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Aligning Data with Strategy to Improve Outpatient Operations

Strickland, Skylar (2023) Aligning Data with Strategy to Improve Outpatient Operations. Master's Thesis, University of Pittsburgh. (Unpublished)

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The purpose is to use data in order to improve outpatient operations through various methodology. Although the sections are based on different specialties, all of them are aligned through improving the current environment. The first project worked to improve shortages especially in the space of medical assistants. The second project proposed a water filtration system in order to reduce cost and waste to the system. The third project strategized ways to decrease traffic to the Oakland offices to improve access. All projects are long-term in nature, and due to the short-term successes, will continue forward. All are significant as they work to improve revenue and access while decreasing the cost burden that an organization takes on. All projects address issues that have been increasingly important in the days after the height of the pandemic which includes improving access, decreasing waste, and addressing workforce shortages. They utilize the data to create strategies to improve these areas of opportunity for the organization. This is important as it is a clear, unbiased, and reliable way to create a strategical method.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Strickland, Skylarsis54@pitt.edusis54
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairBubas, Daviddavid.bubas@pitt.edudavid.bubas
Committee CoChairFisher, Danieldfisher@pitt.edudfisher
Date: 11 May 2023
Date Type: Publication
Defense Date: 7 April 2023
Approval Date: 11 May 2023
Submission Date: 27 April 2023
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 53
Institution: University of Pittsburgh
Schools and Programs: School of Public Health > Health Policy & Management
Degree: MHA - Master of Health Administration
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: None
Date Deposited: 11 May 2023 18:26
Last Modified: 11 May 2023 18:26


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