Data-Powered Participatory Decision Making: Leveraging Systems Thinking and Simulation to Guide Selection and Implementation of Evidence-Based Colorectal Cancer Screening Interventions. Issue 3 (May 2018) - Wheeler, Stephanie B.; Leeman, Jennifer; Hassmiller Lich, Kristen; Tangka, Florence K.L.; Davis, Melinda M.; Richardson, Lisa C.
Abstract : Abstract: A robust evidence base supports the effectiveness of timely colorectal cancer (CRC) screening, follow-up of abnormal results, and referral to care in reducing CRC morbidity and mortality. However, only two-thirds of the US population is current with recommended screening, and rates are much lower for those who are vulnerable because of their race/ethnicity, insurance status, or rural location. Multiple, multilevel factors contribute to observed disparities, and these factors vary across different populations and contexts. As highlighted by the Cancer Moonshot Blue Ribbon Panel working groups focused on Prevention and Early Detection and Implementation Science inadequate CRC screening and follow-up represent an enormous missed opportunity in cancer prevention and control. To measurably reduce CRC morbidity and mortality, the evidence base must be strengthened to guide the identification of (1) multilevel factors that influence screening across different populations and contexts, (2) multilevel interventions and implementation strategies that will be most effective at targeting those factors, and (3) combinations of strategies that interact synergistically to improve outcomes. Systems thinking and simulation modeling (systems science) provide a set of approaches and techniques to aid decision makers in using the best available data and research evidence to guide implementation planning in the context of such complexity. This commentary summarizes current challenges in CRC prevention and control, discusses the status of the evidence base to guide the selection and implementation of multilevel CRC screening interventions, and describes a multi-institution project to showcase how systems science can be leveraged to optimize selection and implementation of CRC screening interventions in diverse populations and contexts.