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PhenoPad: Building AI enabled note-taking interfaces for patient encounters.
- Source :
- NPJ Digital Medicine; 1/27/2022, Vol. 5 Issue 1, p1-9, 9p
- Publication Year :
- 2022
-
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. [ABSTRACT FROM AUTHOR]
- Subjects :
- NOTETAKING
NATURAL language processing
ELECTRONIC health records
ARTIFICIAL intelligence
MEDICAL personnel
KEYBOARDS (Electronics)
ATTITUDES toward technology
INFORMATION storage & retrieval systems
MEDICAL databases
PHYSICIAN-patient relations
RESEARCH methodology
HANDWRITING
PATIENT satisfaction
INTERVIEWING
SURVEYS
PATIENTS' attitudes
DECISION support systems
WORKFLOW
MEDICAL records
QUESTIONNAIRES
Subjects
Details
- Language :
- English
- ISSN :
- 23986352
- Volume :
- 5
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- NPJ Digital Medicine
- Publication Type :
- Academic Journal
- Accession number :
- 154982025
- Full Text :
- https://doi.org/10.1038/s41746-021-00555-9