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.

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 en En | MEDLINE | ID: mdl-36981600

Asunto(s)

Atención Ambulatoria; Ciencia de los Datos; Humanos; Factores de Riesgo; Medición de Riesgo; Hospitalización

Palabras clave

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 Banco de datos: MEDLINE Asunto principal: Atención Ambulatoria / Ciencia de los Datos Tipo de estudio: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2023 Tipo del documento: Article

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