Evaluating quality of dental care among patients with diabetes
| Autor: | Kristen Simmons, Alfa Yansane, Muhammad F. Walji, Elsbeth Kalenderian, Joanna Mullins, Joshua B. Even, Joel M. White, Bunmi Tokede, Suhasini Bangar, Ram Vaderhobli, Ana Neumann, Krishna Kumar Kookal, Jini Etolue, Rachel L. Ramoni, Shwetha V. Kumar |
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| Rok vydání: | 2017 |
| Předmět: |
Measure (data warehouse)
Pathology medicine.medical_specialty business.industry media_common.quotation_subject 030206 dentistry Health records medicine.disease Dental care 03 medical and health sciences 0302 clinical medicine health services administration Diabetes mellitus Positive predicative value medicine Quality (business) Medical physics 030212 general & internal medicine Adaptation (computer science) business General Dentistry Practical implications health care economics and organizations media_common |
| Zdroj: | The Journal of the American Dental Association. 148:634-643.e1 |
| ISSN: | 0002-8177 |
| DOI: | 10.1016/j.adaj.2017.04.017 |
| Popis: | Background Patients with diabetes are at increased risk of developing oral complications, and annual dental examinations are an endorsed preventive strategy. The authors evaluated the feasibility and validity of implementing an automated electronic health record (EHR)–based dental quality measure to determine whether patients with diabetes received such evaluations. Methods The authors selected a Dental Quality Alliance measure developed for claims data and adapted the specifications for EHRs. Automated queries identified patients with diabetes across 4 dental institutions, and the authors manually reviewed a subsample of charts to evaluate query performance. After assessing the initial EHR measure, the authors defined and tested a revised EHR measure to capture better the oral care received by patients with diabetes. Results In the initial and revised measures, the authors used EHR automated queries to identify 12,960 and 13,221 patients with diabetes, respectively, in the reporting year. Variations in the measure scores across sites were greater with the initial measure (range, 36.4-71.3%) than with the revised measure (range, 78.8-88.1%). The automated query performed well (93% or higher) for sensitivity, specificity, and positive and negative predictive values for both measures. Conclusions The results suggest that an automated EHR-based query can be used successfully to measure the quality of oral health care delivered to patients with diabetes. The authors also found that using the rich data available in EHRs may help estimate the quality of care better than can relying on claims data. Practical Implications Detailed clinical patient-level data in dental EHRs may be useful to dentists in evaluating the quality of dental care provided to patients with diabetes. |
| Databáze: | OpenAIRE |
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