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Operations Research Models for Reducing Hospital Readmissions
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Operations Research Models for Reducing Hospital Readmissions. |
| 개인저자 | Liu, Xiang. |
| 단체저자명 | University of Michigan. Industrial & Operations Engineering. |
| 발행사항 | [S.l.]: University of Michigan., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 156 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-05B. Dissertation Abstract International |
| ISBN | 9781687927842 |
| 학위논문주기 | Thesis (Ph.D.)--University of Michigan, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-05, Section: B.
Advisor: Helm, Jonathan |
| 이용제한사항 | This item must not be sold to any third party vendors.This item must not be added to any third party search indexes. |
| 요약 | 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. |
| 일반주제명 | Operations research. Industrial engineering. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
