Understanding efficiency and the effect of pay-for-performance across health facilities in Tanzania

Abstract

BackgroundEnsuring efficient use and allocation of limited resources is crucial to achieving the UHC goal. Performance-based financing that provides financial incentives for health providers reaching predefined targets would be expected to enhance technical efficiency across facilities by promoting an output-oriented payment system. However, there is no study which has systematically assessed efficiency scores across facilities before and after the introduction of pay-for-performance (P4P). This paper seeks to fill this knowledge gap.MethodsWe used data of P4P evaluation related to healthcare inputs (staff, equipment, medicines) and outputs (outpatient consultations and institutional deliveries) from 75 health facilities implementing P4P in Pwani region, and 75 from comparison districts in Tanzania. We measured technical efficiency using Data Envelopment Analysis and obtained efficiency scores across facilities before and after P4P scheme. We analysed which factors influence technical efficiency by regressing the efficiency scores over a number of contextual factors. We also tested the impact of P4P on efficiency through a difference-in-differences regression analysis.ResultsThe overall technical efficiency scores ranged between 0.40 and 0.65 for hospitals and health centres, and around 0.20 for dispensaries. Only 21% of hospitals and health centres were efficient when outpatient consultations and deliveries were considered as output, and <3% out of all facilities were efficient when outpatient consultations only were considered as outputs. Higher efficiency scores were significantly associated with the level of care (hospital and health centre) and wealthier catchment populations. Despite no evidence of P4P effect on efficiency on average, P4P might have improved efficiency marginally among public facilities.ConclusionMost facilities were not operating at their full capacity indicating potential for improving resource usage. A better understanding of the production process at the facility level and of how different healthcare financing reforms affects efficiency is needed. Effective reforms should improve inputs, outputs but also efficiency.

Who is paid in pay-for-performance? Inequalities in the distribution of financial bonuses amongst health centres in Zimbabwe

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“…Distributional effects are relevant in P4P, as incentivized agents (healthcare providers or facilities) with different characteristics likely differ in their ability to provide health services and therefore also differ in their ability to respond to predetermined performance targets. It is easy to imagine how facilities lacking resources and staff might find it more difficult to meet P4P targets, especially in P4P programs without readiness investments prior to implementation or no built-in facility improvement incentives ( Binyaruka and Anselmi (2020) . Moreover, incentivized outcomes in P4P schemes are often not fully under providers’ control and depend on local area and population characteristics.…”

Patient-Provider Interaction in Primary Healthcare Facilities in Tanzania: Findings from Star Rating Assessment

“…In this study, we did not evaluate the workload of healthcare providers as a potential factor influencing the patientprovider interaction. However, it is worth noting that in Tanzania, many PHC facilities have relatively less demanding workloads compared to referral facilities as measured by productivity levels and efficiency in health facilities (Maestad & Mwisongo, 2013;Benjamin W. Mkapa HIV/AIDS Foundation, 2015;Nnko et al, 2019;Binyaruka & Anselmi, 2020).…”

Understanding the maternal and child health system response to payment for performance in Tanzania using a causal loop diagram approach

“…Our study adds to the existing evidence base examining the effects of the P4P pilot in Tanzania on the health system and population ( Mayumana et al, 2017 ; Anselmi et al, 2017 ; Binyaruka et al, 2015 , 2018a ; Binyaruka and Borghi, 2017 ; Olafsdottir et al, 2014 ; Binyaruka and Anselmi, 2020 ), by identifying those variables which are really catalytic both in terms of achieving performance targets (e.g. drugs), and limiting their achievement (staffing).…”

“…Tanzania was selected as a case study as it had implemented a P4P programme which was known to be effective in improving service uptake ( Binyaruka et al, 2015 ), and resulted in health system improvements (provider kindness and greater drug availability) which mediated programme effects ( Anselmi et al, 2017 ). There was also a wealth of evaluation data on the health system effects of the programme ( Mayumana et al, 2017 ; Binyaruka et al, 2015 , 2018a ; Binyaruka and Borghi, 2017 ; Olafsdottir et al, 2014 ; Borghi et al, 2013 ; Binyaruka and Anselmi, 2020 ) to inform the CLD.…”