How personnel diversity and affective bonds affect performance-based financing: a moderator analysis of a difference-in-difference estimator.

To spur improvement in health-care service quality and quantity, performance-based financing (PBF) is an increasingly common policy tool, especially in low- and middle-income countries. This study examines how personnel diversity and affective bonds in primary care clinics affect their ability to improve care quality in PBF arrangements. Leveraging data from a large-scale matched PBF intervention in Tajikistan including 208 primary care clinics, we examined how measures of personnel diversity (position and tenure variety) and affective bonds (mutual support and group pride) were associated with changes in the level and variability of clinical knowledge (diagnostic accuracy of 878 clinical vignettes) and care processes (completion of checklist items in 2485 instances of direct observations). We interacted the explanatory variables with exposure to PBF in cluster-robust, linear regressions to assess how these explanatory variables moderated the PBF treatment's association with clinical knowledge and care process improvements. Providers and facilities with higher group pride exhibited higher care process improvement (greater checklist item completion and lower variability of items completed). Personnel diversity and mutual support showed little significant associations with the outcomes. Organizational features of clinics exposed to PBF may help explain variation in outcomes and warrant further research and intervention in practice to identify and test opportunities to leverage them. Group pride may strengthen clinics' ability to improve care quality in PBF arrangements. Improving health-care facilities' pride may be an affordable and effective way to enhance health-care organization adaptation.

Lives Versus Livelihoods: The Epidemiological, Social, And Economic Impact Of COVID-19 In Latin America And The Caribbean.

During the COVID-19 pandemic, Latin American and Caribbean countries implemented stringent public health and social measures that disrupted economic and social activities. This study used an integrated model to evaluate the epidemiological, economic, and social trade-offs in Argentina, Brazil, Jamaica, and Mexico throughout 2021. Argentina and Mexico displayed a higher gross domestic product (GDP) loss and lower deaths per million compared with Brazil. The magnitude of the trade-offs differed across countries. Reducing GDP loss at the margin by 1 percent would have increased daily deaths by 0.5 per million in Argentina but only 0.3 per million in Brazil. We observed an increase in poverty rates related to the stringency of public health and social measures but no significant income-loss differences by sex. Our results indicate that the economic impact of COVID-19 was uneven across countries as a result of different pandemic trajectories, public health and social measures, and vaccination uptake, as well as socioeconomic differences and fiscal responses. Policy makers need to be informed about the trade-offs to make strategic decisions to save lives and livelihoods.

Performance of predictive algorithms in estimating the risk of being a zero-dose child in India, Mali and Nigeria.

INTRODUCTION: Many children in low-income and middle-income countries fail to receive any routine vaccinations. There is little evidence on how to effectively and efficiently identify and target such 'zero-dose' (ZD) children. METHODS: We examined how well predictive algorithms can characterise a child's risk of being ZD based on predictor variables that are available in routine administrative data. We applied supervised learning algorithms with three increasingly rich sets of predictors and multiple years of data from India, Mali and Nigeria. We assessed performance based on specificity, sensitivity and the F1 Score and investigated feature importance. We also examined how performance decays when the model is trained on older data. For data from India in 2015, we further compared the inclusion and exclusion errors of the algorithmic approach with a simple geographical targeting approach based on district full-immunisation coverage. RESULTS: Cost-sensitive Ridge classification correctly classifies most ZD children as being at high risk in most country-years (high specificity). Performance did not meaningfully increase when predictors were added beyond an initial sparse set of seven variables. Region and measures of contact with the health system (antenatal care and birth in a facility) had the highest feature importance. Model performance decreased in the time between the data on which the model was trained and the data to which it was applied (test data). The exclusion error of the algorithmic approach was about 9.1% lower than the exclusion error of the geographical approach. Furthermore, the algorithmic approach was able to detect ZD children across 176 more areas as compared with the geographical rule, for the same number of children targeted. INTERPRETATION: Predictive algorithms applied to existing data can effectively identify ZD children and could be deployed at low cost to target interventions to reduce ZD prevalence and inequities in vaccination coverage.

The Quality of Primary Care in Cambodia: An Assessment of Knowledge and Effort of Public Sector Maternal and Child Care Providers.

Improving the quality of primary care is essential for achieving universal health coverage in low- and middle-income countries. This study examined the level and variation in primary care provider knowledge and effort in Cambodia, using cross-sectional data collected in 2014-2015 from public sector health centers in nine provinces. The data included clinical vignettes and direct observations of processes of antenatal care, postnatal care, and well-child visits and covered between 290-495 health centers and 370-847 individual providers for each service and type of data. The results indicate that provider knowledge and observed effort were generally low and varied across health centers and across individual providers. In addition, providers' effort scores were generally lower than their knowledge scores, indicating the presence of a "know-do gap." Although higher provider knowledge was correlated with higher levels of effort during patient encounters, knowledge only explained a limited fraction of the provider-level variation in effort. Due to low baseline performance and the know-do gap, improving provider adherence to clinical guidelines through training and practice standardization alone may have limited impact. Overall, the findings suggest that raising the low quality of care provided by Cambodia's public sector will require multidimensional interventions that involve training, strategies that increase provider motivation, and improved health center management. The authors reported there is no funding associated with the work presented in this article.

Role of User Benefit Awareness in Health Coverage Utilization among the Poor in Cambodia.

The objective of this study was to understand the steps to health coverage benefit utilization in Cambodia toward improving access to health care and financial risk protection for the poor. We particularly examine the role of user awareness in the pathway to care seeking and benefit utilization with respect to the Health Equity Funds (HEF). Using 2016 survey data that were nationally representative of households with children under two years of age, we used a series of logistic regression models to evaluate associations between respondents' awareness of benefits, public health care seeking behaviors, coverage benefit claims, and out-of-pocket expenditures. Beneficiaries were generally aware of their entitlements, although their awareness of specific benefits, such as transport reimbursement, was relatively lower. Awareness of free services at public health centers was associated with twice the odds of having ever visited a public provider for outpatient care, while awareness of free services at public hospitals was associated with higher odds of always seeking inpatient care in the public sector. Study findings point to the decision of where to seek care as the critical point in the pathway to HEF utilization. If the decision had already been made to go to a public provider, it was likely that HEF benefits were claimed. Interventions that prompt appropriate care seeking in the public sector may do the most to improve HEF utilization and subsequently improve access to care through sufficient financial risk protection.

The effects of performance-based financing on neonatal health outcomes in Burundi, Lesotho, Senegal, Zambia and Zimbabwe.

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 programmes directly on neonatal health outcomes in Africa, nor compared PBF programmes 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 caesarean 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 and among poor women PBF improved facility delivery, antenatal care utilization or antenatal care quality. There was no improvement on the health outcomes 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.

Health equity funds as the pathway to universal coverage in Cambodia: care seeking and financial risk protection.

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.

The role of health system context in the design and implementation of performance-based financing: evidence from Cote d'Ivoire.

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.

The Association Between Hospital Occupancy and Mortality Among Medicare Patients.

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. The objective of this study 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: The researchers conducted a retrospective, observational study using secondary data from the California Office of Statewide Health Planning and Development, including nonfederal, acute care facilities from 1998 to 2012. Using measures of relative hospital occupancy, the researchers ran logistic regressions to assess the relationship between increasing hospital occupancy and inpatient mortality and 30-day out-of-hospital mortality among Medicare patients age 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. CONCLUSION: This study 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.

Using supervised learning to select audit targets in performance-based financing in health: An example from Zambia.

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.

Measuring and paying for quality of care in performance-based financing: Experience from seven low and middle-income countries (Democratic Republic of Congo, Kyrgyzstan, Malawi, Mozambique, Nigeria, Senegal and Zambia).

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.

Asylum-seekers in Germany differ from regularly insured in their morbidity, utilizations and costs of care.

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.

Plan responses to diagnosis-based payment: Evidence from Germany's morbidity-based risk adjustment.

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.

How do performance-based financing programmes measure quality of care? A descriptive analysis of 68 quality checklists from 28 low- and middle-income countries.

This paper seeks to systematically describe the length and content of quality checklists used in performance-based financing programmes, their similarities and differences, and how checklists have evolved over time. We compiled a list of supply-side, health facility-based performance-based financing (PBF) programmes 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. 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. We conclude that 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.

Quality of Care in Performance-Based Financing: How It Is Incorporated in 32 Programs Across 28 Countries.

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.

Knowledge as a Predictor of Insurance Coverage Under the Affordable Care Act.

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.

Health system changes under pay-for-performance: the effects of Rwanda's national programme on facility inputs.

Pay-for-performance (P4P) programmes have been introduced in numerous developing countries with the goal of increasing the provision and quality of health services through financial incentives. Despite the popularity of P4P, there is limited evidence on how providers achieve performance gains and how P4P affects health system quality by changing structural inputs. We explore these two questions in the context of Rwanda's 2006 national P4P programme by examining the programme's impact on structural quality measures drawn from international and national guidelines. Given the programme's previously documented success at increasing institutional delivery rates, we focus on a set of delivery-specific and more general structural inputs. Using the programme's quasi-randomized roll-out, we apply multivariate regression analysis to short-run facility data from the 2007 Service Provision Assessment. We find positive programme effects on the presence of maternity-related staff, the presence of covered waiting areas and a management indicator and a negative programme effect on delivery statistics monitoring. We find no effects on a set of other delivery-specific physical resources, delivery-specific human resources, delivery-specific operations, general physical resources and general human resources. Using mediation analysis, we find that the positive input differences explain a small and insignificant fraction of P4P's impact on institutional delivery rates. The results suggest that P4P increases provider availability and facility operations but is only weakly linked with short-run structural health system improvements overall.

India's Largest Hospital Insurance Program Faces Challenges In Using Claims Data To Measure Quality.

The routine data generated by India's universal coverage programs offer an important opportunity to evaluate and track the quality of health care systematically and on a large scale. We examined the potential and challenges of measuring the quality of hospital care through claims data from India's hospital insurance program for the poor, Rashtriya Swasthya Bima Yojana (RSBY). Using data from one district in India, we illustrate how these data already provide useful insights and show that simple efforts to enhance data quality and an effort to expand the data captured could facilitate RSBY's ability to track quality of care. The data collected by RSBY has significant potential to characterize and uncover the provision of low-quality care and help inform much-needed efforts to raise the quality of hospital care.