Content-Length: 3330 | pFad | https://www.jmir.org/article/export/end/jmir_v17i11e247
%0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 17 %N 11 %P e247 %T Analysis of Documentation Speed Using Web-Based Medical Speech Recognition Technology: Randomized Controlled Trial %A Vogel,Markus %A Kaisers,Wolfgang %A Wassmuth,Ralf %A Mayatepek,Ertan %+ University Children’s Hospital Düsseldorf, Department of General Pediatrics, Neonatology and Pediatric Cardiology, Heinrich-Heine-University, Moorenstrasse 5, Düsseldorf, 40225, Germany, 49 21181 ext 16984, markus.vogel@med.uni-duesseldorf.de %K electronic health record %K automatic speech recognition %K randomized controlled trial %D 2015 %7 03.11.2015 %9 Original Paper %J J Med Internet Res %G English %X Background: Clinical documentation has undergone a change due to the usage of electronic health records. The core element is to capture clinical findings and document therapy electronically. Health care personnel spend a significant portion of their time on the computer. Alternatives to self-typing, such as speech recognition, are currently believed to increase documentation efficiency and quality, as well as satisfaction of health professionals while accomplishing clinical documentation, but few studies in this area have been published to date. Objective: This study describes the effects of using a Web-based medical speech recognition system for clinical documentation in a university hospital on (1) documentation speed, (2) document length, and (3) physician satisfaction. Methods: Reports of 28 physicians were randomized to be created with (intervention) or without (control) the assistance of a Web-based system of medical automatic speech recognition (ASR) in the German language. The documentation was entered into a browser’s text area and the time to complete the documentation including all necessary corrections, correction effort, number of characters, and mood of participant were stored in a database. The underlying time comprised text entering, text correction, and finalization of the documentation event. Participants self-assessed their moods on a scale of 1-3 (1=good, 2=moderate, 3=bad). Statistical analysis was done using permutation tests. Results: The number of clinical reports eligible for further analysis stood at 1455. Out of 1455 reports, 718 (49.35%) were assisted by ASR and 737 (50.65%) were not assisted by ASR. Average documentation speed without ASR was 173 (SD 101) characters per minute, while it was 217 (SD 120) characters per minute using ASR. The overall increase in documentation speed through Web-based ASR assistance was 26% (P=.04). Participants documented an average of 356 (SD 388) characters per report when not assisted by ASR and 649 (SD 561) characters per report when assisted by ASR. Participants' average mood rating was 1.3 (SD 0.6) using ASR assistance compared to 1.6 (SD 0.7) without ASR assistance (P<.001). Conclusions: We conclude that medical documentation with the assistance of Web-based speech recognition leads to an increase in documentation speed, document length, and participant mood when compared to self-typing. Speech recognition is a meaningful and effective tool for the clinical documentation process. %M 26531850 %R 10.2196/jmir.5072 %U http://www.jmir.org/2015/11/e247/ %U https://doi.org/10.2196/jmir.5072 %U http://www.ncbi.nlm.nih.gov/pubmed/26531850Fetched URL: https://www.jmir.org/article/export/end/jmir_v17i11e247
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