Effectiveness and user experience of ambient artificial intelligence-driven scribe technology among clinicians: a protocol for a systematic review

The increasing adoption of electronic health records (EHRs) has contributed to high documentation burden among clinicians, negatively impacting job satisfaction and contributing to burnout. Ambient AI-driven scribe technology has emerged as a potential solution to automate clinical documentation and reduce clerical burden. However, the effectiveness and user experience of AI-scribes for clinicians have not been comprehensively evaluated. This systematic review will critically evaluate the current scientific evidence on the effectiveness and user experience of AI-driven scribe technology from the perspective of clinicians. We will conduct a systematic search of PubMed, Web of Science, Embase, CINAHL, MEDLINE, The Cochrane Library, PsycINFO, and Scopus from database inception to December 2024. The search strategy will include terms related to AI-scribes, clinical documentation, and clinician experience. We will include randomized trials, observational studies, qualitative studies, and usability evaluations of AI-driven scribe technology used by clinicians in outpatient settings. Two reviewers will independently screen studies, extract data, and assess risk of bias using standardized tools. Results will be synthesized narratively and quantitatively where appropriate, with a focus on identifying key benefits, challenges, and future directions to optimize AI-scribes for enhanced clinician experience and patient care delivery. By providing a comprehensive evidence synthesis, this systematic review will inform strategic decision-making around the adoption and implementation of AI-driven scribes in clinical practice. The results will identify areas for future research and development of this promising technology to best support clinicians and alleviate documentation burden. Findings may also guide policies and best practices. PROSPERO CRD42024600076

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Publication Details

Journal
Systematic Reviews
Published
2026-07-23
DOI
https://doi.org/10.1186/s13643-026-03220-y
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

Effectiveness and user experience of ambient artificial intelligence-driven scribe technology among clinicians: a protocol for a systematic review

Amartya Mukhopadhyay, Anjali Bundele, Ravi Shankar, Fiona Devi Siva Kumar
Systematic Reviews
Artificial Intelligence in Healthcare and Education
article

Effectiveness and user experience of ambient artificial intelligence-driven scribe technology among clinicians: a protocol for a systematic review

Amartya Mukhopadhyay, Anjali Bundele, Ravi Shankar, Fiona Devi Siva Kumar
article en

Abstract

The increasing adoption of electronic health records (EHRs) has contributed to high documentation burden among clinicians, negatively impacting job satisfaction and contributing to burnout. Ambient AI-driven scribe technology has emerged as a potential solution to automate clinical documentation and reduce clerical burden. However, the effectiveness and user experience of AI-scribes for clinicians have not been comprehensively evaluated. This systematic review will critically evaluate the current scientific evidence on the effectiveness and user experience of AI-driven scribe technology from the perspective of clinicians. We will conduct a systematic search of PubMed, Web of Science, Embase, CINAHL, MEDLINE, The Cochrane Library, PsycINFO, and Scopus from database inception to December 2024. The search strategy will include terms related to AI-scribes, clinical documentation, and clinician experience. We will include randomized trials, observational studies, qualitative studies, and usability evaluations of AI-driven scribe technology used by clinicians in outpatient settings. Two reviewers will independently screen studies, extract data, and assess risk of bias using standardized tools. Results will be synthesized narratively and quantitatively where appropriate, with a focus on identifying key benefits, challenges, and future directions to optimize AI-scribes for enhanced clinician experience and patient care delivery. By providing a comprehensive evidence synthesis, this systematic review will inform strategic decision-making around the adoption and implementation of AI-driven scribes in clinical practice. The results will identify areas for future research and development of this promising technology to best support clinicians and alleviate documentation burden. Findings may also guide policies and best practices. PROSPERO CRD42024600076

Systematic Reviews
National University of Singapore (SG), Alexandra Hospital (SG), National University Health System (SG)
Peace, Justice and strong institutions
Openalex Percentile: Top 12%
Artificial Intelligence in Healthcare and Education
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