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Operations Research Models for Reduc...

Liu, Xiang.

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Operations Research Models for Reducing Hospital Readmissions.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Operations Research Models for Reducing Hospital Readmissions./
Author:	Liu, Xiang.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	156 p.
Notes:	Source: Dissertations Abstracts International, Volume: 81-05, Section: B.
Contained By:	Dissertations Abstracts International81-05B.
Subject:	Operations research. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27536152
ISBN:	9781687927842

Operations Research Models for Reducing Hospital Readmissions.
Liu, Xiang.

Operations Research Models for Reducing Hospital Readmissions. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 156 p.

Source: Dissertations Abstracts International, Volume: 81-05, Section: B.

Thesis (Ph.D.)--University of Michigan, 2019.

This item must not be sold to any third party vendors.

Hospital readmissions are burdensome and costly to both healthcare providers and patients. In the U.S., one in five Medicare patients is readmitted within 30 days of discharge. We study how to use operations research models to reduce hospital readmissions. Our approach focuses on both the hospital operations level and the policymaker system level. We develop a delay-time optimization framework to maximize the detection of post-operative complications via post-discharge checkups. Then we study how to design a bundled payment policy to balance and incentivize pre and post-discharge readmission reduction efforts. We build a readmission prediction model using laboratory values observed during the index hospitalization. Ultimately, we provide novel methods for reducing readmissions in the continuum of care spanning between the pre- and post-discharge stages, at the hospital and policymaker levels.

ISBN: 9781687927842Subjects--Topical Terms:

547123
Operations research.
Subjects--Index Terms:

Hospital readmission

Operations Research Models for Reducing Hospital Readmissions.
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245 1 0 $a Operations Research Models for Reducing Hospital Readmissions.
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300 $a 156 p.
500 $a Source: Dissertations Abstracts International, Volume: 81-05, Section: B.
500 $a Advisor: Helm, Jonathan;Lavieri, Mariel.
502 $a Thesis (Ph.D.)--University of Michigan, 2019.
506 $a This item must not be sold to any third party vendors.
506 $a This item must not be added to any third party search indexes.
520 $a Hospital readmissions are burdensome and costly to both healthcare providers and patients. In the U.S., one in five Medicare patients is readmitted within 30 days of discharge. We study how to use operations research models to reduce hospital readmissions. Our approach focuses on both the hospital operations level and the policymaker system level. We develop a delay-time optimization framework to maximize the detection of post-operative complications via post-discharge checkups. Then we study how to design a bundled payment policy to balance and incentivize pre and post-discharge readmission reduction efforts. We build a readmission prediction model using laboratory values observed during the index hospitalization. Ultimately, we provide novel methods for reducing readmissions in the continuum of care spanning between the pre- and post-discharge stages, at the hospital and policymaker levels.
590 $a School code: 0127.
650 4 $a Operations research. $3 547123
650 4 $a Industrial engineering. $3 526216
653 $a Hospital readmission
653 $a Healthcare policy
653 $a Reliability
690 $a 0546
690 $a 0796
710 2 $a University of Michigan. $b Industrial & Operations Engineering. $3 3344010
773 0 $t Dissertations Abstracts International $g 81-05B.
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792 $a 2019
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27536152