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Data Driven Approaches for Healthcare Chengliang Yang

Data Driven Approaches for Healthcare By Chengliang Yang

Data Driven Approaches for Healthcare by Chengliang Yang

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Summary

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.

Data Driven Approaches for Healthcare Summary

Data Driven Approaches for Healthcare: Machine learning for Identifying High Utilizers by Chengliang Yang

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

    • About Chengliang Yang

    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.

    Table of Contents

    Introduction. Overview of Healthcare Data. Machine Learning Modeling from Healthcare Data. Machine Learning Modeling from Healthcare Data. Descriptive Analysis of High Utlizers. Residuals Analysis for Identifying High Utilizers.Machine Learning Results for High Utilizers.

    Additional information

    NLS9781032088686
    9781032088686
    1032088680
    Data Driven Approaches for Healthcare: Machine learning for Identifying High Utilizers by Chengliang Yang
    Chengliang Yang
    Chapman & Hall/CRC Big Data Series
    New
    Paperback
    Taylor & Francis Ltd
    2021-06-30
    120
    N/A
    Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
    This is a new book - be the first to read this copy. With untouched pages and a perfect binding, your brand new copy is ready to be opened for the first time

    Customer Reviews - Data Driven Approaches for Healthcare