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Emergency Department Management: Data Analytics for Improving Productivity and Patient Experience

Foster, Krista (2020) Emergency Department Management: Data Analytics for Improving Productivity and Patient Experience. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

The onset of big data, typically defined by its volume, velocity, and variety, is transforming the healthcare industry. This research utilizes data corresponding to over 23 million emergency department (ED) visits between January 2010 and December 2017 which were treated by physicians and advanced practice providers from a large national emergency physician group. This group has provided ED services to health systems for several years, and each essay aims to address operational challenges faced by this group’s management team.

The first essay focuses on physician performance. We question how to evaluate performance across multiple sites and work to understand the relationships between patient flow, patient complexity, and patient experience. Specifically, an evaluation system to assess physician performance across multiple facilities is proposed, the relationship between productivity and patient experience scores is explored, and the drivers of patient flow and complexity are simultaneously identified.

The second essay explores the relationship between physician performance and malpractice claims as we investigate whether physicians’ practice patterns change after they are named in a malpractice lawsuit. Overall, the results of this analysis indicate that the likelihood of being named in a malpractice claim is largely a function of how long a physician has practiced. Furthermore, physician practice patterns remain consistent after a physician is sued, but patient experience scores increase among sued physicians after the lawsuit is filed. Such insights are beneficial for management as they address the issue of medical malpractice claims.

The final essay takes a closer look at the relationship between advanced practice providers (APPs) and physicians. Can EDs better utilize APPs to reduce waiting times and improve patient flow? A systematic data-driven approach which incorporates descriptive, predictive, and prescriptive analyses is employed to provide recommendations for ED provider staffing practices.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Foster, Kristakmf88@pitt.edukmf88
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairShang, Jennifershang@katz.pitt.edushang
Committee MemberVenkat, Arvindavenkat@ahn-emp.com
Committee MemberKekre, Sunderskekre@cmu.edu
Committee MemberHegde, GajananHegde@kat.pitt.eduhegde
Committee MemberValdes, Leonlvaldes@katz.pitt.edulvaldes
Date: 31 August 2020
Date Type: Publication
Defense Date: 26 June 2020
Approval Date: 31 August 2020
Submission Date: 28 August 2020
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 181
Institution: University of Pittsburgh
Schools and Programs: College of Business Administration > Business Administration
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Big data, healthcare operations, operations management
Date Deposited: 31 Aug 2020 15:58
Last Modified: 31 Aug 2020 15:58
URI: http://d-scholarship.pitt.edu/id/eprint/39678

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