748 Reusing Electronic Dental Record Data Through an Ontology

Thursday, March 21, 2013: 2 p.m. - 3:15 p.m.
Location: Hall 4 (Washington State Convention Center)
Presentation Type: Poster Session
T.K.L. SCHLEYER1, A. RUTTENBERG2, W. DUNCAN3, M. HAENDEL4, C. TORNIAI4, A. ACHARYA5, M. SONG6, T. THYVALIKAKATH7, K. LIU8, and P. HERNANDEZ9, 1School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, 2State University of New York - SUNY - Buffalo, Buffalo, NY, 3State University of New York - Buffalo, Buffalo, NY, 4Oregon Health & Science University, Portland, OR, 5Marshfield Clinic, Marshfield, WI, 6Center for Dental Informatics, University of Pittsburgh, Pittsburgh, PA, 7334 Salk Hall, University of Pittsburgh, Pittsburgh, PA, 8Center for Dental Informatics, University of Pittsburgh, Pittsburgh, 9Reparto Universitario, San Juan, PR
Objective: A key question for healthcare is how to operationalize the vision of the Learning Healthcare System, in which electronic health record data become a continuous information source for quality assurance and research. The development of evidence, comparative effectiveness research, and clinical studies require analysis of data generated during clinical practice. These data are increasingly stored in electronic dental records (EDR). The purpose of this project is to develop a generalizable method for extracting and analyzing research data from EDRs.

Method: In a highly iterative and collaborative process, our team of dentists, informaticians, ontologists and clinical dental researchers developed a pilot process for extracting clinical data from Eaglesoft, a commercial EDR. We defined a set of research questions focused on restorative dentistry; constructed the Oral Health and Disease Ontology (OHD) to represent the study variables; developed mappings for the data; and created a knowledge base that used the OHD to represent clinical data.

Result: We represented data from about 4,500 patients from a single dental practice in our knowledge base. We extracted 232,270 clinical records, of which about 54,000 documented restorative, endodontic and surgical procedures. Currently, the OHD includes 213 classes and reuses 1,658 classes from other ontologies. Most of the classes created de novo were related to procedures, visits, exams and CDT codes that were not available in existing biomedical ontologies.  We have developed an initial set of queries to extract data about patients, teeth, surfaces, restorations, and findings, and are currently in the process of conducting initial statistical analyses of the data.

Conclusion: Our study is a novel application of an ontology-based approach to develop a generalizable method for extracting and reusing data from EDRs. Further work will establish a complete, open and reproducible workflow for reusing data from a variety of EDRs for research and quality assurance.

This abstract is based on research that was funded entirely or partially by an outside source: National Institute of Dental Craniofacial Research (NIDCR) 5R21DE019683-02 and National Institute of Dental Craniofacial Research (NIDCR) 1R21DE021178-01A1

Keywords: Clinical trials, Computers, Health services research, Outcome (Health) and dental informatics
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