Use of Real-Time Information to Predict Future Arrivals in the Emergency Department.

Hu, Yue; Cato, Kenrick D; Chan, Carri W; Dong, Jing; Gavin, Nicholas; Rossetti, Sarah C; Chang, Bernard P

Hu, Yue; Cato, Kenrick D; Chan, Carri W; Dong, Jing; Gavin, Nicholas; Rossetti, Sarah C; Chang, Bernard P.

Afiliação

Hu Y; Decision, Risk, and Operations Division, Columbia Business School, New York, NY. Electronic address: yh2987@columbia.edu.
Cato KD; School of Nursing, Columbia University, New York, NY; Office of Nursing Research, EBP, and Innovation, New York-Presbyterian Hospital, New York, NY; Department of Emergency Medicine, New York, NY.
Chan CW; Decision, Risk, and Operations Division, Columbia Business School, New York, NY.
Dong J; Decision, Risk, and Operations Division, Columbia Business School, New York, NY.
Gavin N; Department of Emergency Medicine, New York, NY.
Rossetti SC; School of Nursing, Columbia University, New York, NY; Department of Biomedical Informatics, Columbia University, New York, NY, USA.
Chang BP; Department of Emergency Medicine, New York, NY.

Ann Emerg Med ; 81(6): 728-737, 2023 06.

Article em En | MEDLINE | ID: mdl-36669911

Assuntos

Serviço Hospitalar de Emergência; Humanos; Estudos Retrospectivos; Modelos Lineares; Fatores de Tempo; Previsões

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Serviço Hospitalar de Emergência Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Ann Emerg Med Ano de publicação: 2023 Tipo de documento: Article

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