Preventive Medicine Reports (Aug 2022)

Barriers associated with inadequate follow-up of abnormal fecal immunochemical test results in a safety-net system: A mixed-methods analysis

  • Rachel B. Issaka,
  • Ari Bell-Brown,
  • Jason Kao,
  • Cyndy Snyder,
  • Dana L. Atkins,
  • Lisa D. Chew,
  • Bryan J. Weiner,
  • Lisa Strate,
  • John M. Inadomi,
  • Scott D. Ramsey

Journal volume & issue
Vol. 28
p. 101831

Abstract

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In safety-net healthcare systems, colonoscopy completion within 1-year of an abnormal fecal immunochemical test (FIT) result rarely exceeds 50%. Understanding how electronic health records (EHR) documented reasons for missed colonoscopy match or differ from patient-reported reasons, is critical to optimize effective interventions to address this challenge. We conducted a convergent mixed-methods study which included a retrospective analysis of EHR data and semi-structured interviews of adults 50–75 years old, with abnormal FIT results between 2014 and 2020 in a large safety-net healthcare system. Of the 299 patients identified, 59.2% (n = 177) did not complete a colonoscopy within one year of their abnormal result. EHR abstraction revealed a documented reason for lack of follow-up colonoscopy in 49.2% (n = 87/177); patient-level (e.g., declined colonoscopy; 51.5%) and multi-factorial reasons (e.g., lost to follow-up; 37.9%) were most common. In 18 patient interviews, patient (e.g., fear of colonoscopy), provider (e.g., lack of result awareness), and system-level reasons (e.g., scheduling challenges) were most common. Only three reasons for lack of colonoscopy overlapped between EHR data and patient interviews (competing health issues, lack of transportation, and abnormal FIT result attributed to another cause). In a cohort of safety-net patients with abnormal FIT results, the most common reasons for lack of follow-up were patient-related. Our analysis revealed a discordance between EHR documented and patient-reported reasons for lack of colonoscopy after an abnormal FIT result. Mixed-methods analyses, as in the present study, may give us the greatest insight into modifiable determinants to develop effective interventions beyond quantitative and qualitative data analysis alone.

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