AI Digital Scribe Template Enhancement for Non-Specific Symptom Documentation in Irish General Practice: A Mixed-Methods Feasibility Protocol

<ns3:p>Background Non-specific symptoms (NSS) such as unexplained fatigue, weight loss, or abdominal discomfort are common in general practice and may herald serious disease, including cancer. These symptoms are less consistently recorded than "alarm" symptoms, partly because time-pressured consultations limit comprehensive documentation. AI-enabled digital scribes are increasingly used in routine consultations and can be configured with templates to surface specified symptom groups, but their acceptability and practical value for NSS documentation in primary care are unknown. Aim To assess the acceptability and feasibility of an AI digital scribe template, enhanced for NSS documentation in Irish general practice, and to describe patterns of NSS documentation in template-generated consultation notes. Design and Setting Mixed-methods feasibility study in general practices within the ARQ Practice-Based Research Network in Ireland, all of which routinely use the Heidi™ AI medical scribe. Method In Phase 1 we will iteratively develop an NSS-focused template (covering eight target symptoms) and test it on publicly available primary care consultation data. In Phase 2, five purposively sampled GPs (n=5) will deploy the template during routine consultations over four weeks. In Phase 3, all GPs in the network using Heidi™ (n=30) will be invited to complete an online acceptability survey, with semi-structured interviews for pilot participants (n=5). In Phase 4, a pseudonymised chart review of clinical notes will describe template utilisation, GP editing behaviour, and NSS documentation prevalence. Quantitative data will be analysed descriptively; qualitative data will be analysed using the Framework Method and integrated using convergence coding matrices. Expected Outcomes Primary feasibility outcomes are: recruitment and retention of GPs; template use during routine consultations; template acceptability; and completeness of routine data extraction. Findings will inform refinement of the NSS template and the design of subsequent evaluative studies examining clinical impact. Study materials will be available via the Open Science Framework.</ns3:p>

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Journal
HRB Open Research
Published
2026-01-15
DOI
https://doi.org/10.12688/hrbopenres.14302.1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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article

AI Digital Scribe Template Enhancement for Non-Specific Symptom Documentation in Irish General Practice: A Mixed-Methods Feasibility Protocol

Nickola D. Pallin, Kurdo Araz, Conor Murphy, Catherine Devereux et al.
HRB Open Research
Artificial Intelligence in Healthcare and Education
article

AI Digital Scribe Template Enhancement for Non-Specific Symptom Documentation in Irish General Practice: A Mixed-Methods Feasibility Protocol

Nickola D. Pallin, Kurdo Araz, Conor Murphy, Catherine Devereux, Brona Mulligan, Patrick Redmond, Benjamin Jacob
article en

Abstract

<ns3:p>Background Non-specific symptoms (NSS) such as unexplained fatigue, weight loss, or abdominal discomfort are common in general practice and may herald serious disease, including cancer. These symptoms are less consistently recorded than "alarm" symptoms, partly because time-pressured consultations limit comprehensive documentation. AI-enabled digital scribes are increasingly used in routine consultations and can be configured with templates to surface specified symptom groups, but their acceptability and practical value for NSS documentation in primary care are unknown. Aim To assess the acceptability and feasibility of an AI digital scribe template, enhanced for NSS documentation in Irish general practice, and to describe patterns of NSS documentation in template-generated consultation notes. Design and Setting Mixed-methods feasibility study in general practices within the ARQ Practice-Based Research Network in Ireland, all of which routinely use the Heidi™ AI medical scribe. Method In Phase 1 we will iteratively develop an NSS-focused template (covering eight target symptoms) and test it on publicly available primary care consultation data. In Phase 2, five purposively sampled GPs (n=5) will deploy the template during routine consultations over four weeks. In Phase 3, all GPs in the network using Heidi™ (n=30) will be invited to complete an online acceptability survey, with semi-structured interviews for pilot participants (n=5). In Phase 4, a pseudonymised chart review of clinical notes will describe template utilisation, GP editing behaviour, and NSS documentation prevalence. Quantitative data will be analysed descriptively; qualitative data will be analysed using the Framework Method and integrated using convergence coding matrices. Expected Outcomes Primary feasibility outcomes are: recruitment and retention of GPs; template use during routine consultations; template acceptability; and completeness of routine data extraction. Findings will inform refinement of the NSS template and the design of subsequent evaluative studies examining clinical impact. Study materials will be available via the Open Science Framework.</ns3:p>

HRB Open ResearchVol. 9
Royal College of Surgeons in Ireland (IE)
Openalex Percentile: Top 88%
Artificial Intelligence in Healthcare and Education
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