Masters Theses

Keywords and Phrases

AI adoption; Artificial Intelligence; Healthcare; Organ Procurement Organizations; Organizational readiness; TOE framework

Abstract

"Although medical AI systems have promise, the healthcare system has not fully integrated them for improved organizational operations. Studies have been conducted to identify root causes for this hesitancy without targeting a specific domain in healthcare. This generalization can be enhanced for the nuanced or domain-specific factors that offer practical insights to organizations leader. In this thesis, I focus on the factors and sources of tensions in AI adoption in transplant system, which is highly regulated but encourages innovation. Applying the Extended Technology, Organization, Environment (TOE) framework, 10 interviews were conducted at Organ Procurement Organizations (OPOs).

Although not always technically feasible, improved organizational outcomes such as maximizing the transplant and donation rate, speeding up the existing process, facilitating expedited placement, and identifying surgeon behavioral patterns drive adoption. Among organizational factors, culture—top manager support, change management strategy and innovative culture—and resource availability encourage adoption. However, disagreement on AI information, inconsistent data practices, reluctance for data sharing, and unclear impact of AI on organizational operations and outcomes may challenge OPO AI adoption. Finally, the results suggests that there are two opposing visions for AI adoption. The top-down adoption involves regulatory and government organizations evaluating AI systems before adoption by all the OPOs at once. In contrast, a bottom-up adoption allows individual OPOs to adopt AI and develop best practices over time through experience. These findings suggest organizations in a highly regulated industry may face several tensions while deciding whether to adopt AI"-- Abstract, p. iii

Advisor(s)

Shank, Daniel Burton

Committee Member(s)

Canfield, Casey I.
Reynolds Kueny, Clair
Krueger, Merilee

Department(s)

Psychological Science

Degree Name

M.S. in Industrial-Organizational Psychology

Publisher

Missouri University of Science and Technology

Publication Date

2026

Pagination

ix, 67 pages

Note about bibliography

Includes_bibliographical_references_(pages 63-66)

Rights

© 2025 Amaneh Babaee , All Rights Reserved

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 12634

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