Comparison of accuracy captured by different controlled languages in oral pathology diagnoses.

This project was comparing the accuracy of capturing the oral pathology diagnoses among different coding systems. 55 diagnoses were selected for comparison among 5 coding systems. The results of accuracy in capturing oral diagnoses are: AFIP (96.4%), followed by Read 99 (85.5%), SNOMED 98 (74.5%), ICD-9 (43.6%), and CDT-3 (14.5%). It shows that the currently used coding systems, ICD-9 and CDT-3, were inadequate, whereas the AFIP coding system captured the majority of oral diagnoses. In conclusion, the most commonly used medical and dental coding systems lack terms for the diagnosis of oral and dental conditions.

DEVELOPING A METHOD FOR IDENTIFYING AND REDUCING FUNCTIONAL DISCREPANCIES OF INFORMATION SYSTEMS

Currently more than half of Electronic Health Record (EHR) projects fail. Most of these failures are not due to flawed technology, but rather due to the lack of systematic considerations of human issues. Among the barriers for EHR adoption, function mismatching among users, activities, and systems is a major area that has not been systematically addressed from a human-centered perspective. A theoretical framework called Functional Framework was developed for identifying and reducing functional discrepancies among users, activities, and systems. The Functional Framework is composed of three models – the User Model, the Designer Model, and the Activity Model. The User Model was developed by conducting a survey (N = 32) that identified the functions needed and desired from the user’s perspective. The Designer Model was developed by conducting a systemic review of an Electronic Dental Record (EDR) and its functions. The Activity Model was developed using an ethnographic method called shadowing where EDR users (5 dentists, 5 dental assistants, 5 administrative personnel) were followed quietly and observed for their activities. These three models were combined to form a unified model. From the unified model the work domain ontology was developed by asking users to rate the functions (a total of 190 functions) in the unified model along the dimensions of frequency and criticality in a survey. The functional discrepancies, as indicated by the regions of the Venn diagrams formed by the three models, were consistent with the survey results, especially with user satisfaction. The survey for the Functional Framework indicated the preference of one system over the other (R=0.895). The results of this project showed that the Functional Framework provides a systematic method for identifying, evaluating, and reducing functional discrepancies among users, systems, and activities. Limitations and generalizability of the Functional Framework were discussed.