Location
Comstock Memorial Union, MSUM
Document Type
Poster
Event Website
https://www.mnstate.edu/sac/
Start Date
23-4-2024 12:00 AM
Publication Date
4-23-2024
Description
Problem or Gap: Numerous studies have shown that AI can be used for diagnosis, problem-solving, identification of key disease features, and treatment planning processes for complex clinical cases1. It is important to note that leaders and managers play a key role in implementing AI methods throughout their organizations, however, there is a dearth of studies that examines attitudes and perceptions of clinical and administrative leaders towards integration of AI in healthcare settings. Furthermore, there is a need for literature that helps in identification of both facilitators that lead to AI adoption and barriers that can hinder AI adoption in healthcare settings. Methods: A qualitative research methodology was employed where participants were required to participate in an hour long semi-structured interview. Research participants were selected because of their experiences and role as clinical and/or administrative leaders in healthcare settings. A purposive sampling strategy was used to recruit participants from a variety of healthcare settings (hospitals, long-term care organizations, hospice). The interview guide included open-ended questions that aimed to explore: (1) AI application in the organization (clinical and administrative processes) (2) leaders’ perspective on AI; (3) staff engagement in the implementation process and facilitators that enable adoption: (4) and the challenges faced when implementing AI in healthcare settings. Braun and Clarke’s thematic framework was selected to analyze the collected data. Results: It is important to note that this is an on-going study with a tentative timeline of April, 2024 for completion. We have recruited more than 20 leaders from a variety of healthcare organizations and 24 interviews have been completed. Four themes have emerged from the preliminary analysis of this on-going study (a) AI can play huge role in clinical and administrative processes; (b) need for education to implement AI and AI enabled tools; (c) need for structural support and resources for effective AI integration; (d) need for clear understanding of regulations and patient/resident privacy when AI will be more clearly integrated in day-to-day processes. Conclusion: This qualitative study aims to examine attitudes and perceptions of leaders towards use of AI and AI enabled tools in their respective settings. Preliminary data analysis suggests that incorporation of AI in clinical and business processes can lead to significant benefits for patients and providers of services. There is an increased need for time/resource investment, education programs, and training sessions to assist with implementation of AI and build much needed understanding of issues surrounding patient privacy issues and other relevant regulations.
Included in
Healthcare Leaders' Attitudes and Perceptions on Use of Artificial Intelligence (AI) and AI Enabled Tools in Healthcare Settings
Comstock Memorial Union, MSUM
Problem or Gap: Numerous studies have shown that AI can be used for diagnosis, problem-solving, identification of key disease features, and treatment planning processes for complex clinical cases1. It is important to note that leaders and managers play a key role in implementing AI methods throughout their organizations, however, there is a dearth of studies that examines attitudes and perceptions of clinical and administrative leaders towards integration of AI in healthcare settings. Furthermore, there is a need for literature that helps in identification of both facilitators that lead to AI adoption and barriers that can hinder AI adoption in healthcare settings. Methods: A qualitative research methodology was employed where participants were required to participate in an hour long semi-structured interview. Research participants were selected because of their experiences and role as clinical and/or administrative leaders in healthcare settings. A purposive sampling strategy was used to recruit participants from a variety of healthcare settings (hospitals, long-term care organizations, hospice). The interview guide included open-ended questions that aimed to explore: (1) AI application in the organization (clinical and administrative processes) (2) leaders’ perspective on AI; (3) staff engagement in the implementation process and facilitators that enable adoption: (4) and the challenges faced when implementing AI in healthcare settings. Braun and Clarke’s thematic framework was selected to analyze the collected data. Results: It is important to note that this is an on-going study with a tentative timeline of April, 2024 for completion. We have recruited more than 20 leaders from a variety of healthcare organizations and 24 interviews have been completed. Four themes have emerged from the preliminary analysis of this on-going study (a) AI can play huge role in clinical and administrative processes; (b) need for education to implement AI and AI enabled tools; (c) need for structural support and resources for effective AI integration; (d) need for clear understanding of regulations and patient/resident privacy when AI will be more clearly integrated in day-to-day processes. Conclusion: This qualitative study aims to examine attitudes and perceptions of leaders towards use of AI and AI enabled tools in their respective settings. Preliminary data analysis suggests that incorporation of AI in clinical and business processes can lead to significant benefits for patients and providers of services. There is an increased need for time/resource investment, education programs, and training sessions to assist with implementation of AI and build much needed understanding of issues surrounding patient privacy issues and other relevant regulations.
https://red.mnstate.edu/sac/2024/cshe/8