Tiwari Tamanna, Kondratenko Maxim, Nasiha Nihmath, Ong Toan, Chandrasekaran Sangeetha, Kostbade Gary, Giano Zachary
School of Dental Medicine, University of Colorado, Aurora, CO, United States.
Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.
Front Oral Health. 2025 Jun 3;6:1535164. doi: 10.3389/froh.2025.1535164. eCollection 2025.
The BigMouth Dental Data Repository is an oral health database developed from de-identified electronic health record (EHR) data from eleven dental schools within the United States. To better understand how this database can be used for further research, the repository must be analyzed for data quality, such as accuracy, consistency, and completeness. This study determined the completeness of all patient health records between 2017 and 2019, including demographic, dental, behavioral, and health history variables at the students, faculty, and resident level.
This study analyzed demographic (age, gender, race/ethnicity, zip code, insurance), dental (pain ratings), behavioral (tobacco, alcohol, and drug use), and health history variables for completeness. ANOVA was conducted to detect differences in providers collecting data by year (using Tukey differences at < .05). Effect sizes are presented by comparing students to all other provider types.
Overall, the data showed high completeness in demographic variables (97.6%-99.9% for age, gender, and zip code) among the total sample of 543,363 patient visits. However, lower completeness rates were found in dental and behavioral variables (ranging from 1.5% to 66.1%), suggesting potential limitations for certain research applications. The study found significant differences in the completeness of records between students, faculty, and residents. In demographic variables, students demonstrated significantly higher completeness rates than faculty across the years 2017-2019, with 79.8%, 79%, and 78.8% completeness for race/ethnicity records, respectively. Furthermore, residents and faculty exhibited significantly higher completeness rates (76.8% and 86.7%, respectively) in insurance information compared to students (56.7%). Notably, students showcased greater completeness percentages in variables related to tobacco use, alcohol use, drug use, and health history compared to both faculty and residents.
This study underscores significant variations in the completeness of EHR data among students, faculty, and residents across different schools. Despite these variances, the overall findings suggest a robust level of completeness in the demographic and health variables within the dataset.
“大嘴牙科数据仓库”是一个口腔健康数据库，它由美国11所牙科学校的去识别化电子健康记录（EHR）数据开发而成。为了更好地理解该数据库如何用于进一步的研究，必须对该仓库进行数据质量分析，如准确性、一致性和完整性。本研究确定了2017年至2019年间所有患者健康记录的完整性，包括学生、教师和住院医师层面的人口统计学、牙科、行为和健康史变量。
本研究分析了人口统计学（年龄、性别、种族/族裔、邮政编码、保险）、牙科（疼痛评级）、行为（烟草、酒精和药物使用）和健康史变量的完整性。进行方差分析以检测按年份收集数据的提供者之间的差异（使用Tukey差异，p<0.05）。通过将学生与所有其他提供者类型进行比较来呈现效应大小。
总体而言，在543,363次患者就诊的总样本中，数据显示人口统计学变量的完整性较高（年龄、性别和邮政编码的完整性为97.6%-99.9%）。然而，在牙科和行为变量中发现较低的完整性率（范围为1.5%至66.1%），这表明某些研究应用可能存在局限性。该研究发现学生、教师和住院医师之间记录的完整性存在显著差异。在人口统计学变量中，2017年至2019年期间，学生的完整性率显著高于教师，种族/族裔记录的完整性分别为79.8%、79%和78.8%。此外，与学生（56.7%）相比，住院医师和教师在保险信息方面的完整性率显著更高（分别为76.8%和86.7%）。值得注意的是，与教师和住院医师相比，学生在与烟草使用、酒精使用、药物使用和健康史相关的变量中展示出更高的完整性百分比。
本研究强调了不同学校的学生、教师和住院医师之间EHR数据完整性的显著差异。尽管存在这些差异，但总体研究结果表明数据集中人口统计学和健康变量的完整性水平较高。
