Trend and spatial clustering of medical education in Brazil: an ecological study of time series from 2010 to 2021.

CONTEXT: Studies that analyze the temporal trend and spatial clustering of medical education indicators are scarce, especially in developing countries such as Brazil. This analysis is essential to subsidize more equitable policies for the medical workforce in the states and regions of Brazil. Thus, this study aimed to analyze the temporal trend and identify spatial clusters of medical education indicators in Brazil disaggregated by public and private education, states, and regions. METHODS: A time-series ecological study was conducted using data from the Higher Education Census of the Ministry of Education from 2010 to 2021. The study analyzed vacancy density indicators of active and former students/100,000 population, disaggregated by public and private education, 27 states, and 5 regions in Brazil. Prais-Winsten regression was used for trend analyses of indicators. Hot Spot Analysis (Getis-Ord Gi*) was used to identify spatial clusters of indicators. RESULTS: The number of medical schools increased by 102.2% between 2010 and 2021. A total of 366 medical schools offered 54,870 vacancies at the end of 2021. Vacancy density and active and former students increased significantly in the period, but this increase was greater in private institutions. Most states and regions showed an increasing trend in the indicators, with higher increase percentages in private than in public schools. Hot spot spaces changed over time, concentrated in the southeast, center-west, and north at the end of 2021. Medical education remains uneven in Brazil, with a low provision in regions with low socioeconomic development, academic structure, and health services, represented by regions in the north and northeast. CONCLUSIONS: There is a growing trend in medical education indicators in Brazil, especially in the private sector. Spatial clusters were found predominantly in the southeast, center-west, and north. These results indicate the need for more equitable medical education planning between the regions.

Overview on and Contextual Determinants of Medical Residencies in North Brazil.

The aim of this study was to analyze the scenario of medical residency programs (MRPs) in the north region of Brazil as well as the contextual determinants (socioeconomic, structural, and epidemiological) influencing the number of MRPs in this region. An ecological study was conducted using MRPs data from 2022. This study used multiple data sources. MRP indicators were described based on the Brazilian state and specialty. The dependent variable was the number of MRPs. The independent variables included sociodemographic, structural, and epidemiological factors. Poisson regression was performed to analyze the association between contextual variables and the number of MRPs. The results showed that only 3.6% of the municipalities had authorized MRPs. The idleness rate in the region was 46.0%, with family and community medicine as the specialties with the greatest idleness. The total density of authorized vacancies in the MRPs was 14.0 vacancies per 100,000 inhabitants. The models showed that with each increase of one unit of the vulnerability index (Socioeconomic Index in the Geographic Context for Health Studies-GeoSES), the number of MRPs increased, ranging from 8122 (p value < 0.001) to 11,138 (p value < 0.001). With each increase in undergraduate degrees in medicine, the number of MRPs increased by 0.945 (p value < 0.001). With each increase of 1 physician per 1000 population, the number of MRPs increased from 0.537 (p value < 0.001) to 0.845 (p value < 0.001). With each increase of one unit in general hospitals, specialized hospitals, teaching hospitals, and primary healthcare units, the number of MRPs increased by 0.176 (p value < 0.001), 0.168 (p value < 0.001), 0.022 (p value < 0.001) and 0.032 (p value < 0.001), respectively. Finally, with each increase of one death per 100,000 inhabitants, the overall mortality rate increased, ranging from 0.006 (p value < 0.001) to 0.022 (p value < 0.001). The study showed a low supply of MRPs in the northern region, a high rate of idleness, and important socioeconomic, structural, and epidemiological determinants of the number of MRPs.