Lynch syndrome (LS) is an inherited cancer syndrome which significantly increases a carriers lifetime risk of several cancers, most notably colorectal cancer (CRC). There are an estimated 19, 040 carriers in NSW , with approximately 1:250 people carrying the gene fault associated with LS. Recent Australian data has shown that up to 54% of CRC patients with suspicious LS phenotypes were not referred for genetic testing. Evidence indicates that hospitals face a plethora of infrastructure, psychosocial and environmental barriers to successfully implementing appropriate referral strategies to detect LS patients. This study aims to discover whether a theory grounded approach to implementing guidelines for appropriately identifying LS patients is more effective than a non-theory grounded approach. This will be an Interrupted time series design (ITS) in 10 hospitals across three Australian states (NSW, VIC, WA). Once matched for size and pathology laboratories, hospitals will be randomly allocated to either the intervention (using a theory grounded approach to implementation) or an active control group (non-theory grounded approach to implementation). Translational genetics coordinators will be trained to deliver the implementation approaches, and provided with support from the research team during the following phases: forming an implementation team, identifying baseline audit data and target behaviours for change, identifying barriers to referral, co-designing interventions, implementation, and evaluation of change. Outcome measures will be a) the change in the proportion of CRC patients appropriately tumour tested in both study arms. This will be evaluated through the collection of date-stamped pathology data; b)the change in proportion of appropriate LS referrals made to Familial Cancer Clinic (FCC). This is the first Australian study that will determine the effectiveness of a theoretical approach in translating genomic evidence based policy in improving both detection and referral outcomes in comparison to a non-theory based implementation approach.