Actionable Intelligence In Healthcare

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Actionable Intelligence in Healthcare

Actionable Intelligence in Healthcare
Author :
Publisher : CRC Press
Total Pages : 294
Release :
ISBN-10 : 9781351803670
ISBN-13 : 1351803670
Rating : 4/5 (670 Downloads)

Book Synopsis Actionable Intelligence in Healthcare by : Jay Liebowitz

Download or read book Actionable Intelligence in Healthcare written by Jay Liebowitz and published by CRC Press. This book was released on 2017-04-07 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows healthcare professionals how to turn data points into meaningful knowledge upon which they can take effective action. Actionable intelligence can take many forms, from informing health policymakers on effective strategies for the population to providing direct and predictive insights on patients to healthcare providers so they can achieve positive outcomes. It can assist those performing clinical research where relevant statistical methods are applied to both identify the efficacy of treatments and improve clinical trial design. It also benefits healthcare data standards groups through which pertinent data governance policies are implemented to ensure quality data are obtained, measured, and evaluated for the benefit of all involved. Although the obvious constant thread among all of these important healthcare use cases of actionable intelligence is the data at hand, such data in and of itself merely represents one element of the full structure of healthcare data analytics. This book examines the structure for turning data into actionable knowledge and discusses: The importance of establishing research questions Data collection policies and data governance Principle-centered data analytics to transform data into information Understanding the "why" of classified causes and effects Narratives and visualizations to inform all interested parties Actionable Intelligence in Healthcare is an important examination of how proper healthcare-related questions should be formulated, how relevant data must be transformed to associated information, and how the processing of information relates to knowledge. It indicates to clinicians and researchers why this relative knowledge is meaningful and how best to apply such newfound understanding for the betterment of all.


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