Applying LLMs to Interpret Qualitative Interviews in Healthcare: Insights from MIE2024

In August, Janna, Lotti, and Marie attended the Medical Informatics Europe Conference “MIE2024” held in August in Athens, Greece. Marie had the privilege of presenting our research paper, “Applying Large Language Models to Interpret Qualitative Interviews in Healthcare.”

In our study, we explored how Large Language Models (LLMs) can enhance and streamline the process of analyzing qualitative data in healthcare research. Our findings suggest that LLMs have the potential to significantly complement traditional human-driven methods, such as coding and annotation, by providing an additional layer of automation and efficiency. This opens up exciting new possibilities for scaling up qualitative research while maintaining the depth and nuance required in healthcare contexts.

By leveraging LLMs, researchers can accelerate the often time-consuming process of qualitative analysis, freeing up time for deeper interpretation and allowing for a more iterative and expansive exploration of healthcare data.

If you are interested in our findings and the potential applications of LLMs in this field, you can access our full conference paper here, and full interview study here.