Digital Scribes in Primary Care: A Rapid Scoping Review Protocol

Abstract Background: Digital scribe technologies are increasingly being explored in primary care as a means of reducing documentation burden and supporting clinical workflows. These systems commonly rely on automatic speech recognition (ASR) and natural language processing (NLP), which form the technical foundation of many artificial intelligence (AI)-enabled documentation tools. The purpose of this rapid scoping review is to map the existing literature on AI-enabled digital scribes in primary care, with a focus on reported effectiveness, integration with clinical workflows, and factors influencing adoption. Methods/design: This scoping review will be conducted in accordance with the Joanna Briggs Institute guidance for scoping reviews and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews framework. A systematic search will be conducted in PubMed. Search terms will include combinations of “digital scribe,” “automatic speech recognition,” “natural language processing,” “machine learning,” “electronic health record,” and “electronic medical record.” Eligible studies will examine AI-enabled digital scribes in primary care settings using quantitative, qualitative, or mixed-methods designs. Two reviewers will independently screen studies and chart data, with disagreements resolved through discussion or consultation with additional team members. Methodological quality will not be used as a criterion for study exclusion. Expected Outcomes: This scoping review is expected to provide a comprehensive mapping of the existing evidence on AI-enabled digital scribes in primary care, including how these technologies are evaluated, implemented, and adopted across different clinical contexts. These findings are intended to inform future research, evaluation design, and evidence-informed adoption of digital scribe technologies in primary care.