Colorectal Cancer Clinical Trial
Official title:
Pilot Implementation Study of a Default Genetics Referral Process for Patients With Young-Onset Colorectal Cancer
The investigators will perform a pilot implementation study of a default genetics referral process among patients with young-onset CRC diagnosed between ages 40 and 49.
The incidence of young-onset colorectal cancer (CRC) - defined as a diagnosis of CRC prior to age 50 - has increased at alarming rates in recent years. Over 75% of cases occur in patients diagnosed between 40-49 years old, a group that is not traditionally included in young adult cancer initiatives tailored only to patients up to 39 years of age. Young age of CRC onset is a defining feature of hereditary CRC syndromes; as such, the National Comprehensive Cancer Network and American College of Medical Genetics and Genomics recommend germline genetics evaluations for all patients diagnosed with CRC under the age of 50. However, multiple studies have shown suboptimal rates and racial and socioeconomic disparities in guideline-recommended genetics evaluations. In this pilot implementation study, the investigators aim to develop, implement, and evaluate the effects of a default genetics referral process among patients with young-onset CRC diagnosed between 40-49 years old. The investigators hypothesize that by applying defaults, or pre-selected choices, to minimize the cognitive effort that patients and clinicians use to make decisions, default referrals will improve rates of genetics referrals while reducing existing racial and socioeconomic disparities. The investigators will implement this intervention at five academic and community hospitals within Penn Medicine that serve a racially, socioeconomically, and geographically diverse patient population. The investigators will use an automated electronic health record-based algorithm to identify eligible patients, after which default referrals for genetic risk evaluation will be made unless patients or their oncology clinicians opt out. The investigators will rigorously evaluate the impact of this default genetics referral process using mixed methods leveraging models and frameworks from the field of implementation science. ;
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