Actionable Intelligence in Healthcare by Liebowitz, Jay; Dawson, Amanda;

Rövid leírás:

Actionable Intelligence in Healthcare cuts through the hype and misconceptions regarding healthcare data analytics, provides a realistic assessment of the state of healthcare data analytics today, and offers an insightful forecast of both the near-term and longer-term development in the field.

Hosszú leírás:

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.

Tartalomjegyzék:

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Making Data Matter: Identifying Care Opportunities for US Healthcare Transformation
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Turning Data into Enhanced Value for Patients
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Data Analytics for the Clinical Researcher
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Intelligent Healthcare: The Case of the Emergency Department
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Network Analytics to Enable Decisions in Healthcare Management
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Modeling and Analysis of Behavioral Health Data Using Graph Analytics
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The Heart of the Digital Workplace: Intelligent Search Moves the Measure from Efficiency to Proficiency for a Fortune Healthcare Company
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The Promise of Big Data Analytics—Transcending Knowledge Discovery through Point-of-Care Applications
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Predictive Analytics and Machine Learning in Medicine
L. Nelson Sanchez-Pinto and Matthew M. Churpek

High-Dimensional Models and Analytics in Large Database Applications
Michael Brimacombe

Learning to Extract Actionable Evidence from Medical Insurance Claims Data
Jieshi Chen and Artur Dubrawski

The Role of Unstructured Data in Healthcare Analytics
Amanda Dawson and Sergei Ananyan