Leveraging Electronic Dental Record Data for Clinical Research in the National Dental PBRN Practices

Appl Clin Inform. 2020 Mar;11(2):305-314. doi: 10.1055/s-0040-1709506. Epub 2020 Apr 29.

Abstract

Objectives: The aim of this study is to determine the feasibility of conducting clinical research using electronic dental record (EDR) data from U.S. solo and small-group general dental practices in the National Dental Practice-Based Research Network (network) and evaluate the data completeness and correctness before performing survival analyses of root canal treatment (RCT) and posterior composite restorations (PCR).

Methods: Ninety-nine network general dentistry practices that used Dentrix or EagleSoft EDR shared de-identified data of patients who received PCR and/or RCT on permanent teeth through October 31, 2015. We evaluated the data completeness and correctness, summarized practice, and patient characteristics and summarized the two treatments by tooth type and arch location.

Results: Eighty-two percent of practitioners were male, with a mean age of 49 and 22.4 years of clinical experience. The final dataset comprised 217,887 patients and 11,289,594 observations, with the observation period ranging from 0 to 37 years. Most patients (73%) were 18 to 64 years old; 56% were female. The data were nearly 100% complete. Eight percent of observations had incorrect data, such as incorrect tooth number or surface, primary teeth, supernumerary teeth, and tooth ranges, indicating multitooth procedures instead of PCR or RCT. Seventy-three percent of patients had dental insurance information; 27% lacked any insurance information. While gender was documented for all patients, race/ethnicity was missing in the dataset.

Conclusion: This study established the feasibility of using EDR data integrated from multiple distinct solo and small-group network practices for longitudinal studies to assess treatment outcomes. The results laid the groundwork for a learning health system that enables practitioners to learn about their patients' outcomes by using data from their own practice.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Child
  • Child, Preschool
  • Data Mining
  • Dentistry*
  • Electronic Health Records*
  • Female
  • Humans
  • Infant
  • Male
  • Middle Aged
  • Young Adult