citizen engagement, provider accountability and health systems performance. Research in high-income settings indicates that the wording, presentation and display of performance information are critical to achieve these goals. However, there are limited insights on developing effective report card designs for middle- and low-income settings. We conducted cognitive interviews to assess consumers’ understanding, interpretation of and preferences for displaying information for a health care report card in rural Tajikistan.
Materials and Methods: We recruited a convenience sample of 40 citizens (20 women and 20 men aged 18-45) from rural areas of two provinces of Tajikistan (Soghd and Khatlon oblasts). The interview protocol was adapted from the model of cognitive interviews used in social science research to improve survey questionnaires. We used multivariate regression to assess understanding and interpretation of the report card; chi2 tests to assess differences in preferences for displaying information; and tests of proportions to assess the preferred comparison group.
Results: Respondents understood the main idea of the report card and are not confused by the indicators or display. However, many respondents had difficulties making comparisons, and when asked to identify worst-performing services. Respondents preferred detailed rankings using school grades, comparisons of their local clinic with the regional or national average performance, and the use of color in the report card. We found some heterogeneity across the two provinces.
Conclusions: Overall, our findings are promising regarding the citizens’ comprehension of health care report cards in rural Tajikistan, while underscoring the challenges of effectively providing health care performance information to communities. Cognitive interviews and iterative testing can support an effective implementation of reporting initiatives.
Objective: To systematically describe the length and content of quality checklists used in performance-based financing programs, their similarities and differences, and how checklists have evolved over time.
Methods: We compiled a list of supply-side, health facility-based performance-based financing (PBF) programs in low- and lower middle-income countries based on a document review. We then solicited PBF manuals and quality checklists from implementers and donors of these PBF mechanisms. We entered each indicator from each quality checklist into a database verbatim in English, and translated into English from French where appropriate, and categorized each indicator according to the Donabedian framework and an author-derived categorization.
Findings: We extracted 8,490 quality indicators from 68 quality checklists across 32 PBF implementations in 28 countries. On average, checklists contained 125 indicators; within the same program, checklists tend to grow as they are updated. Using the Donabedian framework, 80% of indicators were structure-type, 19% process-type, and less than 1% outcome-type. The author-derived categorization showed that 57% of indicators relate to availability of resources, 24% to managing the facility and 17% assess knowledge and effort. There is a high degree of similarity in a narrow set of indicators used in checklists for common service types such as maternal, neonatal and child health.
Conclusion: Performance-based financing offers an appealing approach to targeting specific quality shortfalls and advancing toward the Sustainable Development Goals of high quality coverage. Currently most indicators focus on structural issues and resource availability. There is scope to rationalize and evolve the quality checklists of these programs to help achieve national and global goals to improve quality of care.
Many competitive health insurance markets adjust payments to participating health plans according to their enrollees’ risk – including based on diagnostic information. We investigate responses of German health plans to the introduction of morbidity-based risk adjustment in the Statutory Health Insurance in 2009, which triggers payments based on “validated” diagnoses by providers. Using the regulator’s data from office-based physicians, we estimate a difference-in-difference analysis of the change in the share and number of validated diagnoses for ICD codes that are inside or outside the risk adjustment but are otherwise similar. We find a differential increase in the share of validated diagnoses of 2.6 and 3.6 percentage points (3-4%) between 2008 and 2013. This increase appears to originate from both a shift from not-validated toward validated diagnoses and an increase in the number of such diagnoses. Overall, our results indicate that plans were successful in influencing physicians’ coding practices in a way that could lead to higher payments.
Objective: To describe how quality of care is incorporated into performance-based financing (PBF) programs, what quality indicators are being used, and how these indicators are measured and verified.
Methods: An exploratory scoping methodology was used to characterize the full range of quality components in 32 PBF programs, initiated between 2008 and 2015 in 28 low- and middle-income countries, totaling 68 quality tools and 8,490 quality indicators. The programs were identified through a review of the peer-reviewed and gray literature as well as through expert consultation with key donor representatives.
Findings: Most of the PBF programs were implemented in sub-Saharan Africa and most were funded primarily by the World Bank. On average, PBF quality tools contained 125 indicators predominately assessing maternal, newborn, and child health and facility management and infrastructure. Indicators were primarily measured via checklists (78%, or 6,656 of 8,490 indicators), which largely (over 90%) measured structural aspects of quality, such as equipment, beds, and infrastructure. Of the most common indicators across checklists, 74% measured structural aspects and 24% measured processes of clinical care. The quality portion of the payment formulas were in the form of bonuses (59%), penalties (27%), or both (hybrid) (14%). The median percentage (of a performance payment) allocated to health facilities was 60%, ranging from 10% to 100%, while the median percentage allocated to health care providers was 55%, ranging from 20% to 80%. Nearly all of the programs included in the analysis (91%, n=29) verified quality scores quarterly (every 3 months), typically by regional government teams.
Conclusion: PBF is a potentially appealing instrument to address shortfalls in quality of care by linking verified performance measurement with strategic incentives and could ultimately help meet policy priorities at the country and global levels, including the ambitious Sustainable Development Goals. The substantial variation and complexity in how PBF programs incorporate quality of care considerations suggests a need to further examine whether differences in design are associated with differential program impacts.
Background: The Affordable Care Act established policy mechanisms to increase health insurance coverage in the United States. While insurance coverage has increased, 10%-15% of the US population remains uninsured.
Objectives: To assess whether health insurance literacy and financial literacy predict being uninsured, covered by Medicaid, or covered by Marketplace insurance, holding demographic characteristics, attitudes toward risk, and political affiliation constant.
Research Design: Analysis of longitudinal data from fall 2013 and spring 2015 including financial and health insurance literacy and key covariates collected in 2013.
Subjects: A total of 2742 US residents ages 18-64, 525 uninsured in fall 2013, participating in the RAND American Life Panel, a nationally representative internet panel.
Measures: Self-reported health insurance status and type as of spring 2015.
Results: Among the uninsured in 2013, higher financial and health insurance literacy were associated with greater probability of being insured in 2015. For a typical uninsured individual in 2013, the probability of being insured in 2015 was 8.3 percentage points higher with high compared with low financial literacy, and 9.2 percentage points higher with high compared with low health insurance literacy. For the general population, those with high financial and health insurance literacy were more likely to obtain insurance through Medicaid or the Marketplaces compared with being uninsured. The magnitude of coefficients for these predictors was similar to that of commonly used demographic covariates.
Conclusions: A lack of understanding about health insurance concepts and financial illiteracy predict who remains uninsured. Outreach and consumer-education programs should consider these characteristics.