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Dissertation
Comparative case study on implementing generative AI in medical practices to ease documentative overburden: a sociotechnical systems perspective
Doctor of Business Administration (D.B.A.), Drexel University
Feb 2025
DOI:
https://doi.org/10.17918/00010865
Abstract
This is a comparative case study of a live implementation of a Generative AI solution for clinical documentation in five medical practices. Findings from this study shed new light on the impact of implementing an emerging and uncertain technology such as Generative AI on the social structures, roles, organizational processes, and technical systems of medical practices. It is well known that increasing the burden of documentation on physicians has led to medical errors, patient safety concerns, and physician burnout. This study investigates the adoption and implementation of a Generative AI-based clinical documentation technology in medical practices over a span of five months. The data in this case study consist of interviews, participant observations, the documenting and mapping of processes, the tracking of social interactions, and the textual analysis of user feedback. The findings helped develop an implementation process that can be generalized across medical practices. They also allowed me to identify and categorize changes in the medical practices' social, technical, and organizational, and intermediate outcomes. Furthermore, as an additional post-hoc exploration, I conducted a multi-value qualitative comparative analysis (mvQCA) to determine the factors that promote or impede the adoption of AI in medical practices. Using Generative AI in medical practices has led to both tangible and intangible benefits, including the creation of the new role of scribe to provide human oversight of AI-generated clinical documentation. Resistance and apprehension from the medical staff have impacted the speed of the implementation of AI and decision-making about its use. The study emphasizes the importance of considering changes in social and organizational processes in the adoption of new technologies and identifies the reformulation of roles and triadic co-creation as key concepts. My framework also includes the experiences of an entrepreneur in the field and the team who co-created the technological solution with the medical practices. Overall, this research provides a processual framework to capture the nuances of the adoption and co-evolution of an emerging and uncertain technology.
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Details
- Title
- Comparative case study on implementing generative AI in medical practices to ease documentative overburden
- Creators
- Sri Ramesh Eevani
- Contributors
- Rajiv Nag (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Business Administration (D.B.A.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- iii, i, 258 pages
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- Bennett S. LeBow College of Business; Drexel University
- Other Identifier
- 991022029338204721