“Health services research (HSR) benefits from qualitative approaches, which build understanding of complex issues and the ‘hows and whys’ of the way health services function,” writes SHP’s Sara Singer, PhD, MBA, in this AcademyHealth blog post.

“Rigorous qualitative studies can, for example, offer nuanced insights into patient and provider experiences or systemic barriers to health care access and quality,” Singer, a professor of health policy, continues with Sasha Ronaghi, MS in computer science and a research assistant in Singer’s health policy lab, and Emmilie Aveling, PhD, MPhil, of Harvard University.

“However, the volume of data in qualitative research demands substantial human effort to analyze. A recent study we conducted involved 12 clinical sites with 12 hour-long interviews per site, which generated about 170 hours of data not including archival material.

"Unlike earlier natural language processing models, Generative AI and large language models (LLMs) allow researchers to more actively and creatively participate in the analysis through natural language interaction. LLMs offer powerful tools that could potentially improve the efficiency, creativity, and quality of qualitative research. By accelerating labor-intensive processes such as transcription, coding, and analysis, LLMs may enable researchers to study larger qualitative datasets. "

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