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

Abstract

ObjectiveSecondary 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).MethodsSix 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.ResultsOver 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.ConclusionsOur 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.

The patient‐centered dental home: A standardized definition for quality assessment, improvement, and integration

“…These include separate medical and dental electronic health record systems; lack of physical, geographical, and organizational alignment of medical and dental providers; and separate medical and dental insurance and financing systems . For both dental health services research and cross‐system communication, a particular challenge has been the lack of consistent use and structured recording of diagnostic codes into clinical and administrative databases in dentistry . Diagnostic codes are standard data elements in medical databases but not in dental databases.…”

“…35,36 For both dental health services research and crosssystem communication, a particular challenge has been the lack of consistent use and structured recording of diagnostic codes into clinical and administrative databases in dentistry. 37 Diagnostic codes are standard data elements in medical databases but not in dental databases. Diagnostic codes are integral for measuring health outcomes and identifying patients who would most benefit from care coordination, including the type of care coordination needed.…”

Adoption of dental innovations

“…This lack of and variable adoption is a frustrating truth given the multitude of benefits that would follow from the broad use of a standardized terminology. 37-41 …”

“…42 Through BigMouth and the use of the DDS terminology, we also have been able to quantify adherence to practice guidelines for managing chronic moderate periodontitis. 41 We readily were able to determine that a full 15% of patients with a diagnosis of chronic moderate periodontitis received only prophylaxis, which is below the standard of care set by the American Academy of Periodontology. This is just the tip of the iceberg: Vast knowledge can be extracted efficiently from clinical data if the health care system is instrumented properly.…”

Using big data to promote precision oral health in the context of a learning healthcare system

“…Taiwan Data from the Taiwanese Nationwide Oral Cancer Screening Program were mined to determine the relationship between anatomic site of oral cancer and its staging and mortality 36 Nalilah et al, 2013 USA The Nationwide Emergency Department Sample database was mined to discover the relationship between mental illness and dental disease 37 Boland et al, 2013 USA EHRs from the Columbia University College of Dental Medicine were linked to medical records of the same patients at a nearby hospital and analyzed in order to identify associations between medical and dental diseases 41 Kalenderian et al, 2016 USA Data from the BigMouth data repository were queried for patients diagnosed with chronic moderate periodontitis and analyzed for the percentage that received treatment that followed current evidence-based guidelines 42…”