SynthesisBMC medical informatics and decision making2014
A systematic review of speech recognition technology in health care.
Synthesis in BMC medical informatics and decision making, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
44 citing papers in PubMed, 3 syntheses or guidelines pooled it, 133 citations in OpenAlex.
- 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
- Risks and benefits of speech recognition for clinical documentation: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2016Pooled it
- Analysis of Documentation Speed Using Web-Based Medical Speech Recognition Technology: Randomized Controlled Trial.Journal of medical Internet research · 2015Trial
- Canadian Paramedic User Requirements for Speech Recognition-Aided Documentation.Applied clinical informatics · 2026Article
- 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
- Opportunities for Epidemiological Data Collection in Dental Practices: A Thematic Analysis of Dutch Dentists' Views.International dental journal · 2026Article
- Evaluation of the performance of an artificial intelligence model in recognizing the habitual mixed language in Taiwan for generating periodontal charting text reports.Journal of dental sciences · 2026Article
- Development of reports preparation system for colonoscopy using speech-to-text technology.Surgical endoscopy · 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
- [Implementation and evaluation of a solution for automated documentation of the doctor-patient dialogue (ADAPI) in ophthalmology using the example of the IVI routine].Die Ophthalmologie · 2025Article
- Ambient artificial intelligence scribes: utilization and impact on documentation time.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Charting Tomorrow's Healthcare: A Traditional Literature Review for an Artificial Intelligence-Driven Future.Cureus · 2024Review
- Integrated Hands-Free Electronic Patient Care Report (ePCR) Charting (IHeC): Designing the Architecture.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- An expandable voice user interface as lab assistant based on an improved version of Google's speech recognition.Scientific reports · 2023Article
- Using HIPAA (Health Insurance Portability and Accountability Act)-Compliant Transcription Services for Virtual Psychiatric Interviews: Pilot Comparison Study.JMIR mental health · 2023Article
- Benefits, barriers, and facilitators of using speech recognition technology in nursing documentation and reporting: A cross-sectional study.Health science reports · 2023Article
- Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: A review.Computers in biology and medicine · 2023Review
- Speech Recognition System Generates Highly Accurate Endoscopic Reports in Clinical Practice.Internal medicine (Tokyo, Japan) · 2023Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo undertake a systematic review of existing literature relating to speech recognition technology and its application within health care.
methodsA systematic review of existing literature from 2000 was undertaken. Inclusion criteria were: all papers that referred to speech recognition (SR) in health care settings, used by health professionals (allied health, medicine, nursing, technical or support staff), with an evaluation or patient or staff outcomes. Experimental and non-experimental designs were considered. Six databases (Ebscohost including CINAHL, EMBASE, MEDLINE including the Cochrane Database of Systematic Reviews, OVID Technologies, PreMED-LINE, PsycINFO) were searched by a qualified health librarian trained in systematic review searches initially capturing 1,730 references. Fourteen studies met the inclusion criteria and were retained.
resultsThe heterogeneity of the studies made comparative analysis and synthesis of the data challenging resulting in a narrative presentation of the results. SR, although not as accurate as human transcription, does deliver reduced turnaround times for reporting and cost-effective reporting, although equivocal evidence of improved workflow processes.
conclusionsSR systems have substantial benefits and should be considered in light of the cost and selection of the SR system, training requirements, length of the transcription task, potential use of macros and templates, the presence of accented voices or experienced and in-experienced typists, and workflow patterns.
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.