Researchers from iPATH, an NIH Collaboratory Trial, described key considerations for integrating artificial intelligence tools into analyses of qualitative data.
The report was posted this month on the AcademyHealth Blog.
The iPATH trial, led by principal investigator Sara Singer at Stanford University, will test the implementation of a practice transformation strategy for type 2 diabetes in federally qualified health centers in California, Massachusetts, Ohio, and Puerto Rico. In the first phase of the project, the study team is refining the strategy by conducting case studies with 12 health centers to identify organizational conditions and processes that promote or impede the effectiveness of diabetes care.
Interviews for the 12 case studies generated 170 hours of qualitative data plus related materials. The study team explored how rapidly evolving artificial intelligence tools, such as large language models, might enhance researchers’ handling of large qualitative datasets, including labor-intensive and time-consuming processes of transcription, coding, and analysis.
iPATH is supported by a grant award from the National Institute on Minority Health and Health Disparities. Learn more about iPATH.