Systematically assessing the quality of dental electronic health record data for an investigation into oral health care disparities

Author:

Kookal Krishna Kumar1,Walji Muhammad F.2,Brandon Ryan3ORCID,Kivanc Ferit3,Mertz Elizabeth4ORCID,Kottek Aubri4,Mullins Joanna3,Liang Shuang4,Jenson Larry E.4,White Joel M.4ORCID

Affiliation:

1. Technology Services and Informatics, School of Dentistry University of Texas Health Science Center at Houston Houston Texas USA

2. Department of Clinical and Health Informatics, D. Bradley McWIlliams School of Biomedical Informatics University of Texas Health Science Center at Houston Houston Texas USA

3. Willamette Dental Group and Skourtes Institute Hillsboro Oregon USA

4. Department of Preventive and Restorative Dental Sciences University of California San Francisco California USA

Abstract

AbstractObjectivesThis work describes the process by which the quality of electronic health care data for a public health study was determined. The objectives were to adapt, develop, and implement data quality assessments (DQAs) based on the National Institutes of Health Pragmatic Trials Collaboratory (NIHPTC) data quality framework within the three domains of completeness, accuracy, and consistency, for an investigation into oral health care disparities of a preventive care program.MethodsElectronic health record data for eligible children in a dental accountable care organization of 30 offices, in Oregon, were extracted iteratively from January 1, 2014, through March 31, 2022. Baseline eligibility criteria included: children ages 0–18 with a baseline examination, Oregon home address, and either Medicaid or commercial dental benefits at least once between 2014 and 2108. Using the NIHPTC framework as a guide, DQAs were conducted throughout data element identification, extraction, staging, profiling, review, and documentation.ResultsThe data set included 91,487 subjects, 11 data tables comprising 75 data variables (columns), with a total of 6,861,525 data elements. Data completeness was 97.2%, the accuracy of EHR data elements in extracts was 100%, and consistency between offices was strong; 29 of 30 offices within 2 standard deviations of the mean (s = 94%).ConclusionsThe NIHPTC framework proved to be a useful approach, to identify, document, and characterize the dataset. The concepts of completeness, accuracy, and consistency were adapted by the multidisciplinary research team and the overall quality of the data are demonstrated to be of high quality.

Funder

National Institutes of Health

Publisher

Wiley

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