The effects of decentralized financing and funding levels on the breadth of services and structural quality to provide those services in primary health facilities in Nigeria

Abstract

Background: To improve service delivery of Nigeria's primary health care (PHC) system, the government tested two approaches for facility-level financing: performance-based financing (PBF) and decentralized facility financing (DFF). Facilities also had increased autonomy, supervision, and community oversight. We examine how the intervention approach and funding level affected breadth of services and structural quality.

Methods: We use health facility surveys previously collected in 2014 and 2017, covering three years of implementation, in which districts were randomly assigned PBF or DFF and compared to matched districts in control states. We use log-linear regressions and non-parametric statistics to estimate the effect size of the financing approach and level of funding per capita.

Results: Service availability was highest in PBF facilities, while DFF also outperformed control on most measures. Results showed that structural readiness and service offerings both increased with more funding, especially under DFF. DFF and PBF facilities were better equipped to provide services that they claimed to offer, which was not the case for controls. Overall, PBF outperformed DFF, partially explained by funding levels. The rate of offering complimentary services followed a pattern of easiest-to-hardest to deliver.

Conclusion: PBF and DFF both improved the breadth and structural quality of services, although DFF performance was more sensitive to funding levels. Improvements were observed at relatively low levels of funding, but larger investments were associated with better performance. Most DFF facilities exceeded the performance of higher-funded controls, implying that funding was more valuable in the context of autonomy, increased supervision, and community oversight.

Keywords: Facility financing; Nigeria; PHC; Services; Structural quality.

Fig. 1

Association between revenues and service offerings. Facilities reported 2016 total revenues (from all sources) and the services that they offer, which are summarized and shown. Each point indicates the values for an individual facility. Revenue per capita was calculated as total reported revenues divided by the number of individuals reported to be in the facility’s catchment population. Lines shown are smoothed averages. DFF = direct facility financing. PBF = performance-based financing. 100 Naira ~ $ 0.27 USD

Fig. 2

Percentage of facilities offering services, by study arm and level of revenues. Services are listed from lowest to highest complexity (left to right), based on required provider skill level, supplies, and equipment. Revenue per capita was calculated from reported total facility revenues in 2016, divided by total catchment population for the facility. DFF = direct facility financing. PBF = performance-based financing. 100 Naira ~ $ 0.27 USD

Fig. 3

Results from linear regressions to predict structural quality. Each row represents a separate regression that was run, one for each outcome. The significant predictors are shown and their coefficients colored for interpretation, and the resulting R squared is also indicated. Left: Coefficient estimates are only shown for independent variables with a p-value < 0.05 (blank cells thus indicate non-significance). Text labels and shading indicate the value of the coefficient estimate. Regressions were normalized so that a score of 1.0 is a perfect score, as described in Table 2. “Study Arm * Offered” indicates the interaction term between these two independent variables. Right: Adjusted R-squared for the corresponding regressions. STI = sexually transmitted infection. FP = family planning. IUD = intrauterine device. TB = tuberculosis. DMPA = injectable contraceptive. HIV = human immunodeficiency virus