Abstract
ObjectiveDevelop and validate an initial content taxonomy for patient records in general dentistry. MethodsPhase 1 – obtain 95 de-identified patient records from 11 general dentists in the United States. Phase 2 – extract individual data fields (information items), both explicit (labeled) and implicit (unlabeled), from records, and organize into categories mirroring original field context. Phase 3 – refine raw list of information items by eliminating duplicates/redundancies and focusing on general dentistry. Phase 4 – validate all items regarding inclusion and importance using a two-round Delphi study with a panel of 22 general dentists active in clinical practice, education, and research. ResultsAnalysis of 76 patient records from 9 dentists, combined with previous work, yielded a raw list of 1509 information items. Refinement reduced this list to 1107 items, subsequently rated by the Delphi panel. The final model contained 870 items, with 761 (88%) rated as mandatory. In Round 1, 95% (825) of the final items were accepted, in Round 2 the remaining 5% (45). Only 45 items on the initial list were rejected and 192 (or 17%) remained equivocal. ConclusionGrounded in the reality of clinical practice, our proposed content taxonomy represents a significant advance over existing guidelines and standards by providing a granular and comprehensive information representation for general dental patient records. It offers a significant foundational asset for implementing an interoperable health information technology infrastructure for general dentistry.
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