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Dental clinical research: an illustration of the value of standardized diagnostic terms

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2015

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John Wiley and Sons Inc.
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Kalenderian, Elsbeth, Bunmi Tokede, Rachel Ramoni, Maria Khan, Nicole Kimmes, Joel White, Ram Vaderhobli, Alfa Yansane, Albert Feilzer, and Muhammad Walji. 2015. “Dental clinical research: an illustration of the value of standardized diagnostic terms.” Journal of Public Health Dentistry 76 (2): 152-156. doi:10.1111/jphd.12124. http://dx.doi.org/10.1111/jphd.12124.

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Abstract

Abstract Objective: Secondary data are a significant resource for in‐depth epidemiologic and public health research. It also allows for effective quality control and clinical outcomes measurement. To illustrate the value of structured diagnostic entry, a use case was developed to quantify adherence to current practice guidelines for managing chronic moderate periodontitis (CMP). Methods: Six dental schools using the same electronic health record (EHR) contribute data to a dental data repository (BigMouth) based on the i2b2 data‐warehousing platform. Participating institutions are able to query across the full repository without being able to back trace specific data to its originating institution. At each of the three sites whose data are included in this analysis, the Dental Diagnostic System (DDS) terminology was used to document diagnoses in the clinics. We ran multiple queries against this multi‐institutional database, and the output was validated by manually reviewing a subset of patient charts. Results: Over the period under study, 1,866 patients were diagnosed with CMP. Of these, 15 percent received only periodontal prophylaxis treatment, 20 percent received only periodontal maintenance treatment, and only 41 percent received periodontal maintenance treatment in combination with other AAP guideline treatments. Conclusions: Our results showed that most patients with CMP were not treated according to the AAP guidelines. On the basis of this use case, we conclude that the availability and habitual use of a structured diagnosis in an EHR allow for the aggregation and secondary analyses of clinical data to support downstream analyses for quality improvement and epidemiological assessments.

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Original Article, clinical practice guidelines, diagnostic systems, dental public health, epidemiology, clinical outcomes, evidence‐based dentistry

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