東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

A Framework for Quantitative Evaluat...

Liu, Wei.

FindBook

Google Book

Amazon

博客來

A Framework for Quantitative Evaluation of Care Coordination Effectiveness.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	A Framework for Quantitative Evaluation of Care Coordination Effectiveness./
作者:	Liu, Wei.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:	216 p.
附註:	Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
Contained By:	Dissertation Abstracts International78-12B(E).
標題:	Health care management. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10267511
ISBN:	9780355088786

A Framework for Quantitative Evaluation of Care Coordination Effectiveness.
Liu, Wei.

A Framework for Quantitative Evaluation of Care Coordination Effectiveness. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 216 p.

Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.

Thesis (Ph.D.)--Purdue University, 2017.

The U.S. healthcare system lacks incentives and quantitative evaluation tools to assess coordination in a patient's care transition process. This is needed because poor care coordination has been identified by many studies as one of the major root causes for the U.S. health system's inefficiency, for poor outcomes, and for high cost. Despite efforts dedicated to improve care coordination, technical gaps still exist on how to understand and assess care coordination in a quantitative, effective, and methodological manner. Existing literature primarily focuses on applying case studies and qualitative measures to evaluate care coordination activities and their related outcomes. However, utilizing care transition dynamics to quantitatively evaluate the effectiveness of care coordination in terms of outcomes remains an open problem.

ISBN: 9780355088786Subjects--Topical Terms:

2122906
Health care management.

A Framework for Quantitative Evaluation of Care Coordination Effectiveness.
LDR:03492nmm a2200361 4500 001 2203109
005 20190528072648.5
008 201008s2017 ||||||||||||||||| ||eng d
020 $a 9780355088786
035 $a (MiAaPQ)AAI10267511
035 $a (MiAaPQ)purdue:21120
035 $a AAI10267511
040 $a MiAaPQ $c MiAaPQ
100 1 $a Liu, Wei. $3 1260300
245 1 2 $a A Framework for Quantitative Evaluation of Care Coordination Effectiveness.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 216 p.
500 $a Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
500 $a Advisers: Steven J. Landry; Ping H. Huang.
502 $a Thesis (Ph.D.)--Purdue University, 2017.
520 $a The U.S. healthcare system lacks incentives and quantitative evaluation tools to assess coordination in a patient's care transition process. This is needed because poor care coordination has been identified by many studies as one of the major root causes for the U.S. health system's inefficiency, for poor outcomes, and for high cost. Despite efforts dedicated to improve care coordination, technical gaps still exist on how to understand and assess care coordination in a quantitative, effective, and methodological manner. Existing literature primarily focuses on applying case studies and qualitative measures to evaluate care coordination activities and their related outcomes. However, utilizing care transition dynamics to quantitatively evaluate the effectiveness of care coordination in terms of outcomes remains an open problem.
520 $a This dissertation proposes an integrated data-driven analytical framework for quantitative evaluation of care coordination effectiveness under care transition dynamics. The main objective is to develop quantitative metrics for decision support for identifying care coordination opportunities. First, data structuring, data processing, and aggregation techniques are proposed to extract inpatient episodes that serve as the fundamental units of the proposed framework. Next, a set of metrics are developed to assess care coordination effectiveness from three perspectives, including care transition dynamics, major interactions among patients and providers, and defined patient outcomes -- specifically 30-day hospital readmission. Finally, an integrated metric model is developed to validate the feasibility and effectiveness of the proposed metrics as well as identify the most relevant set of metrics for defined system features.
520 $a For evaluation and validation, the proposed framework has been applied to a healthcare claims data set. A number of metrics have been identified that have significant impacts on the corresponding outcomes. In addition, a set of well-performing metrics has been identified by the integrated metric model for defined system features. Outputs of the proposed framework can be utilized by healthcare professionals and administrators as decision support for understanding the unique features of a specified patient provider network as well as identifying the opportunities for care coordination activities to improve care transition quality and associated patient outcomes.
590 $a School code: 0183.
650 4 $a Health care management. $3 2122906
650 4 $a Statistics. $3 517247
650 4 $a Industrial engineering. $3 526216
650 4 $a Information science. $3 554358
650 4 $a Engineering. $3 586835
690 $a 0769
690 $a 0463
690 $a 0546
690 $a 0723
690 $a 0537
710 2 $a Purdue University. $b Industrial Engineering. $3 1035836
773 0 $t Dissertation Abstracts International $g 78-12B(E).
790 $a 0183
791 $a Ph.D.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10267511