ENGLISH

Healthcare Analytics: Foundations and Frontiers

By Ross M. Mullner , Edward M. Rafalski

Book information

Publisher
Routledge
Year
2019
ISBN
1498755070, 9781498755078
Language
english
Format
PDF
Filesize
6 MB (5958988 bytes)
Pages
120\121
Time added
2020-08-31 17:15:53

Description

This is a comprehensive, practical guide which looks at the advantages and limitations of new data analysis techniques being introduced across public health and administration services. The Affordable Care Act (ACT) and free market reforms in healthcare are generating a rapid change of pace. The "electronification" of medical records from paper to digital, which is required to meet the meaningful use standards set forth by the Act, is advancing what and how information can be analyzed. Coupled with the advent of more computing power and big data analytics and techniques, practitioners now more than ever need to stay on top of these trends. This book presents a comprehensive look at healthcare analytics from population data to geospatial analysis using current case studies and data analysis examples in health. This resource will appeal to undergraduate and graduate students in health administration and public health. It will benefit healthcare professionals and administrators in nursing and public health, as well as medical students who are interested in the future of data within healthcare. Cover Title Page Copyright Page Contents Foreword Lisr of Contributors Introduction 1. Managerial epidemiology: Creating care of health ecosystems Introduction What is epidemiology? What is managerial epidemiology? What is an ecosystem of care? Social media and its application Conclusion References 2. Healthcare and population data: The building blocks Background Why risk stratification? Overview of risk stratification methods Risk stratification: Examples Rising risk methodology: Follow-up on 38109 familiar faces Use of data References 3. Trend toward connected data architectures in healthcare Balancing cost and performance Risk management Sharing and connecting data Current state of databases in healthcare systems Introduction of NoSQL databases Summary References 4. Knowledge management for health data analytics Rise of the electronic health record Data governance and infrastructure issues Importance of data governance and infrastructure Analytics beyond statistics Feature selection Data mining Advantages Potential issues with data mining References 5. Geospatial analysis of patients with healthcare utilization for type 2 diabetes mellitus (T2DM): A use case approach Introduction Burden of the disease Research question Results Discussion References 6. Futuring: A brief overview of methods and tools Statistical regression models Delphi survey technique Environmental scanning: SWOT analysis Scenario analysis Conclusion References 7. Conclusion References Index

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