SynthesisJournal of the American Medical Informatics Association : JAMIA2019
Speech recognition for clinical documentation from 1990 to 2018: a systematic review.
Synthesis in Journal of the American Medical Informatics Association : JAMIA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06792890 (A Randomized Controlled Trial of Two Ambient Artificial Intelligence Scribe Technologies to Improve Documentation Efficiency and Reduce Physician Burnout), which is not on this map. Cited by 42 papers, 5 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.
A Randomized Controlled Trial of Two Ambient Artificial Intelligence Scribe Technologies to Improve Documentation Efficiency and Reduce Physician Burnout
Who cites it
42 citing papers in PubMed, 5 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
- Evaluating the performance of artificial intelligence-based speech recognition for clinical documentation: a systematic review.BMC medical informatics and decision making · 2025Pooled it
- Impact of artificial intelligence on electronic health record-related burnouts among healthcare professionals: systematic review.Frontiers in public health · 2025Pooled it
- Improving Clinical Documentation with Artificial Intelligence: A Systematic Review.Perspectives in health information management · 2024Pooled it
- Technological progress in electronic health record system optimization: Systematic review of systematic literature reviews.International journal of medical informatics · 2021Pooled it
- What happens at the postpartum visit? Discordance between patient-reported and electronic medical record-documented postpartum care.Annals of epidemiology · 2026Trial
- Ambient AI Scribes as Emerging Infrastructure in the Learning Health System.Learning health systems · 2026Article
- Listening in: Orthopaedic Oncology Physicians' Perspectives on Implementation of Audio Recording/Artificial Intelligence Assist in Office Visits.Journal of surgical oncology · 2026Article
- Developing an AI platform for voice-input medical records in Polish: a digital application for optimisation of physicians' workload.Scientific reports · 2026Article
- Large language models in healthcare quality management: a European perspective on process automation and compliance.Frontiers in digital health · 2026Review
- Benchmarking speech-to-text robustness in noisy emergency medical dialogues: an evaluation of models under realistic acoustic conditions.JAMIA open · 2025Article
- Evaluating the Quality and Safety of Ambient Digital Scribe Platforms Using Simulated Ambulatory Encounters.Mayo Clinic proceedings. Digital health · 2025Article
- 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
- Time Motion Analysis of Emergency Physician Workload in Urgent Care Settings.The western journal of emergency medicine · 2025Observational
- Smart Healthcare: The Role of Digital Health in Modern Medicine.Health care science · 2025Article
- Effectiveness of conversational script optimization by intelligent consultation robots on daily work efficiency in vaccination clinics.Frontiers in public health · 2025Article
- Using voice recognition and machine learning techniques for detecting patient-reported outcomes from conversational voice in palliative care patients.Japan journal of nursing science : JJNS · 2025Article
- Revolutionizing Radiology with Natural Language Processing and Chatbot Technologies: A Narrative Umbrella Review on Current Trends and Future Directions.Journal of clinical medicine · 2024Review
- Use of an ambient artificial intelligence tool to improve quality of clinical documentation.Future healthcare journal · 2024Article
- Assessing the Assessment-Developing and Deploying a Novel Tool for Evaluating Clinical Notes' Diagnostic Assessment Quality.Journal of general internal medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
objectiveThe study sought to review recent literature regarding use of speech recognition (SR) technology for clinical documentation and to understand the impact of SR on document accuracy, provider efficiency, institutional cost, and more. MATERIALS AND
methodsWe searched 10 scientific and medical literature databases to find articles about clinician use of SR for documentation published between January 1, 1990, and October 15, 2018. We annotated included articles with their research topic(s), medical domain(s), and SR system(s) evaluated and analyzed the results.
resultsOne hundred twenty-two articles were included. Forty-eight (39.3%) involved the radiology department exclusively and 10 (8.2%) involved emergency medicine; 10 (8.2%) mentioned multiple departments. Forty-eight (39.3%) articles studied productivity; 20 (16.4%) studied the effect of SR on documentation time, with mixed findings. Decreased turnaround time was reported in all 19 (15.6%) studies in which it was evaluated. Twenty-nine (23.8%) studies conducted error analyses, though various evaluation metrics were used. Reported percentage of documents with errors ranged from 4.8% to 71%; reported word error rates ranged from 7.4% to 38.7%. Seven (5.7%) studies assessed documentation-associated costs; 5 reported decreases and 2 reported increases. Many studies (44.3%) used products by Nuance Communications. Other vendors included IBM (9.0%) and Philips (6.6%); 7 (5.7%) used self-developed systems.
conclusionDespite widespread use of SR for clinical documentation, research on this topic remains largely heterogeneous, often using different evaluation metrics with mixed findings. Further, that SR-assisted documentation has become increasingly common in clinical settings beyond radiology warrants further investigation of its use and effectiveness in these settings.
Indexed as
Identifiers
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.