Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Modelo de Previsão de Readmissão Hospitalar× | Modelo de Ocupação de Leitos Hospitalares× | |
|---|---|---|
| Área | Gestão em saúde | Gestão em saúde |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 1998 | 2000 |
| Autor original≠ | Healthcare data analytics and outcomes research | Healthcare operations researchers |
| Tipo≠ | Logistic regression and machine learning methodology | Stochastic simulation and time-series forecasting |
| Fonte seminal≠ | Jencks, S. F., Williams, M. V., & Coleman, E. A. (2009). Rehospitalizations among patients in the Medicare fee-for-service program. New England Journal of Medicine, 360(14), 1418–1428. DOI ↗ | Tikk, D., Kóczy, L. T., & Gedeon, T. D. (2003). A survey on fuzzy relational equations and their applications in web intelligence. In W. Pedrycz (Ed.), Handbook of Granular Computing (pp. 521–542). John Wiley & Sons. link ↗ |
| Outros nomes | Readmission Risk Prediction, Hospital Readmission Forecasting | Bed Occupancy Forecasting, Hospital Census Prediction |
| Relacionados | 5 | 5 |
| Resumo≠ | Hospital readmission prediction models use statistical and machine learning techniques to identify patients at high risk of returning to the hospital shortly after discharge. These models guide targeted discharge planning and follow-up to improve outcomes and reduce costs. | Hospital bed occupancy models forecast the number of occupied beds at future times by analyzing admission patterns, length of stay distributions, and discharge dynamics. These models support tactical decisions about staffing, supply chain management, and strategic decisions about capacity expansion. |
| ScholarGateConjunto de dados ↗ |
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