Assessing the completeness of periodontal disease documentation in the EHR: a first step in measuring the quality of care

• Published in: BMC oral health Vol. 21; no. 1; p. 282
• Main Authors: Mullins, Joanna, Yansane, Alfa, Kumar, Shwetha V, Bangar, Suhasini, Neumann, Ana, Johnson, Todd R, Olson, Gregory W, Kookal, Krishna Kumar, Sedlock, Emily, Kim, Aram, Mertz, Elizabeth, Brandon, Ryan, Simmons, Kristen, White, Joel M, Kalenderian, Elsbeth, Walji, Muhammad F
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 29.05.2021; BioMed Central; BMC
• Subjects: Age; Automation; Care and treatment; Clinical outcomes; Dental care; Dental quality measures (DQMs); Dentistry; Dentists; Diabetes; Diabetes mellitus; Diagnosis; Documentation; EHR; Electronic Health Records; Electronic medical records; Electronic records; Gum disease; Humans; Medical care; Medical records; Patient Compliance; Patients; Performance evaluation; Periodontal disease; Periodontal diseases; Periodontal Diseases - diagnosis; Periodontal risk assessment; Quality; Quality management; Quality of care; Risk assessment; Risk factors; Structured Query Language-SQL; Tobacco; Value; United States; Value; Periodontal disease; Dental quality measures (DQMs); Periodontal risk assessment; Quality; EHR
• ISSN: 1472-6831; 1472-6831
• DOI: 10.1186/s12903-021-01633-w

Our objective was to measure the proportion of patients for which comprehensive periodontal charting, periodontal disease risk factors (diabetes status, tobacco use, and oral home care compliance), and periodontal diagnoses were documented in the electronic health record (EHR). We developed an EHR-based quality measure to assess how well four dental institutions documented periodontal disease-related information. An automated database script was developed and implemented in the EHR at each institution. The measure was validated by comparing the findings from the measure with a manual review of charts. The overall measure scores varied significantly across the four institutions (institution 1 = 20.47%, institution 2 = 0.97%, institution 3 = 22.27% institution 4 = 99.49%, p-value < 0.0001). The largest gaps in documentation were related to periodontal diagnoses and capturing oral homecare compliance. A random sample of 1224 charts were manually reviewed and showed excellent validity when compared with the data generated from the EHR-based measure (Sensitivity, Specificity, PPV, and NPV > 80%). Our results demonstrate the feasibility of developing automated data extraction scripts using structured data from EHRs, and successfully implementing these to identify and measure the periodontal documentation completeness within and across different dental institutions.