A Rapid Update Protocol f a Published Scoping Review on AI-Enabled Digital Scribes in Primary Care (2025-2026)

Abstract Background: Artificial intelligence (AI)-enabled digital scribes, powered by automatic speech recognition (ASR) and natural language processing (NLP), are increasingly implemented in primary care to reduce documentation burden and support clinical workflow within electronic health records and electronic medical records. A scoping review published in 2026 synthesized evidence through November 2024. However, the rapid expansion of large language model-driven ambient documentation systems in 2025–2026 warrants an updated evidence synthesis. Given the accelerated pace of technological development and implementation, a rapid update methodology is appropriate to identify newly published studies and emerging implementation evidence. Methods/design: This rapid update will build upon a previously published scoping review and will follow methodological guidance for rapid reviews while maintaining transparency in reporting. Joanna Briggs Institute guidance for scoping reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) will be followed. The search will be limited to studies published from December 2024 to present (2026). Only a single database will be used (PubMed). Search terms will mirror the original strategy and include combinations of “digital scribe,” “ambient documentation,” “automatic speech recognition,” “natural language processing,” “machine learning,” and “electronic health record.” Eligible studies will include peer-reviewed empirical research examining AI-enabled digital scribes in primary care settings. Consistent with rapid review methodology, screening and data extraction will be conducted by a single reviewer with secondary verification of a subset of records. Extracted findings will be mapped to three predefined analytic domains: (1) effectiveness (documentation accuracy and workflow efficiency), (2) integration (technical interoperability and workflow fit), and (3) adoption (usability, training, uptake, safety, and cost). Methodological quality will not be used as a criterion for exclusion. Modified rapid review techniques will include a single reviewer, single database, and appropriate modifications with the PRISMA-SCR framework. This protocol is registered at Open Science Framework (https://osf.io/qw3v7). Methodological quality will not be used as a criterion for study exclusion. Discussion: This rapid update will identify emerging evidence on real-world implementation, safety, and sustainability of AI-enabled digital scribes in primary care. By focusing on literature published after November 2024, this review aims to capture developments associated with large language model-driven systems and early adoption at scale. Findings will inform future research directions and contribute to understanding how rapidly evolving AI documentation technologies are being integrated into primary care practice.