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Data Mining and Analytics in Healthcare Management

Applications and Tools

David L. Olson, Özgür M. Araz

PDF
ca. 96,29
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Springer Nature Switzerland img Link Publisher

Sozialwissenschaften, Recht, Wirtschaft / Einzelne Wirtschaftszweige, Branchen

Beschreibung

This book presents data mining methods in the field of healthcare management in a practical way. Healthcare quality and disease prevention are essential in today’s world. Healthcare management faces a number of challenges, e.g. reducing patient growth through disease prevention, stopping or slowing disease progression, and reducing healthcare costs while improving quality of care. The book provides an overview of current healthcare management problems and highlights how analytics and knowledge management have been used to better cope with them. It then demonstrates how to use descriptive and predictive analytics tools to help address these challenges. In closing, it presents applications of software solutions in the context of healthcare management.

Given its scope, the book will appeal to a broad readership, from researchers and students in the operations research and management field to practitioners such as data analysts and decision-makers who work in the healthcare sector.


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Schlagwörter

Descriptive data mining, Data visualizaiton, Business Analytics, Prescriptive data mining, Forecasting, Multicriteria decision making, Decision analysis, Healthcare analytics, Cluster analysis, Classification models, Association rules