Brazil’s more doctors programme and infant health outcomes: a longitudinal analysis

Abstract

Background: Providing sufficient numbers of human resources for health is essential for effective and accessible health services. Between 2013 and 2018, the Brazilian Ministry of Health implemented the Programa Mais Médicos (PMM) (More Doctors Programme) to increase the supply of primary care doctors in underserved areas of the country. This study investigated the association between PMM and infant health outcomes and assessed if heterogeneity in the impact of PMM varied by municipal socio-economic factors and health indicators. Methods: An ecological longitudinal (panel) study design was employed to analyse data from 5565 Brazilian municipalities over a 12-year period between 2007 and 2018. A differences-in-differences approach was implemented using longitudinal fixed effect regression models to compare infant health outcomes in municipalities receiving a PMM doctor with those that did not receive a PMM doctor. The impact of PMM was assessed on aggregate and in municipality subgroups. Results: On aggregate, the PMM was not significantly associated with changes in infant or neonatal mortality, but the PMM was associated with reductions in infant mortality rate (IMR) (of − 0.21; 95% CI: − 0.38, − 0.03) in municipalities with highest IMR prior to the programme’s implementation (where (IMR) > 25.2 infant deaths per 1000 live births). The PMM was also associated with an increase in the proportion of expectant mothers receiving seven or more prenatal care visits but only in municipalities with a lower IMR at baseline and high density of non-PMM doctors and community health workers before the PMM. Conclusions: The PMM was associated with reduced infant mortality in municipalities with the highest infant mortality rate prior to the programme. This suggests effectiveness of the PMM was limited only to the areas of greatest need. New programmes to improve the equitable provision of human resources for health should employ comprehensive targeting approaches balancing health needs and socio-economic factors to maximize effectiveness.