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357 On the completeness of medical records of patients with oral health records at three CTSA CORES Institutions: Iowa, Kentucky, and Utah

Published online by Cambridge University Press:  11 April 2025

Julio Facelli
Affiliation:
University of Utah
Brenda Heaton
Affiliation:
School of Dentistry, University of Utah
Ram Gouripeddi
Affiliation:
Department of Biomedical Informatics and Clinical and Translational Science Institute, University of Utah
Luciana Shaddox
Affiliation:
College of Dentistry, University of Kentucky
Jeff Talbert
Affiliation:
Division of Biomedical Informatics, University of Kentucky
Xian Jin
Affiliation:
University of Utah
Xie
Affiliation:
Division of Biostatistics and Computational Biology, College of Dentistry and Dental Clinics, University of Iowa
Boyd Knosp
Affiliation:
Institute for Clinical and Translational Science, University of Iowa
Heath Davis
Affiliation:
Institute for Clinical and Translational Science, University of Iowa
Shareef Dabdoub
Affiliation:
Division of Biostatistics and Computational Biology, College of Dentistry and Dental Clinics, University of Iowa
Julio C. Facelli
Affiliation:
Department of Biomedical Informatics and Clinical and Translational Science Institute, University of Utah
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Abstract

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Objectives/Goals: Oral health is an important and understudied part of overall health. Poor oral health is linked to many systemic conditions, but little has been done to explore these issues in large electronic health records data sources that include dental health records. Here we report on our exploration of data readiness and completeness of three of these data sources in the Clinical and Translational Science Awards (CTSA) network. Methods/Study Population: Three CTSAs from the Consortium of Rural States (CORES) with diverse geographies, demographics, and data ecosystems can integrate medical and dental records, but it is unknown if the target population having both dental and medical records have sufficient completeness and similarity to enable dental/medical health studies. Here we use descriptive analytics to characterize the demographics, and the “complete data” approach presented by Weber et al. to evaluate differences between the completeness of the general populations and the one having both dental/medical records. We accomplish this by identifying patients with dental records in commonly used research networks and performing empirical patient statistics in comparison to the entire population available at the three institutions. Results/Anticipated Results: This poster will present the results of using the Weber et al. approach to compare the completeness of records of the general patient population in the Iowa, Kentucky, and Utah medical/dental health care systems to those for which they have also dental records. The completeness of the records of these two subpopulations is also associated with different demographic characteristics, as it has been established that the populations served by the dental clinics is biased by dental insurance considerations. The work will show what retrospective studies can (or not) be done using these populations when taking into account that it is well established that studies of populations with different level of completeness can be inconsistent. Discussion/Significance of Impact: This study provides an informatics framework to assess similarity and completeness of patient records with and without dental records. Establishing the level of similarity and completeness in these patient populations is critical to justify the validity of studies that utilize a combined record.

Type
Informatics, AI and Data Science
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2025. The Association for Clinical and Translational Science