Performance of Medical Schools and Students in a Rapid Expansion Era: A Cross-sectional Analysis

Performance of Medical Schools and Students in a Rapid Expansion Era: A Cross-sectional Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Performance of Medical Schools and Students in a Rapid Expansion Era: A Cross-sectional Analysis Guilherme Frayha, Danette McKinley, Eliana Amaral This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8622396/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background The rapid expansion of medical schools has been widely adopted as a strategy to address physician shortages and improve access to healthcare. In Brazil, a national policy implemented in 2013 substantially increased medical training capacity, largely through private-sector participation. However, concerns persist regarding whether rapid expansion improved access for students and patients while sustains educational quality. São Paulo is the most populous and economically developed state in Brazil, with structural, regulatory, and market characteristics comparable to those observed in middle- and high-income countries. This offers an informative analytical case to examine the effects of large-scale medical school expansion in a complex health professions education market. Methods This observational, descriptive, cross-sectional study analysed all active undergraduate medical programs registered in the Ministry of Education’s e-MEC system in São Paulo State between 2013 and March 2025. Expansion patterns, geographic distribution, and regional socioeconomic characteristics were assessed using publicly available administrative data. Educational performance was evaluated using official data, the National Student Performance Exam (ENADE 2023) and the Preliminary Course Concept (CPC). Descriptive statistics and non-parametric tests were applied for group comparisons. Multivariate generalized linear models were used to assess associations between institutional characteristics and student performance. Results Between 2013 and 2025, 42 new medical programs were authorized, resulting in a 74.7% increase in available training seats. Expansion was predominantly driven by private institutions, which accounted for 80.5% of newly authorized seats, and was spatially concentrated in regions with higher socioeconomic development and stronger healthcare infrastructure. Regions with lower development indicators experienced little or no expansion. Medical schools with further from their establishment date and public ownership achieved significantly higher student performance scores, whereas newer, predominantly private institutions showed greater variability. Although public institutions demonstrated stronger student performance, they received lower ratings in infrastructure and didactic–pedagogical organization. In multivariate analyses, institutional age and ownership remained independently associated with student performance, while no variables showed significant associations with the overall institutional performance score. Conclusions The expansion of medical education in São Paulo State produced substantial quantitative growth but failed to reduce territorial inequalities. Educational quality was more strongly associated with institutional maturity and public ownership than with expansion alone. As an analytical case reflecting dynamics seen in other regulated health education systems, our example highlights the limits of market-driven expansion and underscores the need for integrated policies that align growth with quality assurance, accreditation, and workforce retention strategies to promote equitable and sustainable healthcare access. Medical Education Public Policy Health Workforce Medical Schools Social accountability Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Medical schools’ expansion and human resources for health For more than a decade, international literature has highlighted persistent shortages and maldistribution of physicians as a central challenge for health systems worldwide 1 – 3 . One commonly adopted strategy to address these imbalances has been the expansion of medical schools and the increase in training capacity. In Brazil, longstanding inequalities in physician distribution and unmet healthcare needs have driven successive public policies aimed at strengthening workforce availability in underserved regions. Policies were intended to expand medical schools in regions with lower physician density 4 and increase the physician workforce 4 , 5 . Implementation of the policies resulted in a rapid and large-scale expansion of medical education, contributing to an increase in the national physician-to-population ratio from 1.76 per 1,000 inhabitants in 2013 to 2.98 in 2025, although variation in geographic distribution persisted 6 . While some service gaps were partially addressed — particularly through newly established decentralized federal medical schools 7 — the accelerated growth generated important challenges related to regulatory capacity, including difficulties in recruiting qualified faculty, securing adequate clinical training environments, and ensuring consistent supervision. These concerns raised questions about institutional performance and training quality 8 . In response, the Ministry of Education (MEC) declared a moratorium in 2018, suspending authorization for new medical courses for five years 9 . Despite this measure, several programs were approved through judicial decisions, bypassing the original requirements of the More Doctors policy 10 . By March 2025, Brazil had 447 active medical courses registered, with more than half (239) established after October 2013 11 . The number of authorized training seats increased from 20,570 to 48,451 6,11 . Expansion was predominantly driven by private institutions (80% of all new seats) 6 . Within this context, São Paulo State with 22% of Brazil’s population (46,081,801 inhabitants) 12 and 18% of the nation’s medical schools, and 91% of all seats offered by private institutions 6 . The National Curricular Guidelines (DCN) are federally mandated standards issued by the Brazilian Ministry of Education that define competencies, learning outcomes, and organizational principles for undergraduate medical education, aligned with the values of the Unified Health System (SUS). The updated 2025 DCN reemphasized the focus on generalist medical doctor training, stressing critical reasoning, humanistic values, and social accountability 13 . Nonetheless, concerns remain regarding whether existing regulatory and evaluation systems are sufficient to ensure educational quality and foster institutional improvement, particularly in contexts of rapid expansion 8 . Using medical schools in São Paulo State as a case-study, we aim to investigate factors associated with institutional and student performance, while examining the geographical distribution of schools and training seats related to the economic development of the region. First, we looked at geographic distribution to examine the extent to which the goal of expansion into areas with fewer resources was achieved. To examine whether there was an association between expansion and educational quality, we analysed student performance on national examinations, and institutional ratings. By focusing on institutional performance during rapid expansion, this analysis offers a data-driven approach that can mirror other regulated health education systems and contributes to the international debate on whether expansion policies can simultaneously promote geographic equity and educational quality. METHODS Study design and inclusion criteria This observational, descriptive, cross-sectional study was conducted using secondary administrative data collected between February and March 2025. The primary data source was the electronic e-MEC system 11 , the official and publicly accessible registry of higher education programs maintained by the Brazilian Ministry of Education (MEC). All active undergraduate medical programs offered by medical schools located in São Paulo State (SP) were identified and included. Programs that were inactive, deregistered, or located outside São Paulo State were excluded. The study was structured in two analytical phases. The first phase examined the alignment between policy goals and the expansion and geographic distribution of medical schools. The second phase focused on institutional characteristics and factors associated with student outcomes. Data were extracted from official sources at a single time point and cross-checked across databases when applicable to minimize the effects of delayed data updates. All active undergraduate medical programs registered in São Paulo State during the study period were included. The e-MEC system defines schools by ownership and legal status. For this study, the classifications for public schools are federal, state, and “special” institutions. Federal public institutions are maintained by the federal government and are generally affiliated with federal universities; state public institutions are managed by state governments. Both categories are tuition-free. Municipal public institutions, classified in the e-MEC system as “special” institutions, are maintained by municipal authorities and may charge tuition fees if established prior to the 1988 Federal Constitution 14 . In this study, the terms “municipal public” and “special” institutions are used interchangeably. Private medical schools were classified into three categories: sectarian institutions linked to religious organizations; non-profit institutions that reinvest financial resources into educational activities; and for-profit institutions that distribute profits to shareholders 15 . When examining geographic distribution, sectarian and other nonprofit institutions were grouped together. When examining educational quality, sectarian institutions were analysed separately to allow a more refined assessment of institutional performance. Geographic distribution To examine the extent to which the goals of expansion improved geographic distribution and access, we used three sets of variables. Changes in medical education capacity across São Paulo State were measured by the number of medical schools and authorized training seats, stratified by administrative category and institutional age. These data were obtained directly from the e-MEC public records 11 . To investigate whether the geographic distribution of medical schools reduced inequalities in distribution, each institution was geocoded by municipality and subsequently grouped according to the Administrative Regions (ARs) defined by the São Paulo Geographic and Cartographic Institute (IGC-SP) 16 . These regions were used as the main territorial units due to the availability of socioeconomic data. We incorporated socioeconomic and demographic characteristics of the ARs hosting medical schools. Indicators related to economic development, social conditions, and population size were extracted from the State System for Data Analysis (SEADE), maintained by the Secretariat of Economic Development of São Paulo State 17 . All datasets used in this phase were publicly available through the e-MEC and SEADE databases. Spatial representations of the distribution of medical schools across the sixteen Administrative Regions were developed using Google Earth® and Adobe Illustrator®. Regional boundaries were based on official geographic data provided by the IGC-SP 16 . Educational performance indicators and statistical analysis Data on institutional performance were obtained from official 2023 report published by the National Institute for Educational Studies and Research Anísio Teixeira (INEP), including results from the National Student Performance Exam (ENADE) and the Preliminary Course Concept (CPC) 18 . ENADE evaluates graduating students’ academic achievement through a multiple-choice assessment with two components, one for general knowledge and another for medical knowledge. The CPC is a composite indicator calculated from a weighted set of components, including students’ performance on ENADE, the value added by the educational process, faculty qualifications and dedication, and students’ perceptions of training conditions, such as pedagogical organization, infrastructure, and opportunities for academic and professional development 18 . Although the final published CPC grade is reported as a categorical integer, the underlying continuous scores were used for statistical analyses. Comparisons of proportions were conducted using the chi-square test or Fisher’s exact test, when appropriate. Comparisons of continuous variables between two groups were performed using the Mann–Whitney U test, while comparisons among three or more groups used the Kruskal–Wallis test, followed by Dunn’s post-hoc test to identify pairwise differences when statistically significant. Associations between continuous variables were assessed using Spearman’s rank correlation coefficient. For all analyses, the level of statistical significance was set at p < 0.05. Ethical considerations and reporting standards This study was approved by the Research Ethics Committee under CAAE 90115225.0.0000.5404. The analysis was based exclusively on publicly available secondary data, without identification of individuals or access to sensitive information. Parts of the English translation and language revision were assisted by an AI-based large language model (ChatGPT, OpenAI), under the authors’ supervision. The study design and reporting followed the recommendations of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement, ensuring transparency, reproducibility, and methodological rigor. RESULTS Expansion and Geographic Distribution Between October 2013 and March 2025, São Paulo State recorded the authorization of 42 new undergraduate medical programs, increasing the total number of active medical schools to 80. During this period, the number of entry-level medical seats increased by 74.7%, rising from 5,661 to 9,892. Most of this expansion occurred before the implementation of a moratorium phase, and by April 2018, the number of authorized seats had already increased to 8,487. Of the 42 new medical programs, 17 (40.5%) were authorized under for-profit private institutions, followed by 14 (33.3%) nonprofit private institutions. Overall, private institutions accounted for 80.5% of all newly authorized seats (n=3,405), whereas public institutions — including municipal programs — represented only 19.5% of the expansion in training capacity (Figure 1). Socioeconomic Context and Distribution of Medical Schools The expansion was spatially concentrated in AR XIII and XV (47.5% of all newly authorized programs), with 11 and 10 new medical schools, respectively. Figure 2 presents the spatial distribution of medical schools according to administrative category and period of establishment (before or after 2013). Regions with higher socioeconomic development (XV and XIII) combining the largest populations with the highest levels of economic output, experienced the most substantial increases in both the number of programs and authorized seats. In contrast, regions characterized by lower per capita income, higher illiteracy rates, and worse health indicators — particularly infant mortality — showed limited or no expansion (Tables 1). Table 1. Administrative Regions of the Sao Paulo State with their socioeconomic and health indicators. Administrative Region Population GDP per capita (R$) Illiteracy * Infant mortality* XV 20.751.191 88.045 2.8 11.3 XIII 7.110.442 93.170 2.9 9.5 IX 2.679.464 64.534 3.2 12.4 XVI 2.530.487 71.821 2.9 11.4 XIV 1.817.099 54.905 3.0 12.3 III 1.626.818 51.852 3.9 10.0 XI 1.399.563 64.977 3.2 11.8 V 1.115.716 60.376 3.4 11.4 VIII 1.029.194 63.352 3.6 12.2 IV 973.565 53.235 3.9 13.4 I 859.287 44.379 4.4 10.8 II 776.333 48.032 4.1 12.0 XII 744.637 53.967 3.5 11.0 VI 524.764 42.512 5.7 11.0 VII 440.381 60.625 3.8 10.3 X 272.773 46.603 5.8 15.2 State 44.651.714 77.958 3.1 11.2 GDP = Gross Domestic Product | *per 1000 live births | ** percentage of the population Table 2 summarizes the distribution of new training seats by AR before and after 2013. Statewide availability increased from 1.29 to 2.25 seats per 10,000 inhabitants, approximately 75% growth. However, this increase was uneven across regions. In contrast, AR VI and X, among the lowest GDP per capita, did not receive any new medical programs or seats during the expansion period. Despite substantial absolute growth in AR XV and XIII, the rates of seat availability per capita in these populous regions remained low. Conversely, one AR (V), with no medical schools in 2013, reached one of the highest seat densities per 10,000 inhabitants by 2025. These findings highlight persistent inequities despite the increase in training capacity. Table 2. Administrative Regions of the State of São Paulo, availability of medical schools, seats, and seats per 10,000 inhabitants, before and after 2013*. Administrative Region Medical Schools (2013) Medical Schools (2025) (% increase) Seats/10,000 inhabitants (2013) Seats/10,000 inhabitants (2025)** Seats in 2013 Seats in 2025 (% increase) XV 12 22 (83.3) 1.21 1.88 2521 3912 (55.2) XIII 5 16 (120) 1.09 2.39 745 1629 (118.7) IX 2 6 (200) 0.88 2.01 220 500 (127.3) XVI 1 4 (300) 0.49 2.04 120 500 (316.7) XIV 2 5 (150) 1.11 2.67 200 480 (140) III 6 7 (16.7) 4.38 4.78 665 725 (9) XI 3 4 (33.3) 2.63 3.19 360 436 (21.1) V 0 3 0 3.74 0 415 VIII 2 2 (0) 1.88 1.88 190 190 (0) IV 2 3 (50) 2.36 2.98 230 290 (26.1) I 1 3 (200) 2.56 4.50 220 386 (75.5) II 0 2 0 2.24 0 173 XII 1 2 (100) 1.34 2.22 100 166 (66) VI 0 0 (0) 0 0 0 0 (0) VII 1 1 (0) 2.08 2.08 90 90 (0) X 0 0 (0) 0 0 0 0 (0) State 38 80 1.29 2.25 5661 9892 *Year of implementation of the More Doctors Law **Total undergraduate medical seats per 10,000 inhabitants in March 2025 Institutional Characteristics and Performance Among the 80 medical schools active in São Paulo State, only 55 had assigned CPC and ENADE indicators in the 2023 national evaluation cycle, reflecting the absence of graduating cohorts in newer programs. Public institutions consistently achieved CPC scores above 3.0 and were predominantly among those with more than 30 years of operation. Private and municipal institutions showed greater dispersion and were more frequently concentrated in lower CPC ranges (Figure 3; Table 3). Federal and state public medical schools also achieved the highest average student performance scores, measured by the continuous ENADE score (4.34 ± 0.36), with significant differences compared to all other administrative categories (p = 0.0018). Both general and specific components of ENADE showed the same trends (Table 3). In contrast, federal and state institutions presented lower average scores in the domains of Didactic-Pedagogical Organization and Infrastructure (p=0.04) and Physical Facilities (p=0.04), according to student perceptions, when compared to private institutions. Table 3. Comparison of the Program Score Descriptors (standardized) and Institutional Age by Administrative Type among Medical Schools in the State of São Paulo Variable (Mean ± Standard Deviation) Federal + State Private For-Profit Private Nonprofit Municipal & Religious TOTAL P-Value (N=6) (N=14) (N=25) (N=10) (N=55) Institution Age (years) 58.17 ± 21.85 15.64 ± 13.31 23.20 ± 19.14 34.10 ± 26.29 27.07 ± 22.85 0.0050 *CPC (Continuous) 3.63 ± 0.32 2.79 ± 0.73 2.88 ± 0.88 2.60 ± 0.74 2.89 ± 0.81 0.0908 Enade Score 4.34 ± 0.36 2.10 ± 0.94 2.58 ± 1.27 2.89 ± 1.05 2.70 ± 1.24 0.0018 Enade General Component 4.32 ± 0.44 1.93 ± 0.70 2.53 ± 1.15 2.78 ± 0.99 2.62 ± 1.16 0.0004 Enade Specific Components 4.35 ± 0.38 2.15 ± 1.06 2.59 ± 1.39 2.92 ± 1.13 2.73 ± 1.32 0.0052 Didactic-Pedagogical Organization 2.69 ± 0.46 3.77 ± 0.76 3.77 ± 0.96 3.53 ± 1.13 3.61 ± 0.94 0.0379 Infrastructure and Physical Facilities 2.61 ± 0.54 3.88 ± 0.77 3.78 ± 0.97 3.70 ± 1.26 3.66 ± 1.00 0.0393 Opportunities for Academic Development 2.88 ± 0.68 3.46 ± 0.92 3.35 ± 1.37 3.25 ± 1.17 3.31 ± 1.16 0.6175 *Course Score (CPC) | All scores range from 0 to 5. Student Performance Student performance distributions by administrative category and institutional age are shown in Figure 4. Federal and state public institutions achieved mean ENADE scores close to or above 4.0, while private and municipal institutions exhibited greater variability, with almost half scoring below 4.0. Institutions operating for more than 30 years demonstrated significantly higher average ENADE scores compared with programs up to 10 years old and those with intermediate years of operation (3.52 ± 1.07; p = 0.0015) (Table 4). This pattern was observed for both the general and specific - medical knowledge- components of student´s performance examination. When analysing separately the specific component, statistically significant differences were observed only between institutions older than 30 years and those up to 10 years (p = 0.0076). No statistically significant differences were identified across institutional age groups for Didactic-Pedagogical Organization, Infrastructure and Physical Facilities, Opportunities for Academic Development, or the summative continuous CPC score – Table 4. Table 4. Comparison of Course Score (CPC) Descriptors by Institutional Age Range among Medical Schools in the State of São Paulo Variable ≤ 10 years 11–30 years (N=19) > 30 years (N=17) TOTAL (N=55) N=19 Mean (± SD) Mean (± SD) Mean (± SD) Mean (± SD) P-Value 1 Enade Score 2.06 ± 1.30 2.62 ± 0.91 3.52 ± 1.07 2.70 ± 1.24 0.0015 Enade General Score 1.99 ± 0.95 2.39 ± 0.91 3.58 ± 1.03 2.62 ± 1.16 0.0002 Enade Specific Score 2.08 ± 1.47 2.70 ± 0.98 3.50 ± 1.11 2.73 ± 1.32 0.0076 Didactic-Pedagogical Organization 3.70 ± 0.87 3.84 ± 0.92 3.26 ± 1.00 3.61 ± 0.94 0.1640 Infrastructure and Physical Facilities 3.78 ± 0.86 3.87 ± 1.01 3.31 ± 1.09 3.66 ± 1.00 0.1908 Opportunities for Academic Development 3.04 ± 1.22 3.46 ± 1.19 3.44 ± 1.06 3.31 ± 1.16 0.4882 *CPC 2.68 ± 0.99 2.91 ± 0.62 3.09 ± 0.76 2.89 ± 0.81 0.2535 ¹ Kruskal–Wallis Test | * Course Score (CPC) | All scores range from 0 to 5. Multivariate analyses using generalized linear models confirmed that institutional age and administrative category remained independently associated with student and school performance. Programs operating for more than 30 years achieved higher ENADE scores than those with up to 10 years of operation (p = 0.0097), and federal or state public institutions performed significantly better than municipal or religious (p = 0.0287), for-profit private (p = 0.0021), and nonprofit private (p = 0.0088) institutions. No variables showed statistically significant associations with the summative CPC score. DISCUSSION The expansion of medical schools in the region, following the implementation of the More Doctors Program, resulted in a substantial increase in training capacity, largely driven by private institutions and concentrated in regions with stronger infrastructure, better social indicators, and higher economic development. In contrast, the most underserved regions did not receive new medical programs. These findings indicate that the Brazilian National policy aiming to stimulate medical training in priority and underserved areas was not reached in the most populous and economically developed state. This pattern mirrors national trends, with limited expansion in regions with lower socioeconomic development, fragile academic structures, and insufficient health-service capacity 19 . The selective and uneven expansion observed across São Paulo State further illustrates how market-driven growth tends to reinforce pre-existing territorial disparities. It is also important to highlight that rapid expansion risks exceeding the capacity required for adequate training clinical spaces in the health system, qualified supervision, risking competency development of trainees. The present findings also demonstrate that medical schools with longer institutional trajectories tend to achieve better educational outcomes, particularly in student performance measures, corroborating previous national studies 8 , 20 . Most newer institutions — predominantly private — have not yet reached comparable levels of performance, reinforcing concerns that rapid expansion may compromise educational quality in the absence of sufficient institutional maturation. Concerns about shortages in medical specialties have recently motivated a new federal initiative, “Now We Have Specialists”, which aims to expand access to high-demand specialties through limited increases in training positions and larger incentives for private-sector participation 21 . However, evidence suggests that physician retention in underserved areas depends on multiple, interrelated factors, including the location of specialty training 22 and broader perceptions of quality of life for professionals and their families 23 . It therefore remains uncertain whether this strategy will improve equitable access to specialized care or further strengthen private-sector control over service provision. Interestingly, federal and state public institutions, despite achieving higher student performance, received lower ratings in domains related to didactic-pedagogical organization and infrastructure. This apparent paradox may reflect the strong critical thinking and academic attitude of students under a selective admission processes characteristic of public universities, alongside structural constraints such as limited funding, bureaucratic rigidity, and reduced managerial flexibility 24 . In contrast, private institutions—especially for-profit ones—often demonstrate greater capacity for infrastructure investment without reaching equivalent academic outcomes. This divergence raises broader questions about how market-driven logic shapes educational quality and the preparation of doctors aligned with the values and premises of the public health systems 25 . This study has important limitations. Its cross-sectional design precludes causal inference, and the use of secondary administrative data may involve reporting inconsistencies. The analysis did not include qualitative dimensions of training, a deeper analysis of physician distribution, nor direct measures of professional competence or quality of care. It also does not focus on impact of expansion on health indictors, a difficulty outcome to assess due to multiple confounding variables. Additionally, as the focus was limited to a wealthy jurisdiction, the findings may not be fully generalizable to less developed regions. Another central issue concerns the reliance on regulatory indicators such as ENADE and CPC as indirect measures of educational quality. While these instruments are valuable for system-level monitoring and policy guidance, they provide only partial assessments of quality and may inadequately capture institutional weaknesses or strengths 26 . Moreover, student performance evaluations carry the risk of incentivizing teaching practices oriented toward test preparation rather than comprehensive, clinically grounded, and transformative education. A comprehensive evaluation of medical education requires integration of multiple dimensions. Accreditation frameworks based on global standards, such as those of the World Federation for Medical Education (WFME) adapted to local contexts, remain key benchmarks for quality and international legitimacy 27 . In Brazil, the Sistema de Acreditação de Escolas Médicas (SAEME), recognized by the WFME, provides a voluntary external evaluation process, though it lacks regulatory authority 28 . As of 2024, only 76 schools had undergone voluntary evaluation, with 72.4% receiving accreditation 29 . At the same time, international trends increasingly emphasize learning outcomes assessed through national licensing examinations—such as the United Kingdom’s Medical Licensing Assessment 30 — or through longitudinal, programmatic assessment models 31 , 32 incorporating multiple sources of evidence, including Entrustable Professional Activities (EPAs) 33 . Although high-stakes examinations ensure minimum competence, their limitations in assessing attitudinal, ethical, and professional dimensions of practice are well recognized 34 – 36 . Brazil’s evaluation landscape is currently evolving with the recent implementation of the National Medical Assessment Exam (ENAMED), designed to assess students at stages of training, before entry into interniship training due in 5th and 6th year 37 . This initiative aligns Brazil with international models of progressive assessment, although its current format is focused on cognitive skills. Taken together, these findings underscore the limits of market-driven expansion in addressing territorial inequities and sustaining educational quality. Effective workforce planning requires integrated strategies encompassing undergraduate education, residency training, working conditions, and broader intersectorial policies aligned with the organizational capacity of the health system in place. The territory under study — whose demographic and economic characteristics resemble those of middle-high income settings— illustrates challenges that are highly relevant internationally, reinforcing the need for regulatory frameworks that balance expansion with quality, accountability, and social mission. CONCLUSION The expansion of medical schools in São Paulo State following the 2013 national policy produced substantial quantitative growth, largely driven by private institutions and concentrated in regions with higher socioeconomic development and more robust healthcare infrastructure. Consequently, the central policy objective of reducing territorial inequalities in medical training was not achieved in the country’s most populous and economically developed state, highlighting the limits of market-oriented expansion strategies in addressing inequitable access. Abbreviations AR Administrative Region CAAE Certificate of Presentation for Ethical Review CPC Preliminary Course Concept DCN National Curricular Guidelines GDP Gross Domestic Product IBGE Brazilian Institute of Geography and Statistics IGC SP–São Paulo Geographic and Cartographic Institute INEP National Institute for Educational Studies and Research MEC Ministry of Education PITS Program for the Decentralization of Health Work PROVAB Program for the Valorization of Primary Care Professionals REUNI Program for the Support to Restructure and Expansion of Federal Universities SEADE State System for Data Analysis SUS Unified Health System WHO World Health Organization Declarations Ethics approval and consent to participate Approved by the Research Ethics Committee of School of Medical Sciences, University of Campinas (Unicamp) under protocol CAAE 90115225.0.0000.5404. Consent to Participate declaration Not applicable. Consent for publication Not applicable. Availability of data and materials All data are publicly available from the e-MEC system (https://emec.mec.gov.br) and SEADE Foundation databases (https://painel.seade.gov.br/saude/). Competing interests The authors declare that they have no competing interests. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors’ contributions GF collected, analyzed, and interpreted data and drafted the manuscript. EA supervised the study, contributed to conceptualization, and critically reviewed the manuscript. DM supervised the study, contributed to conceptualization, and critically reviewed the manuscript. All authors read and approved the final version. Acknowledgements This study was supported by the Coordination for the Improvement of Higher Education Personnel (CAPES) – Brazil – Funding Code 001. Authors' information Guilherme Frayha, MD is a master’s student in Health Professions Education at the School of Medical Sciences, University of Campinas (Unicamp), Brazil. ORCID: 0009-0005-9561-5052. Eliana Amaral, MD, PhD is Full Professor at the Department of Obstetrics & Gynecology at the School of Medical Sciences, University of Campinas (UNICAMP). ORCID: 0000-0001-9151-3108. Danette McKinley, PhD, is Senior Analyst at the Foundation for International Medical Education and Research (FAIMER), a division of Intealth, United States. ORCID: 0000-0002-8709-0365. References Lorkowski J, Jugowicz A. Shortage of Physicians: A Critical Review. Adv Exp Med Biol. 2021;1324:57-62. doi: 10.1007/5584_2020_601. PMID: 33346901. Herrick C, Armstrong D. How many doctors does a health system need? Histories of workforce planning in the NHS. Soc Sci Med. 2025 Apr;371:117882. doi: 10.1016/j.socscimed.2025.117882. Epub 2025 Feb 24. PMID: 40054388. Crisp N, Chen L. 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Brazil’s experiment to expand its medical workforce through private and public schools: impacts and consequences of the balance of regulatory and market forces in resource-scarce settings. Glob Health. 2025;21:14. doi: 10.1186/s12992-025-01105-8. Brasil. Ministério da Educação. Portaria nº 328, de 5 de abril de 2018. Dispõe sobre a suspensão do protocolo de pedidos de aumento de vagas e novos editais de chamamento público para cursos de Medicina. Diário Oficial da União. 2018 abr 6. Brasil. Ministério da Educação. Secretaria de Regulação e Supervisão da Educação Superior. Processos de cursos de medicina em tramitação na Seres/MEC. Brasília: MEC; 2024. Available from: https://www.gov.br/mec/pt-br/assuntos/es/cursos-de-medicina/regulacao-e-supervisao/documentos/AesMedicinaApresentaoNota22Final.pdf Brasil. Ministério da Educação. e-MEC: Sistema eletrônico de acompanhamento dos processos que regulam a educação superior no Brasil [Internet]. Available from: https://emec.mec.gov.br/emec/nova#avancada Instituto Brasileiro de Geografia e Estatística (IBGE). Censo Demográfico 2022: população e domicílios. Rio de Janeiro: IBGE; 2023. Available from: https://biblioteca.ibge.gov.br/index.php/biblioteca-catalogo?id=2102011&view=detalhes Brasil. Ministério da Educação. Conselho Nacional de Educação. Câmara de Educação Superior. Resolução CNE/CES nº 3, de 30 de setembro de 2025. Institui Diretrizes Curriculares Nacionais do Curso de Graduação em Medicina. Diário Oficial da União, Brasília (DF), 1º out 2025; Seção 1:35-37. Barbosa ACQ, Silva APL, Santos NR. A municipalização do ensino superior no Brasil: um estudo de multicasos na dimensão estrutural e de gestão de pessoas. Rev GUAL. 2021;14(1):226-47. doi:10.5007/1983-4535.2021.e80173. Brasil. Lei nº 9.394, de 20 de dezembro de 1996. Estabelece as diretrizes e bases da educação nacional. Diário Oficial da União. 1996 dez 23;Seção 1:27833. Art. 16, 20. Instituto Geográfico e Cartográfico de São Paulo. Mapa das Regiões Administrativas e Metropolitanas do Estado de São Paulo [Internet]. São Paulo: IGC-SP. Available from: http://www.igc.sp.gov.br/produtos/regioes_adm.html Fundação Sistema Estadual de Análise de Dados (SEADE). Painel de dados sociais, econômicos e demográficos: saúde — municípios e regiões do Estado de São Paulo. São Paulo: SEADE. Available from: https://painel.seade.gov.br/saude/ Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira (INEP). CPC 2023 [Internet]. Brasília: INEP; 2023. Available from: https://download.inep.gov.br/educacao_superior/indicadores/resultados/2023/CPC_2023.xlsx Guimarães, R.A., de França e Silva, A.L.G., de Souza, M.R. et al. Trend and spatial clustering of medical education in Brazil: an ecological study of time series from 2010 to 2021. BMC Health Serv Res 23, 882 (2023). https://doi.org/10.1186/s12913-023-09795-9 Oliveira FP, Mota JAC, Almeida RBF, Silva AB. Lessons learned from the expansion of medical schools in Brazil. Front Educ. 2024;8:1494445. doi: 10.3389/feduc.2024.1494445 Brasil. Medida Provisória nº 1.301. Institui o Programa Agora Tem Especialistas. Diário Oficial da União, Brasília (DF), 30 de maio de 2025. Koike, S., Okazaki, K., Tokinobu, A. et al. Factors associated with regional retention of physicians: a cross-sectional online survey of medical students and graduates in Japan. Hum Resour Health 21, 85 (2023). https://doi.org/10.1186/s12960-023-00871-z Mohammadiaghdam, N., Doshmangir, L., Babaie, J. et al. Determining factors in the retention of physicians in rural and underdeveloped areas: a systematic review. BMC Fam Pract 21, 216 (2020). https://doi.org/10.1186/s12875-020-01279 Paula MD. Políticas de democratização da educação superior brasileira: limites e desafios para a próxima década. Avaliação (Campinas). 2017 [acesso em 2022 jul 5]; 22(2):301-15. Disponível em: https://doi.org/10.1590/S1414-40772017000200002 Morais HMM, Sá RGR, Albuquerque MSV, Oliveira RS. Expansão e privatização dos cursos de medicina e a integração ensino-serviço: o caso do estado de Pernambuco. Saúde Debate. 2023 Abr-Jun;47(137):182-195. doi:10.1590/0103-1104202313713 Pereira CA, Araujo JFFE, Machado-Taylor ML. The Brazilian higher education evaluation model: “SINAES” sui generis? Int J Educ Dev. 2018;61:5-15. doi:10.1016/j.ijedudev.2017.11.007. World Federation for Medical Education. WFME Global Standards for Quality Improvement: Basic Medical Education. 2020 revision. Ferney-Voltaire: WFME; 2020. Sistema de Acreditação de Escolas Médicas. [Internet]. [citado em 2025 set 28]. Disponível em: https://www.saeme.org.br/ Tempski P, Girotto LC, Brenelli S, Giamberardino DD, Martins MA. Accreditation of medical education in Brazil: an evaluation of seventy-six medical schools. BMC Med Educ. 2024 Jun 12;24(1):656. doi: 10.1186/s12909-024-05623-8. PMID: 38867222; PMCID: PMC11167757. General Medical Council. Assuring readiness for practice: A framework for the MLA. London: GMC; out 2024. Ross S, Ellaway RH, et al. Toward programmatic assessment in Canadian medical education: national initiatives and early lessons. Acad Med. 2023;98(5):579-586. Jamieson J, et al. Evaluating programmatic assessment: theoretical program evaluation. Adv Health Sci Educ. 2025;30(1):45-62. Cheung WJ, et al. Entrustable Professional Activities in undergraduate medical education: wide-scale implementation. Perspect Med Educ. 2024;13(3):162-170. Sidhu, N. S., & Fleming, S. (2023). Re-examining single-moment-in-time high-stakes examinations in specialist training: A critical narrative review. Medical Teacher, 46(4), 528–536. https://doi.org/10.1080/0142159X.2023.2260081 Bhanji, F., Naik, V., Skoll, A., Pittini, R., Daniels, V.J., Bacchus, C.M. and Bandiera, G. (2024) ‘Competence by Design: The Role of High-Stakes Examinations in a Competence Based Medical Education System’, Perspectives on Medical Education, 13(1), p. 68–74. French, S., Dickerson, A. & Mulder, R.A. A review of the benefits and drawbacks of high-stakes final examinations in higher education. High Educ 88, 893–918 (2024). https://doi.org/10.1007/s10734-023-01148-z Brasil. Ministério da Educação. Portaria MEC nº 330, de 23 de abril de 2025. Institui o Exame Nacional de Avaliação da Formação Médica – Enamed. Diário Oficial da União. 2025 abr 24;Seção 1:119. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 17 Mar, 2026 Editor assigned by journal 01 Feb, 2026 Submission checks completed at journal 01 Feb, 2026 First submitted to journal 16 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8622396","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":608124995,"identity":"ecb9c040-7276-4358-9087-197bf7bc9394","order_by":0,"name":"Guilherme Frayha","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYFACxoYPQDKBgb0BSBlYEKWlcQZYC88BkBYJ4qyBaJFIAHGI0CIfkdzYXFFzOI9/5vOrG34USDDwt3cn4NVieCOxsfHMscPFErdzym72AB0mcebsBvxaZiS2P2xgO5zYcDsn7QYPUIuBRC5BLY2NDf8OJ86/eSbt5h9itMhLALU0th1O3HCD/dhtomwx4HkI1NKXnrjxTA7bbRkDCR6CfpFvT3/Y2PDNOnHe8ePPbr75YyPH395LwJYDYKoZiHkMQCwevMrBtjSAqTogZn9AUPUoGAWjYBSMTAAAmRJSei1oWrsAAAAASUVORK5CYII=","orcid":"","institution":"University of Campinas (UNICAMP)","correspondingAuthor":true,"prefix":"","firstName":"Guilherme","middleName":"","lastName":"Frayha","suffix":""},{"id":608124996,"identity":"f40de3a9-731f-43f8-bcd4-93b5b15d2fe3","order_by":1,"name":"Danette McKinley","email":"","orcid":"","institution":"Foundation for Advancement of International Medical Education and Research","correspondingAuthor":false,"prefix":"","firstName":"Danette","middleName":"","lastName":"McKinley","suffix":""},{"id":608124997,"identity":"e403246b-3bbd-41dc-9365-0146f1ae2d95","order_by":2,"name":"Eliana Amaral","email":"","orcid":"","institution":"University of Campinas (UNICAMP)","correspondingAuthor":false,"prefix":"","firstName":"Eliana","middleName":"","lastName":"Amaral","suffix":""}],"badges":[],"createdAt":"2026-01-16 22:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8622396/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8622396/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105149792,"identity":"5b14ddf3-8777-41db-ae98-50f9e9ea4fcd","added_by":"auto","created_at":"2026-03-22 14:57:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":81301,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eEvolution of the Cumulative Total seats at Medical Schools in the State of São Paulo, by Administrative Category (2005–2025).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8622396/v1/c357c213bc5b14d2d7663f24.png"},{"id":105149793,"identity":"f1f53475-6c80-46a4-9c7a-416c8c7ac12b","added_by":"auto","created_at":"2026-03-22 14:57:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":136900,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSpatial representation of medical courses in the state of São Paulo as of March 2025, classified by administrative category and year of establishment.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8622396/v1/37f0ddbf1b82c2473b3d6df9.png"},{"id":105149795,"identity":"48cd7470-d01c-4dfc-a46e-37cdd3a66310","added_by":"auto","created_at":"2026-03-22 14:57:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":79688,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of continuous course score (CPC) according to the year of establishment of medical schools, categorized by administrative type.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8622396/v1/712b750904eb15a531001717.png"},{"id":105149794,"identity":"cdb3f202-e295-4713-8fab-36496a7a6daa","added_by":"auto","created_at":"2026-03-22 14:57:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":81106,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of student´s performance scores (ENADE) according to the year of establishment of medical schools, categorized by administrative type.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8622396/v1/f730540ec244819e0adcc9c1.png"},{"id":105149800,"identity":"299cc743-ebbe-4525-8a4b-0e4564767a54","added_by":"auto","created_at":"2026-03-22 14:58:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1209733,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8622396/v1/898e9106-ad8e-4688-ae9e-34d5e6f54b69.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003ePerformance of Medical Schools and Students in a Rapid Expansion Era: A Cross-sectional Analysis\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eMedical schools’ expansion and human resources for health\u003c/h2\u003e \u003cp\u003eFor more than a decade, international literature has highlighted persistent shortages and maldistribution of physicians as a central challenge for health systems worldwide\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. One commonly adopted strategy to address these imbalances has been the expansion of medical schools and the increase in training capacity. In Brazil, longstanding inequalities in physician distribution and unmet healthcare needs have driven successive public policies aimed at strengthening workforce availability in underserved regions. Policies were intended to expand medical schools in regions with lower physician density\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e and increase the physician workforce\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eImplementation of the policies resulted in a rapid and large-scale expansion of medical education, contributing to an increase in the national physician-to-population ratio from 1.76 per 1,000 inhabitants in 2013 to 2.98 in 2025, although variation in geographic distribution persisted\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. While some service gaps were partially addressed — particularly through newly established decentralized federal medical schools\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e — the accelerated growth generated important challenges related to regulatory capacity, including difficulties in recruiting qualified faculty, securing adequate clinical training environments, and ensuring consistent supervision. These concerns raised questions about institutional performance and training quality\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. In response, the Ministry of Education (MEC) declared a moratorium in 2018, suspending authorization for new medical courses for five years\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Despite this measure, several programs were approved through judicial decisions, bypassing the original requirements of the More Doctors policy\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBy March 2025, Brazil had 447 active medical courses registered, with more than half (239) established after October 2013\u003csup\u003e11\u003c/sup\u003e. The number of authorized training seats increased from 20,570 to 48,451\u003csup\u003e6,11\u003c/sup\u003e. Expansion was predominantly driven by private institutions (80% of all new seats)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Within this context, São Paulo State with 22% of Brazil’s population (46,081,801 inhabitants)\u003csup\u003e12\u003c/sup\u003e and 18% of the nation’s medical schools, and 91% of all seats offered by private institutions\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe National Curricular Guidelines (DCN) are federally mandated standards issued by the Brazilian Ministry of Education that define competencies, learning outcomes, and organizational principles for undergraduate medical education, aligned with the values of the Unified Health System (SUS). The updated 2025 DCN reemphasized the focus on generalist medical doctor training, stressing critical reasoning, humanistic values, and social accountability\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Nonetheless, concerns remain regarding whether existing regulatory and evaluation systems are sufficient to ensure educational quality and foster institutional improvement, particularly in contexts of rapid expansion\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eUsing medical schools in São Paulo State as a case-study, we aim to investigate factors associated with institutional and student performance, while examining the geographical distribution of schools and training seats related to the economic development of the region. First, we looked at geographic distribution to examine the extent to which the goal of expansion into areas with fewer resources was achieved. To examine whether there was an association between expansion and educational quality, we analysed student performance on national examinations, and institutional ratings. By focusing on institutional performance during rapid expansion, this analysis offers a data-driven approach that can mirror other regulated health education systems and contributes to the international debate on whether expansion policies can simultaneously promote geographic equity and educational quality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e\n\n \n\n \n\n"},{"header":"METHODS","content":"\u003ch2\u003eStudy design and inclusion criteria\u003c/h2\u003e\u003cp\u003eThis observational, descriptive, cross-sectional study was conducted using secondary administrative data collected between February and March 2025. The primary data source was the electronic e-MEC system\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, the official and publicly accessible registry of higher education programs maintained by the Brazilian Ministry of Education (MEC). All active undergraduate medical programs offered by medical schools located in São Paulo State (SP) were identified and included. Programs that were inactive, deregistered, or located outside São Paulo State were excluded.\u003c/p\u003e\u003cp\u003eThe study was structured in two analytical phases. The first phase examined the alignment between policy goals and the expansion and geographic distribution of medical schools. The second phase focused on institutional characteristics and factors associated with student outcomes. Data were extracted from official sources at a single time point and cross-checked across databases when applicable to minimize the effects of delayed data updates.\u003c/p\u003e\u003cp\u003eAll active undergraduate medical programs registered in São Paulo State during the study period were included. The e-MEC system defines schools by ownership and legal status. For this study, the classifications for public schools are federal, state, and “special” institutions. Federal public institutions are maintained by the federal government and are generally affiliated with federal universities; state public institutions are managed by state governments. Both categories are tuition-free. Municipal public institutions, classified in the e-MEC system as “special” institutions, are maintained by municipal authorities and may charge tuition fees if established prior to the 1988 Federal Constitution\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. In this study, the terms “municipal public” and “special” institutions are used interchangeably.\u003c/p\u003e\u003cp\u003ePrivate medical schools were classified into three categories: sectarian institutions linked to religious organizations; non-profit institutions that reinvest financial resources into educational activities; and for-profit institutions that distribute profits to shareholders\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. When examining geographic distribution, sectarian and other nonprofit institutions were grouped together. When examining educational quality, sectarian institutions were analysed separately to allow a more refined assessment of institutional performance.\u003c/p\u003e\u003ch3\u003eGeographic distribution\u003c/h3\u003e\u003cp\u003eTo examine the extent to which the goals of expansion improved geographic distribution and access, we used three sets of variables. Changes in medical education capacity across São Paulo State were measured by the number of medical schools and authorized training seats, stratified by administrative category and institutional age. These data were obtained directly from the e-MEC public records\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTo investigate whether the geographic distribution of medical schools reduced inequalities in distribution, each institution was geocoded by municipality and subsequently grouped according to the Administrative Regions (ARs) defined by the São Paulo Geographic and Cartographic Institute (IGC-SP)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. These regions were used as the main territorial units due to the availability of socioeconomic data.\u003c/p\u003e\u003cp\u003eWe incorporated socioeconomic and demographic characteristics of the ARs hosting medical schools. Indicators related to economic development, social conditions, and population size were extracted from the State System for Data Analysis (SEADE), maintained by the Secretariat of Economic Development of São Paulo State\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. All datasets used in this phase were publicly available through the e-MEC and SEADE databases.\u003c/p\u003e\u003cp\u003eSpatial representations of the distribution of medical schools across the sixteen Administrative Regions were developed using Google Earth® and Adobe Illustrator®. Regional boundaries were based on official geographic data provided by the IGC-SP\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e\u003ch3\u003eEducational performance indicators and statistical analysis\u003c/h3\u003e\u003cp\u003eData on institutional performance were obtained from official 2023 report published by the National Institute for Educational Studies and Research Anísio Teixeira (INEP), including results from the National Student Performance Exam (ENADE) and the Preliminary Course Concept (CPC)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. ENADE evaluates graduating students’ academic achievement through a multiple-choice assessment with two components, one for general knowledge and another for medical knowledge. The CPC is a composite indicator calculated from a weighted set of components, including students’ performance on ENADE, the value added by the educational process, faculty qualifications and dedication, and students’ perceptions of training conditions, such as pedagogical organization, infrastructure, and opportunities for academic and professional development\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAlthough the final published CPC grade is reported as a categorical integer, the underlying continuous scores were used for statistical analyses. Comparisons of proportions were conducted using the chi-square test or Fisher’s exact test, when appropriate. Comparisons of continuous variables between two groups were performed using the Mann–Whitney U test, while comparisons among three or more groups used the Kruskal–Wallis test, followed by Dunn’s post-hoc test to identify pairwise differences when statistically significant. Associations between continuous variables were assessed using Spearman’s rank correlation coefficient. For all analyses, the level of statistical significance was set at p \u0026lt; 0.05.\u003c/p\u003e\u003ch3\u003eEthical considerations and reporting standards\u003c/h3\u003e\u003cp\u003eThis study was approved by the Research Ethics Committee under CAAE 90115225.0.0000.5404. The analysis was based exclusively on publicly available secondary data, without identification of individuals or access to sensitive information. Parts of the English translation and language revision were assisted by an AI-based large language model (ChatGPT, OpenAI), under the authors’ supervision. The study design and reporting followed the recommendations of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement, ensuring transparency, reproducibility, and methodological rigor.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eExpansion and Geographic Distribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBetween October 2013 and March 2025, S\u0026atilde;o Paulo State recorded the authorization of 42 new undergraduate medical programs, increasing the total number of active medical schools to 80. During this period, the number of entry-level medical seats increased by 74.7%, rising from 5,661 to 9,892. Most of this expansion occurred before the implementation of a moratorium phase, and by April 2018, the number of authorized seats had already increased to 8,487.\u003c/p\u003e\n\u003cp\u003eOf the 42 new medical programs, 17 (40.5%) were authorized under for-profit private institutions, followed by 14 (33.3%) nonprofit private institutions. Overall, private institutions accounted for 80.5% of all newly authorized seats (n=3,405), whereas public institutions \u0026mdash; including municipal programs \u0026mdash; represented only 19.5% of the expansion in training capacity (Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSocioeconomic Context and Distribution of Medical Schools\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe expansion was spatially concentrated in AR XIII and XV (47.5% of all newly authorized programs), with 11 and 10 new medical schools, respectively. Figure 2 presents the spatial distribution of medical schools according to administrative category and period of establishment (before or after 2013).\u003c/p\u003e\n\u003cp\u003eRegions with higher socioeconomic development (XV and XIII) combining the largest populations with the highest levels of economic output, experienced the most substantial increases in both the number of programs and authorized seats. In contrast, regions characterized by lower per capita income, higher illiteracy rates, and worse health indicators \u0026mdash; particularly infant mortality \u0026mdash; showed limited or no expansion (Tables 1).\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 605px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Administrative Regions of the Sao Paulo State with their socioeconomic and health indicators.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAdministrative Region\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003ePopulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eGDP per capita (R$)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eIlliteracy *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eInfant mortality*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eXV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e20.751.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e88.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eXIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e7.110.442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e93.170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eIX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2.679.464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e64.534\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e12.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eXVI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2.530.487\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e71.821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eXIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.817.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e54.905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e12.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.626.818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e51.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eXI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.399.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e64.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.115.716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e60.376\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eVIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.029.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e63.352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e973.565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e53.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e13.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e859.287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e44.379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e776.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e48.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eXII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e744.637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e53.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e11.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eVI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e524.764\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e42.512\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e11.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eVII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e440.381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e60.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e10.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e272.773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e46.603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eState\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e44.651.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e77.958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 605px;\"\u003e\n \u003cp\u003eGDP = Gross Domestic Product | *per 1000 live births | **\u0026nbsp;percentage of the population\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Table 2 summarizes the distribution of new training seats by AR before and after 2013. Statewide availability increased from 1.29 to 2.25 seats per 10,000 inhabitants, approximately 75% growth. However, this increase was uneven across regions. In contrast, AR VI and X, among the lowest GDP per capita, did not receive any new medical programs or seats during the expansion period. Despite substantial absolute growth in AR XV and XIII, the rates of seat availability per capita in these populous regions remained low. Conversely, one AR (V), with no medical schools in 2013, reached one of the highest seat densities per 10,000 inhabitants by 2025. These findings highlight persistent inequities despite the increase in training capacity.\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"bottom\" style=\"width: 671px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Administrative Regions of the State of S\u0026atilde;o Paulo, availability of medical schools, seats, and seats per 10,000 inhabitants, before and after 2013*.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eAdministrative Region\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eMedical Schools (2013)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eMedical Schools (2025)\u003c/p\u003e\n \u003cp\u003e(% increase)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSeats/10,000 inhabitants (2013)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eSeats/10,000 inhabitants (2025)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eSeats in 2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSeats in 2025\u003c/p\u003e\n \u003cp\u003e(% increase)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eXV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e22 (83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3912 (55.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eXIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e16 (120)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1629 (118.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eIX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e6 (200)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e500 (127.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eXVI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e4 (300)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e500 (316.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eXIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e5 (150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e480 (140)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e7 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e4.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e4.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e725 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eXI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e4 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e436 (21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e415\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eVIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e2 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e190 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e3 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e290 (26.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e3 (200)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e4.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e386 (75.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e173\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eXII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e2 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e166 (66)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eVI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eVII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e90 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eState\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e5661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e9892\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 671px;\"\u003e\n \u003cp\u003e*Year of implementation of the More Doctors Law\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 671px;\"\u003e\n \u003cp\u003e**Total undergraduate medical seats per 10,000 inhabitants in March 2025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Characteristics and Performance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the 80 medical schools active in S\u0026atilde;o Paulo State, only 55 had assigned CPC and ENADE indicators in the 2023 national evaluation cycle, reflecting the absence of graduating cohorts in newer programs. Public institutions consistently achieved CPC scores above 3.0 and were predominantly among those with more than 30 years of operation. Private and municipal institutions showed greater dispersion and were more frequently concentrated in lower CPC ranges (Figure 3; Table 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFederal and state public medical schools also achieved the highest average student performance scores, measured by the continuous ENADE score (4.34 \u0026plusmn; 0.36), with significant differences compared to all other administrative categories (p = 0.0018). Both general and specific components of ENADE showed the same trends (Table 3). In contrast, federal and state institutions presented lower average scores in the domains of Didactic-Pedagogical Organization and Infrastructure (p=0.04) and Physical Facilities (p=0.04), according to student perceptions, when compared to private institutions.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"680\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 680px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eComparison of the Program Score Descriptors (standardized) and Institutional Age by Administrative Type among Medical Schools in the State of S\u0026atilde;o Paulo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 113px;\"\u003e\n \u003cp\u003eVariable (Mean \u0026plusmn; Standard Deviation)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFederal + State\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrivate For-Profit\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrivate Nonprofit\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Municipal \u0026amp; Religious\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOTAL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 57px;\"\u003e\n \u003cp\u003eP-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e(N=6)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e(N=14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e(N=25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e(N=10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e(N=55)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eInstitution Age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;58.17 \u0026plusmn; 21.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e15.64 \u0026plusmn; 13.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e23.20 \u0026plusmn; 19.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e34.10 \u0026plusmn; 26.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e27.07 \u0026plusmn; 22.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.0050\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e*CPC (Continuous)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3.63 \u0026plusmn; 0.32\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;2.79 \u0026plusmn; 0.73\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.88 \u0026plusmn; 0.88\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.60 \u0026plusmn; 0.74\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e2.89 \u0026plusmn; 0.81 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.0908\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eEnade Score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e4.34 \u0026plusmn; 0.36\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.10 \u0026plusmn; 0.94\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.58 \u0026plusmn; 1.27\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;2.89 \u0026plusmn; 1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e2.70 \u0026plusmn; 1.24\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.0018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eEnade General Component\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e4.32 \u0026plusmn; 0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.93 \u0026plusmn; 0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.53 \u0026plusmn; 1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.78 \u0026plusmn; 0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e2.62 \u0026plusmn; 1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eEnade Specific Components\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e4.35 \u0026plusmn; 0.38 \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;2.15 \u0026plusmn; 1.06\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;2.59 \u0026plusmn; 1.39 \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.92 \u0026plusmn; 1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e2.73 \u0026plusmn; 1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.0052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eDidactic-Pedagogical Organization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;2.69 \u0026plusmn; 0.46\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.77 \u0026plusmn; 0.76\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.77 \u0026plusmn; 0.96\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3.53 \u0026plusmn; 1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e3.61 \u0026plusmn; 0.94\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.0379\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eInfrastructure and Physical Facilities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;2.61 \u0026plusmn; 0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.88 \u0026plusmn; 0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.78 \u0026plusmn; 0.97\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3.70 \u0026plusmn; 1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e3.66 \u0026plusmn; 1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.0393\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eOpportunities for Academic Development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2.88 \u0026plusmn; 0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.46 \u0026plusmn; 0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.35 \u0026plusmn; 1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3.25 \u0026plusmn; 1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;3.31 \u0026plusmn; 1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.6175\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"bottom\" style=\"width: 680px;\"\u003e\n \u003cp\u003e*Course Score (CPC) | All scores range from 0 to 5.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eStudent Performance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudent performance distributions by administrative category and institutional age are shown in Figure 4. Federal and state public institutions achieved mean ENADE scores close to or above 4.0, while private and municipal institutions exhibited greater variability, with almost half scoring below 4.0.\u003c/p\u003e\n\u003cp\u003eInstitutions operating for more than 30 years demonstrated significantly higher average ENADE scores compared with programs up to 10 years old and those with intermediate years of operation (3.52 \u0026plusmn; 1.07; p = 0.0015) (Table 4). This pattern was observed for both the general and specific - medical knowledge- components of student\u0026acute;s performance examination. When analysing separately the specific component, statistically significant differences were observed only between institutions older than 30 years and those up to 10 years (p = 0.0076). No statistically significant differences were identified across institutional age groups for Didactic-Pedagogical Organization, Infrastructure and Physical Facilities, Opportunities for Academic Development, or the summative continuous CPC score \u0026ndash; Table 4.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"706\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 706px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eComparison of Course Score (CPC) Descriptors by Institutional Age Range among Medical Schools in the State of S\u0026atilde;o Paulo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 177px;\"\u003e\n \u003cp\u003eVariable\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026le; 10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e11\u0026ndash;30 years (N=19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026gt; 30 years (N=17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eTOTAL (N=55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003eN=19\u003c/p\u003e\n \u003cp\u003eMean (\u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003eMean (\u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eMean (\u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eMean (\u0026plusmn; SD)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eP-Value\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eEnade Score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2.06 \u0026plusmn; 1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;2.62 \u0026plusmn; 0.91\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.52 \u0026plusmn; 1.07\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;2.70 \u0026plusmn; 1.24\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.0015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eEnade General Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1.99 \u0026plusmn; 0.95\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2.39 \u0026plusmn; 0.91\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.58 \u0026plusmn; 1.03\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.62 \u0026plusmn; 1.16\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eEnade Specific Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2.08 \u0026plusmn; 1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2.70 \u0026plusmn; 0.98\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.50 \u0026plusmn; 1.11\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.73 \u0026plusmn; 1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.0076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eDidactic-Pedagogical Organization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3.70 \u0026plusmn; 0.87\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3.84 \u0026plusmn; 0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.26 \u0026plusmn; 1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;3.61 \u0026plusmn; 0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.1640\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eInfrastructure and Physical Facilities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3.78 \u0026plusmn; 0.86\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3.87 \u0026plusmn; 1.01 \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.31 \u0026plusmn; 1.09\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;3.66 \u0026plusmn; 1.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.1908\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eOpportunities for Academic Development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3.04 \u0026plusmn; 1.22\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3.46 \u0026plusmn; 1.19\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;3.44 \u0026plusmn; 1.06\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.31 \u0026plusmn; 1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.4882\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003e*CPC\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;2.68 \u0026plusmn; 0.99 \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2.91 \u0026plusmn; 0.62 \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.09 \u0026plusmn; 0.76 \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp; 2.89 \u0026plusmn; 0.81 \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.2535\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"bottom\" style=\"width: 706px;\"\u003e\n \u003cp\u003e\u0026sup1; Kruskal\u0026ndash;Wallis Test | * Course Score (CPC) | All scores range from 0 to 5.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMultivariate analyses using generalized linear models confirmed that institutional age and administrative category remained independently associated with student and school performance. Programs operating for more than 30 years achieved higher ENADE scores than those with up to 10 years of operation (p = 0.0097), and federal or state public institutions performed significantly better than municipal or religious (p = 0.0287), for-profit private (p = 0.0021), and nonprofit private (p = 0.0088) institutions. No variables showed statistically significant associations with the summative CPC score.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe expansion of medical schools in the region, following the implementation of the More Doctors Program, resulted in a substantial increase in training capacity, largely driven by private institutions and concentrated in regions with stronger infrastructure, better social indicators, and higher economic development. In contrast, the most underserved regions did not receive new medical programs. These findings indicate that the Brazilian National policy aiming to stimulate medical training in priority and underserved areas was not reached in the most populous and economically developed state. This pattern mirrors national trends, with limited expansion in regions with lower socioeconomic development, fragile academic structures, and insufficient health-service capacity\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe selective and uneven expansion observed across S\u0026atilde;o Paulo State further illustrates how market-driven growth tends to reinforce pre-existing territorial disparities. It is also important to highlight that rapid expansion risks exceeding the capacity required for adequate training clinical spaces in the health system, qualified supervision, risking competency development of trainees. The present findings also demonstrate that medical schools with longer institutional trajectories tend to achieve better educational outcomes, particularly in student performance measures, corroborating previous national studies\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Most newer institutions \u0026mdash; predominantly private \u0026mdash; have not yet reached comparable levels of performance, reinforcing concerns that rapid expansion may compromise educational quality in the absence of sufficient institutional maturation.\u003c/p\u003e \u003cp\u003eConcerns about shortages in medical specialties have recently motivated a new federal initiative, \u0026ldquo;Now We Have Specialists\u0026rdquo;, which aims to expand access to high-demand specialties through limited increases in training positions and larger incentives for private-sector participation\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. However, evidence suggests that physician retention in underserved areas depends on multiple, interrelated factors, including the location of specialty training\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e and broader perceptions of quality of life for professionals and their families\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. It therefore remains uncertain whether this strategy will improve equitable access to specialized care or further strengthen private-sector control over service provision.\u003c/p\u003e \u003cp\u003eInterestingly, federal and state public institutions, despite achieving higher student performance, received lower ratings in domains related to didactic-pedagogical organization and infrastructure. This apparent paradox may reflect the strong critical thinking and academic attitude of students under a selective admission processes characteristic of public universities, alongside structural constraints such as limited funding, bureaucratic rigidity, and reduced managerial flexibility\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In contrast, private institutions\u0026mdash;especially for-profit ones\u0026mdash;often demonstrate greater capacity for infrastructure investment without reaching equivalent academic outcomes. This divergence raises broader questions about how market-driven logic shapes educational quality and the preparation of doctors aligned with the values and premises of the public health systems\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study has important limitations. Its cross-sectional design precludes causal inference, and the use of secondary administrative data may involve reporting inconsistencies. The analysis did not include qualitative dimensions of training, a deeper analysis of physician distribution, nor direct measures of professional competence or quality of care. It also does not focus on impact of expansion on health indictors, a difficulty outcome to assess due to multiple confounding variables. Additionally, as the focus was limited to a wealthy jurisdiction, the findings may not be fully generalizable to less developed regions.\u003c/p\u003e \u003cp\u003eAnother central issue concerns the reliance on regulatory indicators such as ENADE and CPC as indirect measures of educational quality. While these instruments are valuable for system-level monitoring and policy guidance, they provide only partial assessments of quality and may inadequately capture institutional weaknesses or strengths\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Moreover, student performance evaluations carry the risk of incentivizing teaching practices oriented toward test preparation rather than comprehensive, clinically grounded, and transformative education. A comprehensive evaluation of medical education requires integration of multiple dimensions. Accreditation frameworks based on global standards, such as those of the World Federation for Medical Education (WFME) adapted to local contexts, remain key benchmarks for quality and international legitimacy\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. In Brazil, the Sistema de Acredita\u0026ccedil;\u0026atilde;o de Escolas M\u0026eacute;dicas (SAEME), recognized by the WFME, provides a voluntary external evaluation process, though it lacks regulatory authority\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. As of 2024, only 76 schools had undergone voluntary evaluation, with 72.4% receiving accreditation\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAt the same time, international trends increasingly emphasize learning outcomes assessed through national licensing examinations\u0026mdash;such as the United Kingdom\u0026rsquo;s Medical Licensing Assessment\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e \u0026mdash; or through longitudinal, programmatic assessment models\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e incorporating multiple sources of evidence, including Entrustable Professional Activities (EPAs)\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Although high-stakes examinations ensure minimum competence, their limitations in assessing attitudinal, ethical, and professional dimensions of practice are well recognized\u003csup\u003e\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Brazil\u0026rsquo;s evaluation landscape is currently evolving with the recent implementation of the National Medical Assessment Exam (ENAMED), designed to assess students at stages of training, before entry into interniship training due in 5th and 6th year\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. This initiative aligns Brazil with international models of progressive assessment, although its current format is focused on cognitive skills.\u003c/p\u003e \u003cp\u003eTaken together, these findings underscore the limits of market-driven expansion in addressing territorial inequities and sustaining educational quality. Effective workforce planning requires integrated strategies encompassing undergraduate education, residency training, working conditions, and broader intersectorial policies aligned with the organizational capacity of the health system in place. The territory under study \u0026mdash; whose demographic and economic characteristics resemble those of middle-high income settings\u0026mdash; illustrates challenges that are highly relevant internationally, reinforcing the need for regulatory frameworks that balance expansion with quality, accountability, and social mission.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThe expansion of medical schools in S\u0026atilde;o Paulo State following the 2013 national policy produced substantial quantitative growth, largely driven by private institutions and concentrated in regions with higher socioeconomic development and more robust healthcare infrastructure. Consequently, the central policy objective of reducing territorial inequalities in medical training was not achieved in the country\u0026rsquo;s most populous and economically developed state, highlighting the limits of market-oriented expansion strategies in addressing inequitable access.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdministrative Region\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCAAE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCertificate of Presentation for Ethical Review\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCPC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePreliminary Course Concept\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDCN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Curricular Guidelines\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGDP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGross Domestic Product\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIBGE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBrazilian Institute of Geography and Statistics\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIGC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSP\u0026ndash;S\u0026atilde;o Paulo Geographic and Cartographic Institute\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eINEP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Institute for Educational Studies and Research\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMEC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMinistry of Education\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePITS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgram for the Decentralization of Health Work\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePROVAB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgram for the Valorization of Primary Care Professionals\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eREUNI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgram for the Support to Restructure and Expansion of Federal Universities\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSEADE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eState System for Data Analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSUS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnified Health System\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproved by the Research Ethics Committee of School of Medical Sciences, University of Campinas (Unicamp) under protocol CAAE 90115225.0.0000.5404.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data are publicly available from the e-MEC system (https://emec.mec.gov.br) and SEADE Foundation databases (https://painel.seade.gov.br/saude/).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGF collected, analyzed, and interpreted data and drafted the manuscript. EA supervised the study, contributed to conceptualization, and critically reviewed the manuscript. DM supervised the study, contributed to conceptualization, and critically reviewed the manuscript. All authors read and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Coordination for the Improvement of Higher Education Personnel (CAPES) – Brazil – Funding Code 001.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGuilherme Frayha, MD is a master’s student in Health Professions Education at the School of Medical Sciences, University of Campinas (Unicamp), Brazil. ORCID: 0009-0005-9561-5052.\u003c/p\u003e\n\u003cp\u003eEliana Amaral, MD, PhD is Full Professor at the Department of Obstetrics \u0026amp; Gynecology at the School of Medical Sciences, University of Campinas (UNICAMP). ORCID: 0000-0001-9151-3108.\u003c/p\u003e\n\u003cp\u003eDanette McKinley, PhD, is Senior Analyst at the Foundation for International Medical Education and Research (FAIMER), a division of Intealth, United States. ORCID: 0000-0002-8709-0365.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLorkowski J, Jugowicz A. Shortage of Physicians: A Critical Review. Adv Exp Med Biol. 2021;1324:57-62. doi: 10.1007/5584_2020_601. PMID: 33346901.\u003c/li\u003e\n\u003cli\u003eHerrick C, Armstrong D. How many doctors does a health system need? Histories of workforce planning in the NHS. Soc Sci Med. 2025 Apr;371:117882. doi: 10.1016/j.socscimed.2025.117882. Epub 2025 Feb 24. PMID: 40054388.\u003c/li\u003e\n\u003cli\u003eCrisp N, Chen L. Global supply of health professionals. N Engl J Med. 2014;370(10):950-7. doi:10.1056/NEJMra1111610.\u003c/li\u003e\n\u003cli\u003eFigueiredo, A.M., McKinley, D.W., Massuda, A. et al. Evaluating medical education regulation changes in Brazil: workforce impact. Hum Resour Health 19, 33 (2021). https://doi.org/10.1186/s12960-021-00580-5\u003c/li\u003e\n\u003cli\u003eBrasil. Lei n\u0026ordm; 12.871, de 22 de outubro de 2013. Institui o Programa Mais M\u0026eacute;dicos. Di\u0026aacute;rio Oficial da Uni\u0026atilde;o. 2013 out 23.\u003c/li\u003e\n\u003cli\u003eScheffer M, et al. Demografia m\u0026eacute;dica no Brasil 2025. Bras\u0026iacute;lia (DF): Minist\u0026eacute;rio da Sa\u0026uacute;de; 2025. ISBN: 978-65-5993-754-7. Available from: http://bvsms.saude.gov.br/bvs/publicacoes/demografia_medica_brasil_2025.pdf\u003c/li\u003e\n\u003cli\u003eFigueiredo AM, McKinley DW, Lima KC, Azevedo GD. Medical school expansion policies: educational access and physician distribution. Med Educ. 2019 Nov;53(11):1121-1131. doi: 10.1111/medu.13941. Epub 2019 Aug 16. PMID: 31418478. \u003c/li\u003e\n\u003cli\u003eScheffer M, Mosquera P, Cassenote A, et al. 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Available from: https://download.inep.gov.br/educacao_superior/indicadores/resultados/2023/CPC_2023.xlsx\u003c/li\u003e\n\u003cli\u003eGuimar\u0026atilde;es, R.A., de Fran\u0026ccedil;a e Silva, A.L.G., de Souza, M.R. et al. Trend and spatial clustering of medical education in Brazil: an ecological study of time series from 2010 to 2021. BMC Health Serv Res 23, 882 (2023). https://doi.org/10.1186/s12913-023-09795-9\u003c/li\u003e\n\u003cli\u003eOliveira FP, Mota JAC, Almeida RBF, Silva AB. Lessons learned from the expansion of medical schools in Brazil. Front Educ. 2024;8:1494445. doi: 10.3389/feduc.2024.1494445\u003c/li\u003e\n\u003cli\u003eBrasil. Medida Provis\u0026oacute;ria n\u0026ordm; 1.301. Institui o Programa Agora Tem Especialistas. Di\u0026aacute;rio Oficial da Uni\u0026atilde;o, Bras\u0026iacute;lia (DF), 30 de maio de 2025.\u003c/li\u003e\n\u003cli\u003eKoike, S., Okazaki, K., Tokinobu, A. et al. 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Expans\u0026atilde;o e privatiza\u0026ccedil;\u0026atilde;o dos cursos de medicina e a integra\u0026ccedil;\u0026atilde;o ensino-servi\u0026ccedil;o: o caso do estado de Pernambuco. Sa\u0026uacute;de Debate. 2023 Abr-Jun;47(137):182-195. doi:10.1590/0103-1104202313713\u003c/li\u003e\n\u003cli\u003ePereira CA, Araujo JFFE, Machado-Taylor ML. The Brazilian higher education evaluation model: \u0026ldquo;SINAES\u0026rdquo; sui generis? Int J Educ Dev. 2018;61:5-15. doi:10.1016/j.ijedudev.2017.11.007.\u003c/li\u003e\n\u003cli\u003eWorld Federation for Medical Education. WFME Global Standards for Quality Improvement: Basic Medical Education. 2020 revision. Ferney-Voltaire: WFME; 2020.\u003c/li\u003e\n\u003cli\u003eSistema de Acredita\u0026ccedil;\u0026atilde;o de Escolas M\u0026eacute;dicas. [Internet]. [citado em 2025 set 28]. Dispon\u0026iacute;vel em: https://www.saeme.org.br/\u003c/li\u003e\n\u003cli\u003eTempski P, Girotto LC, Brenelli S, Giamberardino DD, Martins MA. 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Institui o Exame Nacional de Avalia\u0026ccedil;\u0026atilde;o da Forma\u0026ccedil;\u0026atilde;o M\u0026eacute;dica \u0026ndash; Enamed. Di\u0026aacute;rio Oficial da Uni\u0026atilde;o. 2025 abr 24;Se\u0026ccedil;\u0026atilde;o 1:119.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Medical Education, Public Policy, Health Workforce, Medical Schools, Social accountability","lastPublishedDoi":"10.21203/rs.3.rs-8622396/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8622396/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe rapid expansion of medical schools has been widely adopted as a strategy to address physician shortages and improve access to healthcare. In Brazil, a national policy implemented in 2013 substantially increased medical training capacity, largely through private-sector participation. However, concerns persist regarding whether rapid expansion improved access for students and patients while sustains educational quality. S\u0026atilde;o Paulo is the most populous and economically developed state in Brazil, with structural, regulatory, and market characteristics comparable to those observed in middle- and high-income countries. This offers an informative analytical case to examine the effects of large-scale medical school expansion in a complex health professions education market.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis observational, descriptive, cross-sectional study analysed all active undergraduate medical programs registered in the Ministry of Education\u0026rsquo;s e-MEC system in S\u0026atilde;o Paulo State between 2013 and March 2025. Expansion patterns, geographic distribution, and regional socioeconomic characteristics were assessed using publicly available administrative data. Educational performance was evaluated using official data, the National Student Performance Exam (ENADE 2023) and the Preliminary Course Concept (CPC). Descriptive statistics and non-parametric tests were applied for group comparisons. Multivariate generalized linear models were used to assess associations between institutional characteristics and student performance.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eBetween 2013 and 2025, 42 new medical programs were authorized, resulting in a 74.7% increase in available training seats. Expansion was predominantly driven by private institutions, which accounted for 80.5% of newly authorized seats, and was spatially concentrated in regions with higher socioeconomic development and stronger healthcare infrastructure. Regions with lower development indicators experienced little or no expansion. Medical schools with further from their establishment date and public ownership achieved significantly higher student performance scores, whereas newer, predominantly private institutions showed greater variability. Although public institutions demonstrated stronger student performance, they received lower ratings in infrastructure and didactic\u0026ndash;pedagogical organization. In multivariate analyses, institutional age and ownership remained independently associated with student performance, while no variables showed significant associations with the overall institutional performance score.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe expansion of medical education in S\u0026atilde;o Paulo State produced substantial quantitative growth but failed to reduce territorial inequalities. Educational quality was more strongly associated with institutional maturity and public ownership than with expansion alone. As an analytical case reflecting dynamics seen in other regulated health education systems, our example highlights the limits of market-driven expansion and underscores the need for integrated policies that align growth with quality assurance, accreditation, and workforce retention strategies to promote equitable and sustainable healthcare access.\u003c/p\u003e","manuscriptTitle":"Performance of Medical Schools and Students in a Rapid Expansion Era: A Cross-sectional Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-22 14:57:48","doi":"10.21203/rs.3.rs-8622396/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-03-18T00:13:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-02T01:02:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-02T01:01:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2026-01-16T22:11:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"38206a4c-9112-45b1-b486-393d6ab60ce6","owner":[],"postedDate":"March 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-22T14:57:48+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-22 14:57:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8622396","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8622396","identity":"rs-8622396","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}