Not Another EHR: Reimagining Physician Information Needs with Generative AI Technology
For physicians and EHR designers, this paper offers qualitative insights into information needs and AI expectations, but it is an early-stage position paper without empirical validation.
This position paper identifies key challenges physicians face with EHRs and explores how generative AI can address them through dynamic interfaces, based on interviews with Microsoft physicians. It presents design considerations for clinician-centered workflows.
Electronic health records (EHRs) have improved data accessibility but have also introduced cognitive burden for physicians, given the sheer volume and complexity of the data involved. Advances in large language models (LLMs) create new opportunities to rethink how clinicians interact with medical data through dynamic, adaptive interfaces. In this position paper, we explore how generative AI can support physicians' information needs by enabling more dynamic interactions with patient data. Through semi-structured interviews with internal physicians at Microsoft, we identify key challenges in data navigation and synthesis, and characterize clinicians' information needs during diagnostic workflows. We further examine how physicians conceptualize AI can help their work process and how these mental models shape expectations for interaction and trust. Based on these insights, we discuss design considerations for generative user interfaces that support clinician-centered workflows.