Many low-and middle-income countries have expanded maternal and child health services, yet district-level efficiency and equity remain concerns, particularly in settings that rely on international assistance for health. Senegal uses the national DHIS2 platform to monitor maternal and child health indicators, but little is known about how capacity-building programs affect district efficiency after accounting for contextual need and remaining inefficiency gaps. Data from 2019 and 2023 were analyzed for 27 health districts in central Senegal. Inputs were numbers of doctors, nurses, midwives, and beds; outputs were maternal and child health services, including antenatal and postnatal contacts, skilled births, and vaccinations. Technical efficiency was estimated using input-oriented, constant-returns-to-scale data envelopment analysis. Efficiency was related to environmental factors (women of reproductive age, health facilities, community health workers, and distance to the nearest facility), and significant factors were incorporated to obtain environment-adjusted scores. Changes in efficiency and gaps were compared between intervention and comparison districts. In the unadjusted analysis, mean TE was 0.798 in 2019 and 0.796 in 2023. Intervention districts demonstrated higher TE than comparison districts, increasing from 0.840 to 0.916, whereas comparison districts declined slightly from 0.790 to 0.776. Fertility was significantly associated with TE in 2019 (Estimate = 1.121, p = 0.028) and 2023 (Estimate = 9.901, p = 0.009), while other environmental variables were not significant. After fertility adjustment, mean TE reached 1.000 in intervention districts and 0.901 in comparison districts in 2023. Gap reduction rates averaged 0.995 in intervention districts and −0.364 in comparison districts, indicating substantial closure of inefficiency gaps in intervention districts. The maternal and child health capacity‑building program in central Senegal appears to have substantially reduced residual inefficiency in already relatively efficient districts when environment‑adjusted efficiency scores and a normalized gap reduction metric were used. Incorporating demand‑related environmental factors and gap‑based change measures into routine efficiency monitoring can support more informative and equity‑sensitive evaluations of health programs in resource‑constrained settings.
Kang et al. (Wed,) studied this question.