Evaluating the adoption of voice recognition technology for real-time dictation in a rural healthcare system: A retrospective analysis of dragon medical one
<h4>Background</h4> In 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 documenta...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2023-01-01
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| Series: | PLoS ONE |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035815/?tool=EBI |
| _version_ | 1797860165700026368 |
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| author | Adedayo A. Onitilo Abdul R. Shour David S. Puthoff Yusuf Tanimu Adedayo Joseph Michael T. Sheehan |
| author_facet | Adedayo A. Onitilo Abdul R. Shour David S. Puthoff Yusuf Tanimu Adedayo Joseph Michael T. Sheehan |
| author_sort | Adedayo A. Onitilo |
| collection | DOAJ |
| description | <h4>Background</h4> In 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. <h4>Objective</h4> To evaluate the uptake/adoption of VR technology for RTD in MCHS, between 2018–2020. <h4>Methods</h4> DMO 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. <h4>Results</h4> Of 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). <h4>Conclusion</h4> Since 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. |
| first_indexed | 2024-04-09T21:41:23Z |
| format | Article |
| id | doaj.art-8afa6ea9c0ed4017a2f38a31cf9dd78c |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-04-09T21:41:23Z |
| publishDate | 2023-01-01 |
| publisher | Public Library of Science (PLoS) |
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| series | PLoS ONE |
| spelling | doaj.art-8afa6ea9c0ed4017a2f38a31cf9dd78c2023-03-26T05:32:09ZengPublic Library of Science (PLoS)PLoS ONE1932-62032023-01-01183Evaluating the adoption of voice recognition technology for real-time dictation in a rural healthcare system: A retrospective analysis of dragon medical oneAdedayo A. OnitiloAbdul R. ShourDavid S. PuthoffYusuf TanimuAdedayo JosephMichael T. Sheehan<h4>Background</h4> In 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. <h4>Objective</h4> To evaluate the uptake/adoption of VR technology for RTD in MCHS, between 2018–2020. <h4>Methods</h4> DMO 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. <h4>Results</h4> Of 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). <h4>Conclusion</h4> Since 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.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035815/?tool=EBI |
| spellingShingle | Adedayo A. Onitilo Abdul R. Shour David S. Puthoff Yusuf Tanimu Adedayo Joseph Michael T. Sheehan Evaluating the adoption of voice recognition technology for real-time dictation in a rural healthcare system: A retrospective analysis of dragon medical one PLoS ONE |
| title | Evaluating the adoption of voice recognition technology for real-time dictation in a rural healthcare system: A retrospective analysis of dragon medical one |
| title_full | Evaluating the adoption of voice recognition technology for real-time dictation in a rural healthcare system: A retrospective analysis of dragon medical one |
| title_fullStr | Evaluating the adoption of voice recognition technology for real-time dictation in a rural healthcare system: A retrospective analysis of dragon medical one |
| title_full_unstemmed | Evaluating the adoption of voice recognition technology for real-time dictation in a rural healthcare system: A retrospective analysis of dragon medical one |
| title_short | Evaluating the adoption of voice recognition technology for real-time dictation in a rural healthcare system: A retrospective analysis of dragon medical one |
| title_sort | evaluating the adoption of voice recognition technology for real time dictation in a rural healthcare system a retrospective analysis of dragon medical one |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035815/?tool=EBI |
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