PurposeThis 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.Design/methodology/approachThe study is based on a desk review and thematic analysis of 64 policy and academic literatures supplemented with 28 multi-stakeholder interviews.FindingsThe 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.Originality/valueRBF 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.
Although pay-for-performance (P4P) schemes have been implemented across low and middle-income countries (LMICs), little is known about their distributional consequences. A key concern is that, in case there is a Matthew Effect and financial bonuses are primarily captured by providers who are already better able to perform (say those in wealthier areas), P4P could exacerbate existing inequalities within the health system. We examine inequalities in the distribution of pay-outs in Zimbabwe’s national P4P scheme (2014–2016) using quantitative data on bonus payments and facility characteristics and findings from a thematic policy review and 28 semi-structured interviews with stakeholders at all system levels. We found that in Zimbabwe, facilities with better baseline access to guidelines, more staff, higher consultation volumes and wealthier and less remote target populations earned significantly higher P4P bonuses throughout the programme. For instance, facilities that were one standard-deviation above the mean in terms of access to guidelines, earned 90 USD more per quarter than those that were one-standard deviation below the mean. Differences in bonus pay-outs for facilities that were one standard-deviation above and below the mean in terms of number of staff and consultation volumes are even more pronounced at 348 USD and 445 USD per quarter. Similarly, facilities with villages in the poorest wealth quintile in their vicinity earned less than all others—and 752 USD less per quarter than those in the richest quintile. Qualitative data confirm these findings. Respondents identified facilities’ baseline structural quality, leadership, catchment population size and remoteness as affecting performance in the scheme. Unequal distribution of P4P pay-outs was identified as having negative consequences on staff retention, absenteeism and motivation. Based on our findings and previous work, we provide some guidance to policymakers on how to design more equitable P4P schemes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.