Journal article
Finding buried genetic test results in the electronic health record is inefficient and variable across institutions
Therapeutic advances in rare disease, Vol.6, pp.1-13
01/2025
DOI: 10.1177/26330040251356521
PMCID: PMC12254648
PMID: 40657271
Abstract
Background:
The absence of standardized approaches for handling genetic test results in electronic health records (EHRs), combined with a lack of diagnostic codes for most rare disorders, hinders accurate and timely identification of patients with rare genetic variants. This impedes access to research opportunities and genomic-driven care. To reduce the diagnostic odyssey, identify research-eligible subjects, and ultimately enhance patient care, it is critical to optimize approaches to retrieve genetic results.
Objectives:
To characterize resource requirements, yield, and biases among methods for identifying and retrieving genetic test results across 11 Intellectual and Developmental Disability Research Centers (IDDRC).
Design:
A survey was used to collect details from the authors on approaches to identify EHRs from patients who had genetic testing and variants of interest were reported; surveys were completed in 2022.
Methods:
Strengths and limitations in approaches to identify and retrieve genetic test results conducted from the implementation of EHR systems were evaluated. A standard template was used to collect genetic testing storage formats, methods to identify patients with rare disease variants, estimates of time/cost, nature of accessed data, method-specific bias in types of American College of Medical Genetics and Genomics classified variants identified. When possible, precision when performing gene name searches in the EHR was calculated.
Results:
Four approaches were used: (1) manual searches, reviews, and extractions, (2) natural language processing software-aided manual reviews and extractions, (3) custom databases via testing lab collaborations, and (4) testing EHR vendor-designed genomics modules. The fully manual approach required minimal infrastructure and allowed access to clinical notes but missed variants of unknown clinical significance. Precision for gene name matches based on searches of 59 genes was 0.16. Natural language processing software minimized effort but required considerable informatics support. Custom databases and EHR vendor modules necessitated substantial computational support; however, genetic testing results retrieval was efficient.
Conclusion:
Leveraging the IDDRC network, we found that methods to store, search and extract genetic testing results vary widely, especially regarding older test results, and have distinct benefits and limitations. Limitations are best addressed through practice guidelines that standardize storage and retrieval of genetic test results to facilitate efficient identification of research eligible subjects and genomic-informed patient care.
Details
- Title: Subtitle
- Finding buried genetic test results in the electronic health record is inefficient and variable across institutions
- Creators
- Olivia J. Veatch - University of Kansas Medical CenterJomol Mathew - University of Wisconsin–MadisonShira Rockowitz - Boston Children's HospitalDustin Baldridge - Washington University in St. LouisAlyssa Wetzel - University of IowaMaria Niarchou - Vanderbilt University Medical CenterMegan Clarke - Albert Einstein College of MedicinePrabhu Shankar - University of California, DavisSuma Shankar - University of California, DavisJulie S. Cohen - Kennedy Krieger InstituteKendell German - University of WashingtonSeth Berger - Children's NationalAngela Sellitto - Washington University in St. LouisInez Y. Oh - Washington University in St. LouisRashi Raizada - Albert Einstein College of MedicinePiotr Sliz - Boston Children's HospitalSelvin Soby - Albert Einstein College of MedicineMihailo Kaplarevic - Children's NationalDan Doherty - University of WashingtonAndrea Gropman - Children's NationalConstance Smith-Hicks - Kennedy Krieger InstituteJeffrey L. Neul - Vanderbilt University Medical CenterVirginia Lanzotti - Washington University in St. LouisBenjamin Darbro - University of IowaQiang Chang - University of Wisconsin–MadisonMustafa Sahin - Boston Children's HospitalMaya Chopra - Boston Children's Hospital
- Resource Type
- Journal article
- Publication Details
- Therapeutic advances in rare disease, Vol.6, pp.1-13
- DOI
- 10.1177/26330040251356521
- PMID
- 40657271
- PMCID
- PMC12254648
- NLM abbreviation
- Ther Adv Rare Dis
- ISSN
- 2633-0040
- eISSN
- 2633-0040
- Publisher
- SAGE Publications
- Grant note
- P50HD105353 / ; MCHT7317245 / ; P50HD103556 / ; P50HD103524 / ; P50HD103537 / ; P50HD105328 / ; P50HD105352 / ; R21HD107535 / ; P50HD105351 / ; UL1TR002366 / ;
- Language
- English
- Date published
- 01/2025
- Academic Unit
- Stead Family Department of Pediatrics; Medical Genetics and Genomics
- Record Identifier
- 9984848113502771
Metrics
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