Data Driven Approaches for Healthcare

using a data-driven approach, we need to ensure high utilizers can be identified as outliers when we represent the data. Existing studies usually depend on count- and cost-based criteria [19, 68]. Thus, we will start from these criteria ...

Data Driven Approaches for Healthcare

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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Data Driven Approaches for Healthcare
Language: en
Pages: 112
Authors: Chengliang Yang, Chris Delcher, Elizabeth Shenkman, Sanjay Ranka
Categories: Business & Economics
Type: BOOK - Published: 2019-10-10 - Publisher: CRC Press

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
Healthcare Service Management
Language: en
Pages: 168
Authors: Li Tao, Jiming Liu
Categories: Computers
Type: BOOK - Published: 2019-05-08 - Publisher: Springer

Healthcare service systems are of profound importance in promoting the public health and wellness of people. This book introduces a data-driven complex systems modeling approach (D2CSM) to systematically understand and improve the essence of healthcare service systems. In particular, this data-driven approach provides new perspectives on health service performance by
Data Driven Approach Towards Disruptive Technologies
Language: en
Pages: 597
Authors: T P Singh, Ravi Tomar, Tanupriya Choudhury, Thinagaran Perumal, Hussain Falih Mahdi
Categories: Technology & Engineering
Type: BOOK - Published: 2021-04-06 - Publisher: Springer Nature

This book is a compilation of peer-reviewed papers presented at the International Conference on Machine Intelligence and Data Science Applications, organized by the School of Computer Science, University of Petroleum & Energy Studies, Dehradun, India, during 4–5 September 2020. The book addresses the algorithmic aspect of machine intelligence which includes
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Language: en
Pages:
Authors: Dov Greenbaum, Laura Yenisa Cabrera
Categories: Science
Type: BOOK - Published: 2020-12-15 - Publisher: Frontiers Media SA

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Mastering Leadership
Language: en
Pages: 322
Authors: Alan T. Belasen, Barry Eisenberg, John W. Huppertz
Categories: Business & Economics
Type: BOOK - Published: 2015-01-17 - Publisher: Jones & Bartlett Publishers

The challenges facing the healthcare industry are unparalleled in scope, number, and magnitude. Organizational realignments of health care systems, uncertainty about the course and impact of legislation, an aging population with evolving clinical needs, the rapid evolution of information management technologies--all combined with pressure to establish reliable systems of quality