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Using predictive analytics to improve healthcare outcomes

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Using predictive analytics to improve healthcare outcomesedited by John W. Nelson, Jayne Felgen, Mary Ann Hozak.
其他作者:	Nelson, John W.
出版者:	Hoboken, NJ :Wiley,2021.
面頁冊數:	1 online resource (xxv, 438 p.) :ill.
標題:	Medical statistics.
電子資源:	https://onlinelibrary.wiley.com/doi/book/10.1002/9781119747826
ISBN:	9781119747826$q(electronic bk. ;$qoBook)

Using predictive analytics to improve healthcare outcomes
Using predictive analytics to improve healthcare outcomes[electronic resource] /edited by John W. Nelson, Jayne Felgen, Mary Ann Hozak. - Hoboken, NJ :Wiley,2021. - 1 online resource (xxv, 438 p.) :ill.

Includes bibliographical references and index.

Using Predictive Analytics to Improve Healthcare Outcomes delivers a 16-step process to use predictive analytics to improve operations in the complex industry of healthcare. The book includes numerous case studies that make use of predictive analytics and other mathematical methodologies to save money and improve patient outcomes. The book is organized as a "how-to" manual, showing how to use existing theory and tools to achieve desired positive outcomes. You will learn how your organization can use predictive analytics to identify the most impactful operational interventions before changing operations. This includes: A thorough introduction to data, caring theory, Relationship-Based Care, the Caring Behaviors Assurance System, and healthcare operations, including how to build a measurement model and improve organizational outcomes; An exploration of analytics in action, including comprehensive case studies on patient falls, palliative care, infection reduction, reducing rates of readmission for heart failure, and more - all resulting in action plans allowing clinicians to make changes that have been proven in advance to result in positive outcomes; Discussions of how to refine quality improvement initiatives, including the use of "comfort" as a construct to illustrate the importance of solid theory and good measurement in adequate pain management; and an examination of international organizations using analytics to improve operations within cultural context.

ISBN: 9781119747826$q(electronic bk. ;$qoBook)

Standard No.: 10.1002/9781119747826doiSubjects--Topical Terms:

182007
Medical statistics.

LC Class. No.: R850 / .U85 2021eb

Dewey Class. No.: 610.72

Using predictive analytics to improve healthcare outcomes
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300 $a 1 online resource (xxv, 438 p.) : $b ill.
504 $a Includes bibliographical references and index.
520 $a Using Predictive Analytics to Improve Healthcare Outcomes delivers a 16-step process to use predictive analytics to improve operations in the complex industry of healthcare. The book includes numerous case studies that make use of predictive analytics and other mathematical methodologies to save money and improve patient outcomes. The book is organized as a "how-to" manual, showing how to use existing theory and tools to achieve desired positive outcomes. You will learn how your organization can use predictive analytics to identify the most impactful operational interventions before changing operations. This includes: A thorough introduction to data, caring theory, Relationship-Based Care, the Caring Behaviors Assurance System, and healthcare operations, including how to build a measurement model and improve organizational outcomes; An exploration of analytics in action, including comprehensive case studies on patient falls, palliative care, infection reduction, reducing rates of readmission for heart failure, and more - all resulting in action plans allowing clinicians to make changes that have been proven in advance to result in positive outcomes; Discussions of how to refine quality improvement initiatives, including the use of "comfort" as a construct to illustrate the importance of solid theory and good measurement in adequate pain management; and an examination of international organizations using analytics to improve operations within cultural context.
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