ArticleFrontiers in medicine2025
Evaluating medical education in Brazil: analysis of the National Student Performance Exam 2023.
Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
Background: The evaluation of medical education in Brazil relies on instruments such as the National Student Performance Exam (ENADE) and the Preliminary Course Concept (PCC), which guide regulation and funding. Objectives: To analyze national data from the 2023 ENADE for the medical program, describing variations by administrative category and region, and to discuss implications for building a fairer assessment model aligned with the principles of the Brazilian Unified Health System (SUS). Methods: A descriptive study using consolidated data from 309 Medical Programs participating in ENADE 2023. Mean scores and standard deviations for the continuous PCC (scale 0-5) were calculated by institutional category (federal, state, municipal public institutions, and private with or without profit) and geographic region. Results: Federal public institutions showed a mean PCC of 2.82 ± 0.38; state, 2.74 ± 0.42; and municipal, 2.65 ± 0.45. Private for-profit institutions had 2.72 ± 0.48, and non-profit institutions 2.85 ± 0.42. The Indicator of Difference Between Observed and Expected Performance (IDOEP) component, which accounts for 35% of the PCC, was higher in for-profit private institutions (3.70 ± 0.68) compared to public ones (2.65 ± 0.50), reflecting limitations in adjusting for socioeconomic intake profiles. Student perception scores were also higher in private institutions (3.85 ± 0.60) than in public ones (3.00 ± 0.55). Regionally, PCC means were higher in the South (3.45 ± 0.40) and Southeast (3.35 ± 0.45) than in the Northeast (2.85 ± 0.55) and North (2.70 ± 0.60). Conclusion: Results suggest that the current ENADE/PCC model may mask structural and regional inequalities, favoring institutional strategies focused on large-scale enrollment with lower admission requirements.
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