Elizabeth Mertz

Objectives This 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. Methods Electronic 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. Results The 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%). Conclusions The 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.

Objective There is a lack of diversity in the dental workforce. Efforts to enhance underrepresented minority (URM) recruitment and retention within dental school exist, but little effort has been made to track URM providers through education and practice. This study assesses the status of workforce diversity in the dental specialties and the predictors of URM dentist specialization. Methods The primary data used were a 2012 national sample survey of Hispanic/Latino (H/L), Black, or American Indian/Alaska Native (AI/AN) dentists in the US, supplemented by publicly available workforce data. Descriptive and multivariate statistical analyses were performed to describe the demographic composition of URM clinical general and specialist dentists and analyze changes in proportions of URMs specializing among age cohorts, differences in specific type of specialization, and racial concordance between specialists and their patients. Results The pathway continues to winnow with fewer URM dentists in specialty practice. Among all URM clinical dentists being first in his/her family to obtain a college degree, having a strong desire to work in his/her own cultural community or joining a loan repayment program due to debt load independently predicted lower odds of specialization. Alternatively, being initially foreign trained as a dentist and valuing professional training were independently predictive of higher odds of specialization. Conclusion The lack of diversity within the dental specialties is a critical flaw in our education and care delivery systems demanding clear actions toward improving the pathway into residency programs for URM students.