RESUMO
Models for situations where some individuals are long-term survivors, immune or non-susceptible to the event of interest, are extensively studied in biomedical research. Fitting a regression can be problematic in situations involving small sample sizes with high censoring rate, since the maximum likelihood estimates of some coefficients may be infinity. This phenomenon is called monotone likelihood, and it occurs in the presence of many categorical covariates, especially when one covariate level is not associated with any failure (in survival analysis) or when a categorical covariate perfectly predicts a binary response (in the logistic regression). A well known solution is an adaptation of the Firth method, originally created to reduce the estimation bias. The method provides a finite estimate by penalizing the likelihood function. Bias correction in the mixture cure model is a topic rarely discussed in the literature and it configures a central contribution of this work. In order to handle this point in such context, we propose to derive the adjusted score function based on the Firth method. An extensive Monte Carlo simulation study indicates good inference performance for the penalized maximum likelihood estimates. The analysis is illustrated through a real application involving patients with melanoma assisted at the Hospital das Clínicas/UFMG in Brazil. This is a relatively novel data set affected by the monotone likelihood issue and containing cured individuals.
Assuntos
Funções Verossimilhança , Análise de Sobrevida , Algoritmos , Viés , Brasil , Humanos , MelanomaRESUMO
OBJECTIVE: To estimate the flow of professionals and the financial impact of the Programa Mais Médicos para o Brasil (PMMB - More Doctors for Brazil Program) within the More Doctors Program (MDP) for the Brazilian Ministry of Health and the participating municipalities of the state of São Paulo, from January 2019 to March 2022. METHODS: A financial impact study was conducted in the state of São Paulo based on public secondary databases. The number of PMMB vacancies per municipality, of physicians and vulnerability profiles were described to measure the loss of replacement of professionals in the period. RESULTS: In the specified period, the number of PMMB physicians in participating cities will decrease from 2,533 to 320, and the number of participating municipalities from 373 to 86. The municipalities that will need to replace the physicians will have a financial impact of R$ 929,487,904.77 (with sensitivity analysis, ranging from R$ 650,641,533.34 to R$ 1,208,334,276.20). CONCLUSION: The change of vulnerability methodology adopted for the PMMB will represent serious consequences, that is, less population assistance and high financial impact for the municipalities of the state of São Paulo in a scenario of budget limitations.
Assuntos
Educação Médica , Médicos , Brasil , Cidades , Educação Médica/economia , Humanos , Médicos/provisão & distribuição , Avaliação de Programas e Projetos de SaúdeRESUMO
ABSTRACT OBJECTIVE To estimate the flow of professionals and the financial impact of the Programa Mais Médicos para o Brasil (PMMB - More Doctors for Brazil Program) within the More Doctors Program (MDP) for the Brazilian Ministry of Health and the participating municipalities of the state of São Paulo, from January 2019 to March 2022. METHODS A financial impact study was conducted in the state of São Paulo based on public secondary databases. The number of PMMB vacancies per municipality, of physicians and vulnerability profiles were described to measure the loss of replacement of professionals in the period. RESULTS In the specified period, the number of PMMB physicians in participating cities will decrease from 2,533 to 320, and the number of participating municipalities from 373 to 86. The municipalities that will need to replace the physicians will have a financial impact of R$ 929,487,904.77 (with sensitivity analysis, ranging from R$ 650,641,533.34 to R$ 1,208,334,276.20). CONCLUSION The change of vulnerability methodology adopted for the PMMB will represent serious consequences, that is, less population assistance and high financial impact for the municipalities of the state of São Paulo in a scenario of budget limitations.
RESUMO OBJETIVO Calcular o fluxo de profissionais e o impacto financeiro do Projeto Mais Médicos para o Brasil (PMMB), dentro do Programa Mais Médicos (PMM), para o Ministério da Saúde e os municípios do estado de São Paulo aderentes, no período de janeiro de 2019 a março de 2022. MÉTODOS Realizou-se estudo de impacto financeiro a partir de bases de dados secundários públicos do estado de São Paulo. O número de vagas do PMMB por município, de médicos do projeto e os perfis de vulnerabilidade foram descritos para dimensionar a perda de reposição de profissionais no período. RESULTADOS No intervalo de tempo especificado, o número de médicos do PMMB em cidades a ele aderentes passará de 2.533 para 320, e o número de municípios participantes de 373 para 86. O impacto orçamentário para os municípios que necessitarão repor médicos será de R$ 929.487.904,77 (com análise de sensibilidade variando de R$ 650.641.533,34 a R$ 1.208.334.276,20). CONCLUSÃO A mudança de metodologia da vulnerabilidade adotada para o PMMB trará sérias consequências, ou seja, desassistência da população e alto impacto financeiro para os municípios do estado de São Paulo em um cenário de limitações orçamentárias.