Appl Clin Inform 2018; 09(03): 635-645
DOI: 10.1055/s-0038-1667331
Research Article
Georg Thieme Verlag KG Stuttgart · New York

Adoption of Electronic Dental Records: Examining the Influence of Practice Characteristics on Adoption in One State

Zain Chauhan
1  Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, University of Miami, Miami, Florida, United States
2  Center for Medicine, Health, and Society, Vanderbilt University, Nashville, Tennessee, United States
Mohammad Samarah
3  Computer Science and Big Data Analytics, Florida Polytechnic University, Lakeland, Florida, United States
Kim M. Unertl
4  Department of Biomedical Informatics, Vanderbilt University School of Medicine, Vanderbilt University, Nashville, Tennessee, United States
Martha W. Jones
2  Center for Medicine, Health, and Society, Vanderbilt University, Nashville, Tennessee, United States
› Author Affiliations
Further Information

Publication History

02 May 2018

25 June 2018

Publication Date:
15 August 2018 (online)


Objective Compared with medicine, less research has focused on adoption rates and factors contributing to the adoption of electronic dental records (EDRs) and certified electronic health records (EHRs) in the field of dentistry. We ran two multivariate models on EDR adoption and certification-capable EHR adoption to determine environmental and organizational factors associated with adoption.

Methods We conducted telephone survey of a 10-item questionnaire using disproportionate stratified sampling procedure of 149 dental clinics in Tennessee in 2017 measuring adoption of dental information technology (IT) (EDRs and certification-capable EHRs) and practice characteristics, including region, rurality, specialty, and practice size. We used binomial logistic regression models to determine associations of adoption with predictor variables.

Results A total of 77% of surveyed dental clinics in Tennessee had adopted some type of EDR system. When the definitions of certification capable were applied, the adoption rates in dental clinics dropped to 58%. A binomial logistic regression model for the effects of rurality, specialization, and practice size on the likelihood that a clinic would adopt an EHR product was statistically significant (chi-square (3) = 12.41, p = 0.0061). Of the three predictor variables, specialization and practice size were significant: Odds of adopting an EHR is 67% lower for specialists than for general dentists; and clinics with two or more practicing dentists were associated with a much greater likelihood of adopting an EHR-capable system (adjusted odds ratio = 3.09, p = 0.009).

Conclusion Findings from this study indicate moderate to high levels of overall dental IT adoption. However, adoption rates in dental clinics do remain lower than those observed in office-based physician practices in medicine. Specialization and practice size were significant predictors of EHR-capable system adoption. Efforts to increase EHR adoption in dentistry should be mindful of potential disparities in smaller practices and between dental specialties and generalists.

Protection of Human and Animal Subjects

Interviews were administered by the authors with data collection and analysis procedures approved by the Vanderbilt University's Institutional Review Board for the protection of human subjects.