BACKGROUND: Longitudinal patient level dataavailable in the electronic health record (EHR)allows for
the development, implementation, and validations of dental quality measures (eMeasures).
Objective We report the feasibility and validity of implementing two eMeasures. The
eMeasures determined the proportion of patients receiving a caries risk assessment (eCRA)
and corresponding appropriate risk-based preventative treatments for patients at elevated
risk of caries (appropriateness of care [eAoC]) in two academic institutions and one
accountable care organization, in the 2019 reporting year.
METHODS: Both eMeasures define the numerator and denominator beginning at the patient
level, populations’ specifications, and validated the automated queries. For eCRA, patients
who completed a comprehensive or periodic oral evaluation formed the denominator, and
patients of any age who received a CRA formed the numerator. The eAoC evaluated the
proportion of patients at elevated caries risk who received the corresponding appropriate
risk-based preventative treatments.
RESULTS: EHR automated queries identified in three sites 269,536 patients who met the inclusion
criteria for receiving a CRA. The overall proportion of patients who received a CRA was 94.4% (eCRA).
In eAoC, patients at elevated caries risk levels (moderate, high, or extreme) received fluoride
preventive treatment ranging from 56 to 93.8%. For patients at high and extreme risk, antimicrobials
were prescribed more frequently site 3 (80.6%) than sites 2 (16.7%) and 1 (2.9%).
CONCLUSION: Patient-level data available in the EHRs can be used to implement process-ofcare dental eCRA and AoC, eAoC measures identify gaps in clinical practice. EHR-based
measures can be useful in improving delivery of evidence-based preventative treatments to
reduce risk, prevent tooth decay, and improve oral health.U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Dental and Craniofacial Research.http://www.thieme.com/books-main/clinical-informatics/product/4433-aci-applied-clinical-informaticsDental Management Science
