Open AccessCaries Risk Documentation And Prevention: eMeasures For Dental Electronic Health Records
Author(s) -
Suhasini Bangar,
Aeumann,
Joel M. White,
Alfa Yansane,
Todd R. Johnson,
Greg Olson,
Shria Kumar,
Krishna Kumar Kookal,
Aram Kim,
Enihomo ObadanUdoh,
Elizabeth Mertz,
Kristen Simmons,
Joanna Mullins,
Ryan Brandon,
Muhammad F. Walji,
Elsbeth Kalenderian
Publication year - 2022
Publication title -
applied clinical informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 27
ISSN - 1869-0327
DOI - 10.1055/s-0041-1740920
Subject(s) - medicine , documentation , electronic health record , dental care , risk assessment , health records , family medicine , health care , computer science , computer security , economics , programming language , economic growth
Background Longitudinal patient level data available 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-of-care 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.