Identification of elderly patients at risk for 30-day readmission: Clinical insight beyond big data prediction.

Flaks-Manov, Natalie; Shadmi, Efrat; Yahalom, Rina; Perry-Mezre, Henia; Balicer, Ran D; Srulovici, Einav

Flaks-Manov, Natalie; Shadmi, Efrat; Yahalom, Rina; Perry-Mezre, Henia; Balicer, Ran D; Srulovici, Einav.

Afiliação

Flaks-Manov N; Institute for Computational Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Shadmi E; Cheryl Spencer Department of Nursing, University of Haifa, Haifa, Israel.
Yahalom R; Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel.
Perry-Mezre H; Cheryl Spencer Department of Nursing, University of Haifa, Haifa, Israel.
Balicer RD; Hospital Division, Clalit Health Services, Tel Aviv, Israel.
Srulovici E; Hospital Division, Clalit Health Services, Tel Aviv, Israel.

J Nurs Manag ; 30(8): 3743-3753, 2022 Nov.

Article em En | MEDLINE | ID: mdl-34661943

Assuntos

Big Data; Readmissão do Paciente; Humanos; Idoso; Estudos Prospectivos; Medição de Risco; Pacientes

Palavras-chave

automated readmission predictive model; decision trees; nurses' and physicians' assessments

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Readmissão do Paciente / Big Data Tipo de estudo: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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