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The use of pay for performance (P4P) as an instrument to incentivise quality improvements in health care is at a crossroads in high-income countries but has remained a commonly used tool in low- and middle-income countries. The authors aimed to take stock of the evidence on effectiveness and design from across income settings to reveal insights for the future design of performance payment across income contexts.

The authors identified Cochrane literature reviews of the use of P4P in health care in any income setting, tracked the development in the quantity and quality of evidence over time, and compared the incentive design features used across high-income countries compared to low- and middle-income countries.

The quantity and quality of the evidence base have grown over time but can still be improved. Scheme design varies across income settings, and although some design choices may reflect differences in context, the authors find that incentive designers in both income settings can learn from practices used in the other setting.

The research and literature on P4P in high-, low- and middle-income countries largely operate in silos. By taking stock of the evidence on P4P from across income settings, the authors are able to draw out key insights between these settings, which remain underexplored in the literature.

Objective – Measurement of the incidence of health financing contributions across socio-economic groups has proven valuable in informing health care financing reforms. However, there is little evidence as to how to carry out financing incidence analysis (FIA) in lower income settings. We outline some of the challenges faced when carrying out a FIA in Ghana, Tanzania and South Africa and illustrate how innovative techniques were used to overcome data weaknesses in these settings.

Methodology – FIA was carried out for tax, insurance and out-of-pocket (OOP) payments. The primary data sources were Living Standards Measurement Surveys (LSMS) and household surveys conducted in each of the countries; tax authorities and insurance funds also provided information. Consumption expenditure and a composite index of socio-economic status (SES) were used to assess financing equity. Where possible conventional methods of FIA were applied. Numerous challenges were documented and solution strategies devised.

Results – LSMS are likely to underestimate financial contributions to health care by individuals. For tax incidence analysis, reported income tax payments from secondary sources were severely under-reported. Income tax payers and shareholders could not be reliably identified. The use of income or consumption expenditure to estimate income tax contributions was found to be a more reliable method of estimating income tax incidence. Assumptions regarding corporate tax incidence had a huge effect on the progressivity of corporate tax and on overall tax progressivity. LSMS consumption categories did not always coincide with tax categories for goods subject to excise tax (e.g. wine and spirits were combined, despite differing tax rates). Tobacco companies, alcohol distributors and advertising agencies were used to provide more detailed information on consumption patterns for goods subject to excise tax by income category. There was little guidance on how to allocate fuel levies associated with ‘public transport’ use. Hence, calculations of fuel tax on public transport were based on individual expenditure on public transport, the average cost per kilometre and average rates of fuel consumption for each form of transport. For insurance contributions, employees will not report on employer contributions unless specifically requested to and are frequently unsure of their contributions. Therefore, we collected information on total health insurance contributions from individual schemes and regulatory authorities. OOP payments are likely to be under-reported due to long recall periods; linking OOP expenditure and illness incidence questions – omitting preventive care; and focusing on the last service used when people may have used multiple services during an illness episode. To derive more robust estimates of financing incidence, we collected additional primary data on OOP expenditures together with insurance enrolment rates and associated payments. To link primary data to the LSMS, a composite index of SES was used in Ghana and Tanzania and non-durable expenditure was used in South Africa.

Policy implications – We show how data constraints can be overcome for FIA in lower income countries and provide recommendations for future studies.

This study examines key adaptations that occurred in the Zimbabwean Results-Based Financing (RBF) programme between 2010 and 2017, locating the endogenous and exogenous factors that required adaptive response and the processes from which changes were made.

The study is based on a desk review and thematic analysis of 64 policy and academic literatures supplemented with 28 multi-stakeholder interviews.

The programme experienced substantive adaption between 2010 and 2017, demonstrating a significant level of responsiveness towards increasing efficiency as well as to respond to unforeseen factors that undermined RBF mechanisms. The programme was adaptive due to its phased design, which allowed revision competencies and responsive adaptation, which provide useful insights for other low-and-middle income countries (LMICs) settings where graduated scale-up might better meet contextualised needs. However, exogenous factors were often not systematically examined or reported in RBF evaluations, demonstrating that adaptation could have been better anticipated, planned, reported and communicated, especially if RBF is to be a more effective health system reform tool.

RBF is an increasingly popular health system reform tool in LMICs. However, there are questions about how exogenous factors affect RBF performance and acknowledgement that unforeseen endogenous programme design and implementation factors also greatly affect the performance of RBF. As a result, a better understanding of how RBF operates and adapts to programme level (endogenous) and exogenous (external) factors in LMICs is necessary.