Typically, when using practice management systems (PMS), dentists perform data entry by utilizing an assistant as a transcriptionist. This prevents dentists from interacting directly with the PMSs. Speech recognition interfaces can provide the solution to this problem. Existing speech interfaces of PMSs are cumbersome and poorly designed. In dentistry, there is a desire and need for a usable natural language interface for clinical data entry.
Objectives. (1) evaluate the efficiency, effectiveness, and user satisfaction of the speech interfaces of four dental PMSs, (2) develop and evaluate a speech-to-chart prototype for charting naturally spoken dental exams.
Methods. We evaluated the speech interfaces of four leading PMSs. We manually reviewed the capabilities of each system and then had 18 dental students chart 18 findings via speech in each of the systems. We measured time, errors, and user satisfaction. Next, we developed and evaluated a speech-to-chart prototype which contained the following components: speech recognizer; post-processor for error correction; NLP application (ONYX) and; graphical chart generator. We evaluated the accuracy of the speech recognizer and the post-processor. We then performed a summative evaluation on the entire system. Our prototype charted 12 hard tissue exams. We compared the charted exams to reference standard exams charted by two dentists.
Results. Of the four systems, only two allowed both hard tissue and periodontal charting via speech. All interfaces required using specific commands directly comparable to using a mouse. The average time to chart the nine hard tissue findings was 2:48 and the nine periodontal findings was 2:06. There was an average of 7.5 errors per exam. We created a speech-to-chart prototype that supports natural dictation with no structured commands. On manually transcribed exams, the system performed with an average 80% accuracy. The average time to chart a single hard tissue finding with the prototype was 7.3 seconds. An improved discourse processor will greatly enhance the prototypes accuracy.
Conclusions. The speech interfaces of existing PMSs are cumbersome, require using specific speech commands, and make several errors per exam. We successfully created a speech-to-chart prototype that charts hard tissue findings from naturally spoken dental exams.
| Identifer | oai:union.ndltd.org:PITT/oai:PITTETD:etd-12012009-163519 |
| Date | 11 January 2010 |
| Creators | Irwin, Regina (Jeannie) Yuhaniak |
| Contributors | Wendy Webber Chapman, Peter Haug, Titus Schleyer, Brian Chapman, Heiko Spallek |
| Publisher | University of Pittsburgh |
| Source Sets | University of Pittsburgh |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.library.pitt.edu/ETD/available/etd-12012009-163519/ |
| Rights | restricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University of Pittsburgh or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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