Explainable Notes: Examining How to Unlock Meaning in Medical Notes with Interactivity and Artificial Intelligence

要旨

Medical progress notes have recently become available to patients at an unprecedented scale. Progress notes offer patients insight into their care that they cannot find elsewhere. That said, reading a note requires patients to contend with the language, unspoken assumptions, and clutter common to clinical documentation. As the health system reinvents many of its interfaces to incorporate AI assistance, this paper examines what intelligent interfaces could do to help patients read their progress notes. In a qualitative study, we examine the needs of patients as they read a progress note. We then formulate a vision for the explainable note, an augmented progress note that provides support for directing attention, phrase-level understanding, and tracing lines of reasoning. This vision manifests in a set of patient-inspired opportunities for advancing intelligent interfaces for writing and reading progress notes.

著者
Hita Kambhamettu
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Danaë Metaxa
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Kevin Johnson
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Andrew Head
University of Pennsylvania, Philadelphia, Pennsylvania, United States
論文URL

https://doi.org/10.1145/3613904.3642573

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Health and AI C

313C
5 件の発表
2024-05-15 20:00:00
2024-05-15 21:20:00