Predictors of readmission and long length of stay in elders admitted with neurological disorders in a tertiary center: a real-world investigation
| Autor: | Osvaldo J. M. Nascimento, Camila Lobo, Telma Assis, Aroldo Bacellar, Bruno Bacellar Pedreira, Gersonita Costa |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Male
Multivariate analysis Neurology idoso Comorbidity Logistic regression fatores de risco Tertiary Care Centers Risk model 0302 clinical medicine Risk Factors Medicine risk factors 030212 general & internal medicine tempo de internação Aged 80 and over education.field_of_study aged Acute Disease Hypertension Female Readmissão do paciente Brazil medicine.medical_specialty nervous system diseases doenças do sistema nervoso multimorbidity Patient readmission Population Patient Readmission Statistics Nonparametric lcsh:RC321-571 03 medical and health sciences length of stay Internal medicine multimorbidade Humans education lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry Aged Retrospective Studies Hospital readmission business.industry Genitourinary system Length of Stay Confidence interval Logistic Models ROC Curve Multivariate Analysis Neurology (clinical) Nervous System Diseases business 030217 neurology & neurosurgery |
| Zdroj: | Arquivos de Neuro-Psiquiatria, Volume: 77, Issue: 5, Pages: 321-329, Published: 2019 Arquivos de Neuro-Psiquiatria v.77 n.5 2019 Arquivos de neuro-psiquiatria Academia Brasileira de Neurologia instacron:ABNEURO Arquivos de Neuro-Psiquiatria, Vol 77, Iss 5, Pp 321-329 |
| Popis: | 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. RESUMO Readmissão hospitalar e tempo longo de internação aumentam a morbidade, a mortalidade hospitalar e estão associados a custos excessivos para os sistemas de saúde. Objetivo: Este estudo almejou identificar preditores de readmissões hospitalares e longo tempo de internação (TDI) entre idosos com doenças neurológicas (DN). Métodos: Pacientes de idade ≥ 60 anos admitidos no hospital entre 1 de janeiro de 2009 e 31 de dezembro de 2010 com DN aguda, DN crônica subjacente a transtorno clínico agudo e complicações neurológicas de outras doenças foram estudados. Nos analisamos fatores demográficos, DN e comorbidades como preditores independentes de readmissão hospitalar e TDI (≥ 9 dias). Utilizamos regressão logística para analise multivariada. Resultados: Um total de 1154 DN e 2679 comorbidades foram identificadas entre 798 pacientes com idade ≥ 60 anos (media 75.8 ± 9.1). Desses pacientes 54.5% foram mulheres. Foram 251(31%) readmissões de pacientes e 409 (51%) dos pacientes tiveram um TDI≥9 dias (intervalo de confiança 95%, 48%–55%). Não encontramos preditores para readmissões. Baixa classe social (p = 0,001), distúrbio respiratório (p < 0,001), infecção (p < 0,001), distúrbio genito-urinário (p = 0,033) e hipertensão arterial (p = 0,002) foram os preditores de longo tempo de internação. Esses fatores de risco compõem 22% dos preditores para longo TDI. Conclusões: A identificação de fatores de risco para readmissão hospitalar é um desafio para equipes neurológicas e gestores dos sistemas de saúde. Conquanto baixa classe social e 4 comorbidades, todavia nenhuma DN, foram identificadas como preditoras para longo TDI nós recomendamos investigar multimorbidade, escores funcionais e cognitivos para saber se eles melhoram o modelo de risco para longo TDI nesta população. |
| Databáze: | OpenAIRE |
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