Surveillance Colonoscopy in Older Adults: The SurvOlderAdults Study

Inclusion Criteria:

Study Base and Inclusion Criteria, Aim 1:

* The study base will consist of any Veteran alive at age 75 between 2005-2019, with exposure to a qualifying colonoscopy in the 10-year period prior to turning age 75
* The investigators will include those with a qualifying colonoscopy associated with a colonoscopy note that can be processed by the previously established natural language processing (NLP) pipelines for extracting colonoscopy data from free-text reports60, 61 (see prior work below)
* The colonoscopy done closest to, but prior to age 75 will be considered as a candidate qualifying colonoscopy
* Date of cohort entry (start of follow up) will be defined as date at which a participant meeting inclusion criteria turned 75
* Date of qualifying colonoscopy prior to age 75 will be defined as the qualifying colonoscopy reference date

Study Base and Inclusion Criteria for Cases and Subcohort, Aim 2:

* The study base for Aim 2 consists of Veterans ages 75 and alive between 2003-2019 who had a polypectomy prior to turning age 75
* Identification of the study base for Aim 2 will take a distinct approach from Aim 1
* A candidate qualifying colonoscopy event will be defined by presence of a CPT code for colonoscopy associated with a pathology note-based diagnosis of an adenoma within 30 days of the CPT code for colonoscopy
* The colonoscopy event occurring closest to, but prior to age 75 will be selected
* From the study base, all individuals who developed incident or fatal CRC, and a random sample of the entire study base will undergo manual EHR chart review to confirm study eligibility
* To identify candidate incident CRC cases, the investigators will identify all adults with a CRC diagnosis at ages 75, utilizing the Oncology Domain with the same strategy for incident CRC identification as described for Aim 1
* To identify candidate fatal CRC cases, the investigators will identify all adults with a fatal CRC diagnosis at ages 75, using NDI cause-specific mortality data
* To identify candidate members of the subcohort for chart review, a random sample of the study base will be drawn
* This sample may include Veterans with and without subsequent CRC. Rationale for including Veterans with and without subsequent CRC (incident and/or fatal) in the control subcohort is well established
* Specifically, if the investigators were to conduct a cohort study without sampling, then at the start of follow up, the cohort would include people with subsequent CRC
* In a traditional cohort study, every CRC case contributes to the denominator of individuals at risk. Thus, by including in the subcohort Veterans with and without CRC on follow up, the investigators are able to calculate risk based on exposure to surveillance as if the investigators had conducted a cohort study utilizing the entire cohort

Inclusion Criteria, Aim 3a:

Participant selection for qualitative interviews. Patient Selection:

* The investigators will use EHR data to generate a list of VASDHS and VAGLA patients who have:

  * a) age 75
  * b) history of colonoscopy with polypectomy in the past 10 years
  * c) been referred for surveillance colonoscopy
* The investigators will randomly select patients, recruiting until the investigators have 12 who completed surveillance colonoscopy and 12 who have not completed surveillance
* The investigators will monitor the sample to assure sex balance consistent with VA demographics for patients who have had colonoscopy (98.2% male and 1.8% females age 75)
* The investigators will also ensure that at least one- third of sampled patients have moderate or severe frailty based on the claims-based VA-FI36, 64 and make efforts to maintain patient racial/ethnic and geographic (i.e. San Diego/Los Angeles areas) diversity

Provider Selection:

* The investigators will conduct interviews with 20 providers, specifically 10 primary care providers (including 3-4 geriatricians) and 10 gastroenterologists
* The investigators will select providers from a randomly generated list of practicing VA clinicians (5/8th or greater) at VASDHS or VAGLA
* If the investigators experience challenges reaching the target sample size, the investigators will employ snowball sampling by asking participants to name other potentially eligible clinicians
* The investigators anticipate reaching thematic saturation given \> 17 interviews in each group and have made provisions to accommodate up to 6 additional patient and/or provider interviews if new themes continue to arise by the end of the planned interviews
* The investigators will make efforts to achieve geographic balance to ensure provider representation from VASDHS and VAGLA

Participant selection for expert panel:

* The investigators will convene a group of 15-20 multi-level stakeholders for the in-person expert panel in Quarter 1 of Year 4
* The panel will include VA patients and caregivers (not included in Aim 3a):

  * VA providers
  * VA leadership and policymakers
  * health services and clinical researchers
  * individuals with non-VA healthcare systems perspectives

Exclusion Criteria:

Study Base and Exclusion Criteria, Aim 1:

* History of CRC prior to age 75
* History of sessile serrated adenoma/polyp/lesion (SSL), traditional serrated adenoma (TSA), or large serrated polyp (LSP, defined as hyperplastic polyp \>10mm) at qualifying colonoscopy
* History of inflammatory bowel disease (IBD) prior to age 75
* Absence of exposure to normal colonoscopy or colonoscopy with polypectomy between ages 65-75

Study Base and Exclusion Criteria for Cases and Subcohort, Aim 2:

* All candidate CRC cases and members for the subcohort will be included in the analytic sample unless they meet one of the following exclusion criteria:

  * absence of a reviewable colonoscopy note
  * absence of polypectomy with adenoma diagnosis at candidate qualifying colonoscopy event
  * presence of a SSL, TSA, or LSP
  * history of CRC or IBD
  * history of hereditary cancer syndrome (this criteria is not used for Aim 1 because it cannot be reliably assessed with structured EHR data)