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A01=Chengliang Yang
A01=Chris Delcher
A01=Elizabeth Shenkman
A01=Sanjay Ranka
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Age Group_Uncategorized
Author_Chengliang Yang
Author_Chris Delcher
Author_Elizabeth Shenkman
Author_Sanjay Ranka
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Data Driven Approaches for Healthcare: Machine learning for Identifying High Utilizers

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 codes
  • Provides tailored supervised and unsupervised machine learning approaches for understanding and predicting the high utilizers
  • Presents descriptive data driven methods for the high utilizer population
  • Identifies a best-fitting linear and tree-based regression model to account for patients acute and chronic condition loads and demographic characteristics
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    Current price €155.79
    Original price €163.99
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    A01=Chengliang YangA01=Chris DelcherA01=Elizabeth ShenkmanA01=Sanjay RankaAge Group_UncategorizedAuthor_Chengliang YangAuthor_Chris DelcherAuthor_Elizabeth ShenkmanAuthor_Sanjay Rankaautomatic-updateCategory1=Non-FictionCategory=MBPCategory=TJFMCategory=UBCategory=UBHCategory=UNCategory=UTFCategory=UYCategory=VCOP=United KingdomDelivery_Delivery within 10-20 working daysLanguage_EnglishPA=AvailablePrice_€100 and abovePS=Activesoftlaunch
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    Product Details
    • Weight: 850g
    • Dimensions: 178 x 254mm
    • Publication Date: 07 Oct 2019
    • Publisher: Taylor & Francis Ltd
    • Publication City/Country: United Kingdom
    • Language: English
    • ISBN13: 9780367342906

    About Chengliang YangChris DelcherElizabeth ShenkmanSanjay Ranka

    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 Department of Computer Science University of Florida.

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