PhenoPad: Building AI enabled note-taking interfaces for patient encounters

Jixuan Wang,Helen Lu,Nicole Sultanum,Mia Husić,Aryan Arbabi,Marta Skreta,Haochi Zhang,Michael Brudno,Jingbo Yang

doi:10.1038/s41746-021-00555-9

Abstract

Current clinical note-taking approaches cannot capture the entirety of information available from patient encounters and detract from patient-clinician interactions. By surveying healthcare providers’ current note-taking practices and attitudes toward new clinical technologies, we developed a patient-centered paradigm for clinical note-taking that makes use of hybrid tablet/keyboard devices and artificial intelligence (AI) technologies. PhenoPad is an intelligent clinical note-taking interface that captures free-form notes and standard phenotypic information via a variety of modalities, including speech and natural language processing techniques, handwriting recognition, and more. The output is unobtrusively presented on mobile devices to clinicians for real-time validation and can be automatically transformed into digital formats that would be compatible with integration into electronic health record systems. Semi-structured interviews and trials in clinical settings rendered positive feedback from both clinicians and patients, demonstrating that AI-enabled clinical note-taking under our design improves ease and breadth of information captured during clinical visits without compromising patient-clinician interactions. We open source a proof-of-concept implementation that can lay the foundation for broader clinical use cases.

Highlights

Clinicians produce a considerable amount of data when seeing a patient, including records of patient history, physical examination, lab test requests, referral reports, etc
Some clinicians begin with free-text note-taking or structured paper forms, which are digitized through dictation, typing into electronic health record (EHR) systems, or scanning and indexing to the patient’s records
We investigated the current clinical note-taking workflows and unmet needs by surveying and interviewing health care providers

Summary

Introduction

Clinicians produce a considerable amount of data when seeing a patient, including records of patient history, physical examination, lab test requests, referral reports, etc. Others prefer typing digital notes directly into EHR systems while talking with patients and polishing the drafts after the encounters. These methods have a significant impact on clinicians’ workflow and workload. With paper-based note-taking, patient data must be registered first during the patient’s visit, and again during digitization. The large portion of time spent on documentation outside of patient encounters is tedious and repetitive[6], and heavy workloads can lead to dissatisfaction and burnout among clinicians, impacting their ability to provide patient care[7,8,9,10,11]

Methods

Results

Conclusion