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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.
List of contents
Managerial epidemiology: Creating care of health ecosystems. Healthcare and population data: The building blocks. Trend toward connected data architectures in healthcare. Knowledge management for health data analytics. Geospatial analysis of patients with healthcare utilization for type 2 diabetes mellitus (T2DM): A use case approach. Futuring: A brief overview of methods and tools. Conclusion.
About the author
Ross M. Mullner is Associate Professor of Health Policy Administration at the University of Chicago at Illinois. Dr. Mullner's research interests are Health Services Research, Cancer Care and the History of Public Health.
Edward M. Rafalski is Clinical Assistant Professor at University of Illinois School of Public Health. He holds qualifications from the University of Chicago and Yale University School of Public Health.
Summary
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.
