Predictors of readmission and long length of stay in elders admitted with neurological disorders in a tertiary center: a real-world investigation

ABSTRACT Hospital readmission and long length of stay (LOS) increase morbidity and hospital mortality and are associated with excessive costs to health systems. Objective: This study aimed to identify predictors of hospital readmission and long LOS among elders with neurological disorders (NDs). Methods: Patients ≥ 60 years of age admitted to the hospital between January 1, 2009, and December 31, 2010, with acute NDs, chronic NDs as underpinnings of acute clinical disorders, and neurological complications of other diseases were studied. We analyzed demographic factors, NDs, and comorbidities as independent predictors of readmission and long LOS (≥ 9 days). Logistic regression was performed for multivariate analysis. Results: Overall, 1,154 NDs and 2,679 comorbidities were identified among 798 inpatients aged ≥ 60 years (mean 75.8 ± 9.1). Of the patients, 54.5% were female. Patient readmissions were 251(31%) and 409 patients (51%) had an LOS ≥ 9 days (95% confidence interval 48%–55%). We found no predictors for readmission. Low socioeconomic class (p = 0.001), respiratory disorder (p < 0.001), infection (p < 0.001), genitourinary disorder (p < 0.033), and arterial hypertension (p = 0.002) were predictors of long LOS. Identified risks of long LOS explained 22% of predictors. Conclusions: Identifying risk factors for patient readmission are challenges for neurology teams and health system stakeholders. As low socioeconomic class and four comorbidities, but no NDs, were identified as predictors for long LOS, we recommend studying patient multimorbidity as well as functional and cognitive scores to determine whether they improve the risk model of long LOS in this population.

Bibliographic Details

Main Authors:	Bacellar,Aroldo, Pedreira,Bruno B., Costa,Gersonita, Assis,Telma, Lobo,Camila, Nascimento,Osvaldo
Format:	Digital revista
Language:	English
Published:	Academia Brasileira de Neurologia - ABNEURO 2019
Online Access:	http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0004-282X2019000500321
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