SynthesisJournal of the American Medical Informatics Association : JAMIA2016
Risks and benefits of speech recognition for clinical documentation: a systematic review.
Synthesis in Journal of the American Medical Informatics Association : JAMIA, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 3 of them syntheses that pooled it.
What it found
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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
37 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
- Speech recognition for clinical documentation from 1990 to 2018: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2019Pooled it
- Speech Recognition for Medical Dictation: Overview in Quebec and Systematic Review.Journal of medical systems · 2018Pooled it
- Assessing the Reliability, Accuracy, and Relevance of Artificial Intelligence Speech Recognition for Clinical Documentation: A Scoping Review.Journal of evaluation in clinical practice · 2026Article
- Automatic Speech Recognition and Large Language Models for Multilingual Pathology Report Generation: Proof-of-Concept Study.JMIR formative research · 2026Article
- A hybrid large language model framework for structured data entry from code-switched persian clinical speech.Scientific reports · 2026Article
- Development of reports preparation system for colonoscopy using speech-to-text technology.Surgical endoscopy · 2025Article
- Technical requirements and optimization strategies for home-based teleradiology workstations: a review article.Insights into imaging · 2025Review
- Ambient Documentation Technology in Clinician Experience of Documentation Burden and Burnout.JAMA network open · 2025Article
- American College of Veterinary Radiology and European College of Veterinary Diagnostic Imaging consensus statement on imaging report foundations.Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association · 2025Article
- Standardized Comparison of Voice-Based Information and Documentation Systems to Established Systems in Intensive Care: Crossover Study.JMIR medical informatics · 2023Article
- Benefits, barriers, and facilitators of using speech recognition technology in nursing documentation and reporting: A cross-sectional study.Health science reports · 2023Article
- Speech Recognition System Generates Highly Accurate Endoscopic Reports in Clinical Practice.Internal medicine (Tokyo, Japan) · 2023Observational
- Evidence synthesis, digital scribes, and translational challenges for artificial intelligence in healthcare.Cell reports. Medicine · 2022Review
- A dataset of simulated patient-physician medical interviews with a focus on respiratory cases.Scientific data · 2022Article
- Accuracy of Cloud-Based Speech Recognition Open Application Programming Interface for Medical Terms of Korean.Journal of Korean medical science · 2022Article
- Memory-memory (M2) Authentication.Journal of medical systems · 2022Article
- Evaluation and comparison of errors on nursing notes created by online and offline speech recognition technology and handwritten: an interventional study.BMC medical informatics and decision making · 2022Article
- Radiology Dictation Errors with COVID-19 Protective Equipment: Does Wearing a Surgical Mask Increase the Dictation Error Rate?Journal of digital imaging · 2021Article
- Effect of Speech Recognition on Problem Solving and Recall in Consumer Digital Health Tasks: Controlled Laboratory Experiment.Journal of medical Internet research · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo review literature assessing the impact of speech recognition (SR) on clinical documentation.
methodsStudies published prior to December 2014 reporting clinical documentation using SR were identified by searching Scopus, Compendex and Inspect, PubMed, and Google Scholar. Outcome variables analyzed included dictation and editing time, document turnaround time (TAT), SR accuracy, error rates per document, and economic benefit. Twenty-three articles met inclusion criteria from a pool of 441.
resultsMost studies compared SR to dictation and transcription (DT) in radiology, and heterogeneity across studies was high. Document editing time increased using SR compared to DT in four of six studies (+1876.47% to -16.50%). Dictation time similarly increased in three of five studies (+91.60% to -25.00%). TAT consistently improved using SR compared to DT (16.41% to 82.34%); across all studies the improvement was 0.90% per year. SR accuracy was reported in ten studies (88.90% to 96.00%) and appears to improve 0.03% per year as the technology matured. Mean number of errors per report increased using SR (0.05 to 6.66) compared to DT (0.02 to 0.40). Economic benefits were poorly reported.
conclusionsSR is steadily maturing and offers some advantages for clinical documentation. However, evidence supporting the use of SR is weak, and further investigation is required to assess the impact of SR on documentation error types, rates, and clinical outcomes.
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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.