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Patients with Lynch syndrome (an inherited cancer predisposition syndrome) remain largely underdiagnosed despite clinically and cost-effective testing strategies to detect patients. This is largely due to poor referral rates for high-risk patients for consideration of genetic testing. Targeted approaches to improve the implementation of guidelines and thus uptake rates of genetic testing require the use of limited and valuable healthcare resources. Decision makers must carefully balance the potential health impacts of implementation approaches against the associated costs, similar to when assessing the direct impact of health interventions. This protocol outlines the methods used to conduct an economic evaluation of different implementation approaches aimed at improving referral rates of high-risk patients, including estimating implementation approach costs. A cluster randomised controlled trial (the Hide and Seek Project, HaSP) is underway to compare two different implementation approaches aimed at improving referral rates, and thus detection, of Lynch syndrome among colorectal cancer patients across eight Australian hospital networks. An in-depth process evaluation is being conducted alongside the trial and includes measures to collect comprehensive data on both implementation and intervention costs. These costs, in addition to HaSP outcome data, will be incorporated as inputs into an existing microsimulation model—Policy1-Lynch—to project the downstream economic and health impacts and determine the more cost-effective implementation approach from the Australian healthcare perspective. The ability to model the impact of different implementation approaches will enable the most efficient way of improving Lynch syndrome detection. The approach used in this study could also be applied to assess other implementation approaches aimed at increasing the uptake of cost-effective health interventions. ANZCTR, ACTRN12618001072202. Registered on 27 June 2018.

implementation science communications

The health and economic impact of implementation strategies for improving detection of hereditary cancer patients—protocol for an in-depth cost-effectiveness evaluation with microsimulation modelling