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Exploring Factors That Impact Genetic Counseling Referral and Uptake Using Learning Health Approaches

Year: 2025
Type: article
Study design: Observational Study
Abstract: ABSTRACT Introduction Germline testing and pretest genetic counseling are advised for many cancer patients, yet not all receive these services. Electronic Health Records (EHRs) offer a valuable resource to measure referral to genetic counseling (referral receipt) and uptake (completion of counseling). This study uses EHR data to assess demographic factors influencing genetic counseling referral and uptake among prostate cancer patients, serving as a learning health system model. Methods We included prostate cancer patients who met germline testing and counseling criteria at an NCI‐designated cancer center from January 1, 2018, to June 30, 2022. Demographic factors—age at diagnosis, race, employment, insurance, and geographic region—were assessed for associations with genetic counseling referral and uptake. Analyses involved descriptive statistics, two‐group comparisons, and regression models. Results Among 356 prostate cancer patients, only 34.2% received genetic counseling referrals, and of these, 73% completed a counseling visit. Older patients were less likely to receive referrals (OR = 0.93, 95% CI [0.89–0.97]) and complete visits (OR = 0.92, 95% CI [0.87–0.96]). Patients employed full‐time were more likely to receive referrals (39.2% vs. 23.1%; p = 0.01), while White (93% vs. 81%; p = 0.047) and rural patients (42.7% vs. 6.1%; p = 0.02) had higher uptake. Insurance status did not significantly affect referral or uptake. Conclusion This study demonstrates the potential of EHRs to identify demographic disparities in genetic counseling services. Using a learning health system approach, healthcare institutions can leverage EHR data to design targeted interventions aimed at improving access and reducing disparities in genetic services, ultimately enhancing patient outcomes.
Language: English
Subfield: Genetics
Open Access status: gold
Estimated APC paid: $2,500
OpenAlex ID: W4417025582
FWCI:
Cites: 39
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