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J Rural Health ; 34(1): 103-108, 2018 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-27273735

RESUMO

PURPOSE: Considering the high prevalence of heart failure and the economic burden of the disease, factors that influence in-hospital mortality are of importance in improving outcomes of care for this patient population. The purpose of this study was to examine the determinants of in-hospital mortality for adult heart failure patients. METHODS: The study design is a retrospective observational study design using the 2010 Nebraska Hospital Discharge data set including 4,319 hospitalizations for 3,521 heart failure patients admitted to 79 hospitals in Nebraska. Hierarchical logistic regression models including patient- and hospital-specific random intercepts were analyzed. Covariates included in the analysis were patient age in years, gender, comorbidity status, length of stay, primary payer, type and source of admission, transfers, and rurality of county of residence. RESULTS: Overall, 3.5% of heart failure patients died during their hospital stay. In logistic regression analysis that adjusted for age, sex, and comorbidities, the odds of dying in hospital for heart failure patients increased with age (OR = 1.03, 95% CI: 1.01-1.04), co-morbidity (OR = 1.15; 95% CI: 1.05-1.25) and length of stay (OR = 1.03, 95% CI: 1.01-1.05). The patient's gender, payer source, rurality of county of residence, source, and type of admission were not risk factors for in-hospital death. CONCLUSION: Increasing age, comorbidity and length of stay were risk factors for in-hospital death for heart failure. An understanding of the risk factors for in-hospital death is critical to improving outcomes of care for heart failure patients.


Assuntos
Insuficiência Cardíaca/mortalidade , Mortalidade Hospitalar/tendências , Admissão do Paciente/estatística & dados numéricos , População Rural/estatística & dados numéricos , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Insuficiência Cardíaca/epidemiologia , Hospitalização , Humanos , Cobertura do Seguro/estatística & dados numéricos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Nebraska , Razão de Chances , Estudos Retrospectivos , Fatores de Risco
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