Big Data Analytics to Reduce Preventable Hospitalizations-Using Real-World Data to Predict Ambulatory Care-Sensitive Conditions.

Schulte, Timo; Wurz, Tillmann; Groene, Oliver; Bohnet-Joschko, Sabine

Schulte, Timo; Wurz, Tillmann; Groene, Oliver; Bohnet-Joschko, Sabine.

Afiliação

Schulte T; Faculty of Management, Economics and Society, Witten/Herdecke University, 58455 Witten, Germany.
Wurz T; Faculty of Health, Witten/Herdecke University, 58455 Witten, Germany.
Groene O; Department of Business Analytics, Clinics of Maerkischer Kreis, 58515 Luedenscheid, Germany.
Bohnet-Joschko S; Department of Project and Change Management, University Clinic Hamburg-Eppendorf, 20251 Hamburg, Germany.

Int J Environ Res Public Health ; 20(6)2023 03 07.

Article em En | MEDLINE | ID: mdl-36981600

Assuntos

Assistência Ambulatorial; Ciência de Dados; Humanos; Fatores de Risco; Medição de Risco; Hospitalização

Palavras-chave

ambulatory care-sensitive conditions; claims data; hospitalization; integrated care; machine learning; population health; prediction model; prevention; real-world evidence

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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