Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New.
Language: English
Published by Taylor & Francis Ltd, London, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
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Hardcover. Condition: new. Hardcover. Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges uniquely posed by this problem.Key Features:Introduces basic elements of health care data, especially for administrative claims data, including disease code, procedure codes, and drug codesProvides tailored supervised and unsupervised machine learning approaches for understanding and predicting the high utilizersPresents descriptive data driven methods for the high utilizer populationIdentifies a best-fitting linear and tree-based regression model to account for patients acute and chronic condition loads and demographic characteristics This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges posed by this problem. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition.
Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
US$ 240.82
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Add to basketCondition: As New. Unread book in perfect condition.
Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Seller: Majestic Books, Hounslow, United Kingdom
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Add to basketCondition: New.
Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. 1st edition NO-PA16APR2015-KAP.
Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Language: English
Published by Taylor & Francis Ltd, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
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Add to basketCondition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
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Add to basketHardcover. Condition: Brand New. 107 pages. 10.00x7.25x0.50 inches. In Stock.
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Add to basketCondition: New. Chengliang Yang, Department of Computer Science, University of Florida Chris Delcher, Institute of Child Health Policy, University of Florida Elizabeth Shenkman, Institute of Child Health Policy, University of Florida Sanjay Ranka, Depar.
Language: English
Published by Taylor & Francis Ltd, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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Add to basketHardback. Condition: New. New copy - Usually dispatched within 4 working days.
Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Seller: Biblios, Frankfurt am main, HESSE, Germany
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Language: English
Published by Taylor & Francis Ltd Okt 2019, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Neuware.
Language: English
Published by Taylor & Francis Ltd, London, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Seller: AussieBookSeller, Truganina, VIC, Australia
Hardcover. Condition: new. Hardcover. Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges uniquely posed by this problem.Key Features:Introduces basic elements of health care data, especially for administrative claims data, including disease code, procedure codes, and drug codesProvides tailored supervised and unsupervised machine learning approaches for understanding and predicting the high utilizersPresents descriptive data driven methods for the high utilizer populationIdentifies a best-fitting linear and tree-based regression model to account for patients acute and chronic condition loads and demographic characteristics This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges posed by this problem. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.