Beyond implementation: developing and utilizing a 5-factor scale to measure optimization of Lynch syndrome tumor screening programs in health systems [abstract] Abstract uri icon
  • Background : Implementation of universal tumor screening (UTS) programs for Lynch syndrome remains variable when comparing health systems nationwide. The IMPULSS study aims to better understand this variability and identify elements that facilitate or impede program optimization.
    Methods : The IMPULSS study utilized purposive sampling of 9 health systems (7 in HCSRN, 1 academic, 1 national system) with variability in UTS implementation. Semistructured interviews with 44 relevant stakeholders were conducted. Data collection and thematic analyses were guided by the Consolidated Framework for Implementation Research (CFIR) with the intent to identify domains and constructs differing across sites that have successfully implemented and optimized UTS using cross-case comparisons of the data matrices generated.
    Results : Some sites had multiple unique UTS operations under the same organizational umbrella, each considered separate analytic units (AUs). To date, we have identified 14 distinct AUs within 6 health systems. Of these, 10 AUs had implemented a UTS program, represented by 31 interviewed stakeholders involved in direct-patient care and/or administrative leadership; 13 stakeholders were interviewed from the 4 AUs without a program. Thematic coding guided by CFIR found differences primarily in constructs within the “Innovation Characteristics” CFIR domain. A 5-point UTS optimization scale was created to indicate presence or absence of each of the following factors important to program optimization: 1) systematic tracking; 2) procedural uniformity; 3) process for “bridging the gap” between tumor screening and germline testing; 4) automatic ordering of appropriate reflex testing; and 5) using data and quality assurance methods to determine and improve program efficacy. By scoring each factor as 1-present or 0-absent, progress toward UTS program optimization was calculated and areas that need improvement were identified. AUs that scored a 4 or 5 on optimization demonstrated high quality and consistency in “Networks & Communication.”
    Conclusion : Identification and stratification of CFIR domains and constructs allowed the study team to separate out the processes and factors pertinent to initial implementation and program optimization. We subsequently identified 5 key factors important to UTS program optimization. This will allow us to tailor toolkits to assist with both implementation and optimization of UTS programs.

  • Link to Article
    publication date
  • 2021
  • Research
  • Colorectal Cancer
  • Screening
  • Additional Document Info
  • 8
  • issue
  • 2