ReviewNPJ digital medicine2019
Challenges of developing a digital scribe to reduce clinical documentation burden.
Review in NPJ digital medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07302906 (The SOAR Trial), which is not on this map. Cited by 67 papers, 3 of them syntheses that pooled it.
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.
The SOAR Trial (Scribe Optimization for Ambulatory Records): Ambient Artificial Intelligence Scribe With Voa Health for Generating Medical Documentation From Outpatient Visit Audio - A Randomized Controlled Trial
Who cites it
67 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Evidence on artificial intelligence-assisted clinical documentation and healthcare workers' emotional wellbeing at work: a scoping review.Frontiers in psychology · 2026Pooled it
- The burden of the digital environment: a systematic review on organization-directed workplace interventions to mitigate physician burnout.Journal of the American Medical Informatics Association : JAMIA · 2021Pooled it
- How does medical scribes' work inform development of speech-based clinical documentation technologies? A systematic review.Journal of the American Medical Informatics Association : JAMIA · 2020Pooled it
- AI-Assisted Medical Documentation in a Multilingual Swiss Health Care System: Proof-of-Concept Study.JMIR AI · 2026Article
- From Clinical Encounter to Draft Documentation: A Mechanistic Narrative Review of Ambient Scribe Technology.Cureus · 2026Review
- Validating Digital Scribes: A Scoping Review of Evaluation Practices and Clinical Use.Journal of medical systems · 2026Article
- When better data meets better design: How EHR data usability and system usability shape physicians' cognitive load.NPJ digital medicine · 2026Article
- The Current State of Digital Scribes in Primary Care: A Scoping Review.Journal of medical systems · 2026Article
- Management of Patients With Comorbid Asthma and Obesity: A Large Language Model Evaluation of Clinical Documentation.The journal of allergy and clinical immunology. In practice · 2026Article
- Review
- [Oncological operation reports: minimum requirements, legal aspects and future developments].Chirurgie (Heidelberg, Germany) · 2025Review
- The Current State and Future Prospects for Artificial Intelligence in Dermatology.Dermatologic clinics · 2025Review
- Assessing the Effectiveness of Automatic Speech Recognition Technology in Emergency Medicine Settings: a Comparative Study of Four AI-Powered Engines.Journal of healthcare informatics research · 2025Article
- Understanding Clinician Perceptions of GenAI: A Mixed Methods Analysis of Clinical Documentation Tasks.Journal of medical systems · 2025Article
- AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration.JMIR medical informatics · 2025Article
- Evaluating the Usability, Technical Performance, and Accuracy of Artificial Intelligence Scribes for Primary Care: Competitive Analysis.JMIR human factors · 2025Article
- The Impact of AI Scribes on Streamlining Clinical Documentation: A Systematic Review.Healthcare (Basel, Switzerland) · 2025Review
- Assessment and Integration of Large Language Models for Automated Electronic Health Record Documentation in Emergency Medical Services.Journal of medical systems · 2025Article
- Assessing Patient-Reported Satisfaction With Care and Documentation Time in Primary Care Through AI-Driven Automatic Clinical Note Generation: Protocol for a Proof-of-Concept Study.JMIR research protocols · 2025Article
- [Research progress in application of intelligent remote follow-up mode in hip and knee arthroplasty].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2025Review
7 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Clinicians spend a large amount of time on clinical documentation of patient encounters, often impacting quality of care and clinician satisfaction, and causing physician burnout. Advances in artificial intelligence (AI) and machine learning (ML) open the possibility of automating clinical documentation with digital scribes, using speech recognition to eliminate manual documentation by clinicians or medical scribes. However, developing a digital scribe is fraught with problems due to the complex nature of clinical environments and clinical conversations. This paper identifies and discusses major challenges associated with developing automated speech-based documentation in clinical settings: recording high-quality audio, converting audio to transcripts using speech recognition, inducing topic structure from conversation data, extracting medical concepts, generating clinically meaningful summaries of conversations, and obtaining clinical data for AI and ML algorithms.
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What 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.