ArticlePloS one2023
Evaluating the adoption of voice recognition technology for real-time dictation in a rural healthcare system: A retrospective analysis of dragon medical one.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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.
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Who cites it
6 citing papers in PubMed, 16 citations in OpenAlex.
- Benchmarking speech-to-text robustness in noisy emergency medical dialogues: an evaluation of models under realistic acoustic conditions.JAMIA open · 2025Article
- Speech Recognition Technology and Documentation Efficiency.JAMA network open · 2025Article
- Enhancing Immersion in Virtual Reality-Based Advanced Life Support Training: Randomized Controlled Trial.JMIR serious games · 2025Article
- Few-shot network intrusion detection method based on multi-domain fusion and cross-attention.PloS one · 2025Article
- Article
- A voice-based digital assistant for intelligent prompting of evidence-based practices during ICU rounds.Journal of biomedical informatics · 2023Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn 2013, Marshfield Clinic Health System (MCHS) implemented the Dragon Medical One (DMO) system provided by Nuance Management Center (NMC) for Real-Time Dictation (RTD), embracing the idea of streamlined clinic workflow, reduced dictation hours, and improved documentation legibility. Since then, MCHS has observed a trend of reduced time in documentation, however, the target goal of 100% adoption of voice recognition (VR)-based RTD has not been met.
objectiveTo evaluate the uptake/adoption of VR technology for RTD in MCHS, between 2018-2020.
methodsDMO data for 1,373 MCHS providers from 2018-2020 were analyzed. The study outcome was VR uptake, defined as the median number of hours each provider used VR technology to dictate patient information, and classified as no/yes. Covariates included sex, age, US-trained/international medical graduates, trend, specialty, and facility. Descriptive statistics and unadjusted and adjusted logistic regression analyses were performed. Stata/SE.version.17 was used for analyses. P-values less than/equal to 0.05 were considered statistically significant.
resultsOf the 1,373 MCHS providers, the mean (SD) age was 48.3 (12.4) years. VR uptake was higher than no uptake (72.0% vs. 28.0%). In both unadjusted and adjusted analyses, VR uptake was 4.3 times and 7.7 times higher in 2019-2020 compared to 2018, respectively (OR:4.30,95%CI:2.44-7.46 and AOR:7.74,95%CI:2.51-23.86). VR uptake was 0.5 and 0.6 times lower among US-trained physicians compared to internationally-trained physicians (OR:0.53,95%CI:0.37-0.76 and AOR:0.58,95%CI:0.35-0.97). Uptake was 0.2 times lower among physicians aged 60/above than physicians aged 29/less (OR:0.20,95%CI:0.10-0.59, and AOR:0.17,95%CI:0.27-1.06).
conclusionSince 2018, VR adoption has increased significantly across MCHS. However, it was lower among US-trained physicians than among internationally-trained physicians (although internationally physicians were in minority) and lower among more senior physicians than among younger physicians. These findings provide critical information about VR trends, physician factors, and which providers could benefit from additional training to increase VR adoption in healthcare systems.
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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.