Gary D. Miner, Linda A. Miner, Mitchell Goldstein, Robert Nisbet, Nephi Walton, Pat Bolding, Joseph Hilbe, Thomas Hill

Practical Predictive Analytics and Decisioning Systems for Medicine (eBook, ePUB)

Informatics Accuracy and Cost-Effectiveness for Healthcare Administration and Delivery Including Medical Research

• Format: ePub

Produktbeschreibung

With the advent of electronic medical records years ago and the increasing capabilities of computers, our healthcare systems are sitting on growing mountains of data. Not only does the data grow from patient volume but the type of data we store is also growing exponentially. Practical Predictive Analytics and Decisioning Systems for Medicine provides research tools to analyze these large amounts of data and addresses some of the most pressing issues and challenges where data integrity is compromised: patient safety, patient communication, and patient information. Through the use of predictive analytic models and applications, this book is an invaluable resource to predict more accurate outcomes to help improve quality care in the healthcare and medical industries in the most cost-efficient manner. Practical Predictive Analytics and Decisioning Systems for Medicine provides the basics of predictive analytics for those new to the area and focuses on general philosophy and activities in the healthcare and medical system. It explains why predictive models are important, and how they can be applied to the predictive analysis process in order to solve real industry problems. Researchers need this valuable resource to improve data analysis skills and make more accurate and cost-effective decisions.

• Includes models and applications of predictive analytics why they are important and how they can be used in healthcare and medical research
• Provides real world step-by-step tutorials to help beginners understand how the predictive analytic processes works and to successfully do the computations
• Demonstrates methods to help sort through data to make better observations and allow you to make better predictions

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 1110
• Erscheinungstermin: 27. September 2014
• Englisch
• ISBN-13: 9780124116405
• Artikelnr.: 41738392

Autorenporträt

Linda A. Winters-Miner, PhD, earned her bachelor's and master's degrees at University of Kansas, her doctorate at the University of Minnesota, and completed post-doctoral studies in psychiatric epidemiology at the University of Iowa. While she, with her husband Gary Miner, raised their children, Becky and Matt, she spent most of her career as an educator, in teacher education and statistics and research design. She spent nearly two years as a site coordinator for a major (Coxnex) drug trial. For 23 years, Miner directed academic programs for Southern Nazarene University- Tulsa. Her program direction included three undergraduate programs in business and psychology and three graduate programs in management, business administration, and health care administration. She has authored or co-authored numerous articles and books including with Gary and others, the first book concerning the genetics of Alzheimer's, Alzheimer's disease: Molecular genetics, clinical perspectives and promising new research. Winters - Miner authored some of the tutorials in the first two predictive analytic books published in 2009 and 2012 by Elsevier. At present, she teaches both undergraduate statistics and research at SNU-Tulsa, teaches statistics and predictive analytics for the IHI Family Practice Medical Residency program in Tulsa, and also teaches predictive analytics online, including 'healthcare predictive analytics', for both the University of California-Irvine and University of California - San Diego.