Deborah Cragun, Zachary M. Salvati, Jennifer L. Schneider, et al. use CNA to identify factors and causal chains associated with optimal implementation of Lynch syndrome tumor screening.
This study compared Lynch syndrome universal tumor screening (UTS) across multiple health systems (some of which had 2 or more distinct UTS programs) to understand multilevel factors that may affect the successful implementation of complex programs.
Data from 66 stakeholder interviews were used to conduct multivalue coincidence analysis and identify key factors that consistently make a difference in whether UTS programs were implemented and optimized at the system level.
The selected coincidence analysis model revealed combinations of conditions that distinguish 4 optimized UTS programs, 10 nonoptimized programs, and 4 systems with no program. Fully optimized UTS programs had both a maintenance champion and a positive inner setting. Two independent paths were unique to nonoptimized programs: (1) positive attitudes and a mixed inner setting or (2) limited planning and engaging among stakeholders. Negative views about UTS evidence or lack of knowledge about UTS led to a lack of planning and engaging, which subsequently prevented program implementation.
The model improved our understanding of program implementation in health care systems and informed the creation of a toolkit to guide UTS implementation, optimization, and changes. Our findings and toolkit may serve as a use case to increase the successful implementation of other complex precision health programs.
Deborah Cragun, Zachary M. Salvati, Jennifer L. Schneider, et al., Alanna Kulchak Rahm, (2024) Identifying factors and causal chains associated with optimal implementation of Lynch syndrome tumor screening: An application of Coincidence Analysis, Genetics in Medicine, 26(10), 101201. https://doi.org/10.1016/j.gim.2024.101201