ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2024
Selection and Implementation of Virtual Scribe Solutions to Reduce Documentation Burden: A Mixed Methods Pilot.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Clinician Perceptions of Virtual Scribe Use: A Survey Study.Journal of general internal medicine · 2026Article
- AI-Powered Documentation for Mental Health Providers: Retrospective Observational Mixed Methods Study.JMIR formative research · 2026Observational
- The Current State of Digital Scribes in Primary Care: A Scoping Review.Journal of medical systems · 2026Article
- The use of ambient voice technology (AVT) for clinician-patient consultations in healthcare practice: A rapid systematic scoping review.BMJ digital health & AI · 2026Article
- Pre-Post Evaluation of Documentation Burden, Time Perception, and Cognitive Workload of Ambient AI Scribe Tools.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026Article
- Review
- The Impact of AI Scribes on Streamlining Clinical Documentation: A Systematic Review.Healthcare (Basel, Switzerland) · 2025Review
- Ethical data acquisition for LLMs and AI algorithms in healthcare.NPJ digital medicine · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Electronic health record (EHR) documentation is a leading reason for clinician burnout. While technology-enabled solutions like virtual and digital scribes aim to improve this, there is limited evidence of their effectiveness and minimal guidance for healthcare systems around solution selection and implementation. A transdisciplinary approach, informed by clinician interviews and other considerations, was used to evaluate and select a virtual scribe solution to pilot in a rapid iterative sprint over 12 weeks. Surveys, interviews, and EHR metadata were analyzed over a staggered 30 day implementation with live and asynchronous virtual scribe solutions. Among 16 pilot clinicians, documentation burden metrics decreased for some but not all. Some clinicians had highly positive comments, and others had concerns regarding scribe training and quality. Our findings demonstrate that virtual scribes may reduce documentation burden for some clinicians and describe a method for a collaborative and iterative technology selection process for digital tools in practice.
Identifiers
38827085PMC11141854What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.