Factors associated with hospital mortality in Rio Grande do Sul SUS network in 2005 : application of a multilevel model

• Autor(a) principal: Gomes, Andrea Silveira
• Data de Publicação: 2010
• Outros Autores: Kluck, Mariza Machado, Fachel, Jandyra Maria Guimarães, Riboldi, João
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFRGS
• Texto Completo: http://hdl.handle.net/10183/30598
• topic: Estatística aplicada : Medicina; Modelo multinível; Hospital mortality.; Multilevel analysis; Multilevel logistic regression models; Quality care; Evaluation of health services; Unified Health System

Objective: To use a multilevel analysis methodology to evaluate hospital mortality from the data available in the Hospital Information System of the National Unified Health System. Methods: Cross-sectional study with data obtained from Authorization Forms for Hospital Admissions in Rio Grande do Sul, Brazil in 2005. The modeling was performed using multilevel logistic regression, with variables from the individual level (hospital admissions) and the context level (hospital profile). The variability originated from individual variables was analyzed as well as the participation of the profile of hospitals in the rate of hospital mortality. Results: The crude death rate calculated for all hospitals was 6.3%. The variables “Use of Intensive Care Unit” followed by “Patient Age” were the main predictors for hospital death at the individual level. The context variables that were related most closely to hospital death (outcome) were: size of hospital, legal nature, and average length of stay. The OR for deaths at large hospitals was 1.85 times the odds for small hospitals and the OR for medium hospitals was 1.69 times the odds for small ones. The chance of deaths in public hospitals was 67% higher than in private ones. Conclusions: The hospital profile has an important role in hospital mortality in the Hospital Information System of the National Unified Health System. Multilevel analysis should be used to estimate the contribution of the profile of mortality in hospitals.