early detection of genetic risk (edge)

Conditions: Genetic Predisposition

Summary: the study intervention involves having patients complete a familial cancer risk assessment survey. those who are found to be at high risk will be offered genetic testing for a panel of hereditary cancers. a "previvor" plan will be created to assist patients and their providers in completing the appropriate follow-up for those with a mutation identified.

current practice guidelines from acmg (american college of medical genetics and genomics) provide referral indications for cancer predisposition assessment. identifying patients with high genetic risk for breast, ovary, colon, or other cancers has important clinical ramifications for an individual's healthcare, but genetic risk if often not identified because of testing barriers at several levels. barriers at the provider level include inadequacies in risk recognition, patient referrals and availability of genetic professionals to provide counseling in a traditional testing paradigm. barriers at the level of the patient include poor understanding of the availability and benefits of testing and inadequate access to testing services. how to best implement appropriate genomic testing and follow-up care into an operating healthcare system is not known. issues of communication, clinical flow, reportable actions, and transmission of information and support are of critical importance, and must change and grow to accommodate the new information contained within genomic testing. studies to date of the implementation process have been conducted in high resourced facilities, under optimal conditions, often not at the system level. aims include: 1. compare the efficacy and implementation of two strategies for identifying members of a primary care clinic's population who have a family or personal history of cancer and offering high-risk individuals to obtain genetic testing for cancer susceptibility mutations in a randomized trial. the two methods are: 1) point of care (poc) approach: a tablet-based screening for family/personal history of cancer will be offered to all patients aged 25 and up coming in for a routine appointment at the clinic. 2) direct patient engagement (dpe): emails and letters will be sent to all individuals aged 25 and older in a clinic's population, inviting them to visit a web site for screening for family /personal history of cancer. in both strategies, those determined to be high-risk will receive online education about genetic testing and an invitation to obtain such testing through a web-based platform. randomization will occur at the clinic level, with half of the clinics using the poc approach and the other half using dpe. outcomes will be the fraction of the active clinic patient population that completes screening and the fraction of the active clinic patient population that undergoes testing. hypothesis 1: dpe screening will result in a higher proportion of active patients who screen for familial cancer risk compared with poc screening. hypothesis 2: of screened patients, poc patients will produce a higher proportion of tested patients compared with dpe. 2. identify changes, problems, and inefficiencies in clinical flow and interactions during and after the implementation of genomic testing for cancer risk across primary care clinics. 3. evaluate the effects of two methods of implementation of genomic screening for cancer risk on patient, provider, and health system leader reports of benefits and harms, satisfaction, perceived quality of care, including across gender, racial/ethnic, socioeconomic, and genetic literacy divides. 4. evaluate the value (cost-effectiveness) and affordability (budget impact) of each screening strategy.

Eligibility criteria:
inclusion criteria for patients: * age 25 or older * an active patient at a participating clinic (had at least one visit in the past 12 months) * comfortable reading and writing in english exclusion criteria: * those who do not meet inclusion criteria.

Keywords: primary care genetic testing risk assessment hereditary cancer implementation