The goals of this proposal are to: (1) identify patient- and system-level determinants of diagnostic colonoscopy after positive FIT; (2) identify patient- and system-level equity-driven implementation strategies for diagnostic colonoscopy after positive FIT matched to determinants; and (3) pilot test patient- and systems-level implementation strategies to increase rate of colonoscopy after positive FIT and determine feasibility and acceptability of strategies using mixed methods

A. Study Overview: The goals of this proposal are to: (1) identify systems-level determinants of colorectal cancer screening and patient- and systems-level determinants of follow-up colonoscopy after positive FIT in individuals aged 45-75using mixed methods, guided by Consolidated Framework for Implementation Research 2.0 (CFIR 2.0); (2) identify equity-driven implementation strategies for colorectal cancer screening; and (3) to pilot test implementation strategies and determine feasibility and acceptability using mixed methods (Figure 1). Outcomes for our pilot are informed by the RE-AIM framework with an equity lens.

B. Setting: Codman Square Health Center has a majority Black patient population (86%). It is in the Dorchester neighborhood of Boston, which has among the highest colorectal cancer mortality rates in the city. Also, 87% of patients at this community health center live at or below the federal poverty level. The clinical champion at the community health center, Dr. Rachel Hindin, is the medical director for the Internal Medicine department who has previously collaborated with the investigator.

The overall colorectal cancer screening rate at Codman Square Health Center is 47.9%. Colorectal cancer screening rates at Codman Square Health Center are lowest in those 45 to 49 (22.2%) and 50 to 54 (36.8%), well below the national average. Approximately 4.7% of patients at CHSC have a positive FIT test, with only 42.1% receiving diagnostic colonoscopy. My prior work with Codman Square Health Center has identified initial gaps at the system-level that create barriers to colorectal cancer screening, thus the investigator will specifically target this level.

C. Primary and Secondary Outcomes: Feasibility and acceptability are primary outcomes. Acceptability is "the perception among implementation stakeholders that a given treatment, service, practice, or innovation is agreeable, palatable, or satisfactory." Feasibility is "the extent to which an innovation, can be successfully used or carried out within a given agency or setting. Reach, effectiveness, and maintenance are secondary outcomes. Across all dimensions, the investigator will track equity based on differences in uptake and delivery by race, ethnicity, language, sex assigned at birth (male/female), sexual/gender minority status, and insurance status.

AIM 1: Identify patient- and system-level determinants of diagnostic colonoscopy after positive FIT test using mixed methods.

A. Overview: Aim 1 will identify patient- and systems-level determinants of diagnostic colonoscopy after positive FIT test through mixed effect modeling and in-depth interviews with patients and staff using the CFIR framework and mixed methods.

B. Approach:

B.1. Identify predictors of diagnostic colonoscopy after positive FIT test: We will use data from DRVS to determine predictors of diagnostic colonoscopy after positive FIT tests across 14 CHC partners. We will look at patient-level data, individual clinic-level data (CFIR inner setting), and larger community-level data (CFIR outer setting). We will include de-identified patient-level data from DRVS for individuals who are age 45 to 75 and average risk for CRC (e.g. no family or personal history of CRC, no high-risk cancer syndromes such as Lynch Syndrome, no history of inflammatory bowel disease).

Data Analysis: Generalized linear mixed effect models will be used to examine the outcome of diagnostic colonoscopy after positive FIT (yes/no) as function of patient demographics (first level) and inner setting survey construct scores for individual CHCs (second level) and outer setting community-level factors (third level). The model will specify a random intercept for clustering at the community health center level (second level) and at community-level (third level). Inner setting construct scores have already been collected across CHC partners from an organizational survey conducted in previous work by ISCCCE. Data on outer setting has also been collected at multiple geographic levels (eg. zipcode tabulation, county, census tract) across the United States in previous ISCCCE work and this data will be incorporated into our model32. Findings from our analysis will be used to shape our interview guides. Prior to the start of analysis, I will complete coursework in multilevel modeling under the guidance of Dr. Chan.

B.2. In-depth interviews:

Participants and recruitment: We will conduct in-depth interviews with a sample of 10 providers and staff directly involved in CRC screening practices in patient-facing roles at CSHC, and 10 interviews with patients per age strata (45-49; 50-75). Patients aged 45 to 75 years who have been seen in the primary care clinic at CSHC within the last 36 months and are average-risk for CRC (e.g. no family or personal history of CRC, no high-risk cancer syndromes such as Lynch Syndrome, no history of inflammatory bowel disease) will be recruited for in-depth interviews. We will ensure race/ethnicity and sex distribution (male/female) proportionate to the clinic demographics. We expect that 20 interviews with patients and 10 interviews with providers and staff will lead to thematic saturation, but will extend if needed.33-35 Eligible staff will be identified by Dr. Hindin; eligible patients will be identified by the population management team at CSHC and contacted by the study team with permission from their providers.

Procedures: Verbal informed consent will be obtained prior to each interview. I will conduct interviews, with Dr. Park observing and providing feedback. I will complete interviewer training from the Qualitative and Mixed Methods Research Unit at MGH and pilot the interview guide with the research team and a separate sample of representative patients (using recruitment and consent procedures as above) prior to conducting interviews. Each interview will be audio-recorded with participants' permission, and sessions will be conducted in-person or via video based on participant preference.

Content of CFIR inner and outer setting questions will be informed by our quantitative analysis to determine predictors of colonoscopy after FIT.

Guided by CFIR 2.0, qualitative domains for patient interviews will include: 1) The Innovation (e.g., knowledge/perceptions about diagnostic colonoscopy after positive FIT); 2) Outer Setting (e.g., structural barriers to diagnostic colonoscopy); 3) Inner Setting (e.g., ease of scheduling diagnostic colonoscopy, health center resources for assistance); 4) Characteristics of Individuals (e.g. knowledge/attitudes about diagnostic colonoscopy after positive FIT, patient-provider concordance).

The CFIR qualitative interview domains for staff interviews will include: 1) The Innovation (e.g., knowledge/perceptions about diagnostic colonoscopy after FIT); 2) Outer Setting (e.g., structural barriers to diagnostic colonoscopy, public awareness about need for colonoscopy after FIT); 3) Inner Setting (e.g., leadership and staff buy-in, resources, patient needs, cultural competency); 4) Characteristics of Individuals (e.g. linguistic representation, staff turnover, patient-provider concordance); 5) Implementation Process (implementation stress/demands).

Data Analysis: I will oversee all data collection and analysis. Interviews will be recorded and transcribed using an institutionally-approved software and analyzed using NVivo. Analyses will include inductive (thematic analyses of barriers and facilitators) and deductive strategies (structural coding). We will apply the 5 stages of Framework analysis (Familiarization, Identifying Themes, Indexing, Charting, and Interpreting)36 to conduct content analyses, which will be done by me and a research coordinator with oversight from Dr. Park. We will analyze along CFIR domains. Discrepancies will be resolved with Dr. Park through discussion and comparison of raw data. Coding will continue until a high level of reliability (Kappa=>0.80) is established. Qualitative findings will be compared by age-specific strata for patients, and patients vs staff. Prior to interviews, I will complete coursework in qualitative analysis.

C. Expected Outcomes: The identification of patient and system-level determinants of diagnostic colonoscopy after positive FIT.

D. Potential Problems and Alternative Strategies: A potential problem may be difficulty recruiting patients for interviews. Recruitment will be done with the help of Dr. Hindin, our clinical champion who has had prior success in recruiting individuals for qualitative data collection.

VI. AIM 2: Co-design equity-driven implementation strategies to increase timely diagnostic colonoscopy after positive FIT test matched to patient- and systems-level determinants with CHC partners.

A. Overview: Aim 2 will match patient- and systems-level determinants of diagnostic colonoscopy after positive FIT (identified in Aim 1) to potential implementation strategies.

B. Approach:

B.1. Workflow mapping: After determinant themes are identified, we will meet with the CSHC team for workflow mapping. Workflow maps detail every step in the CRC screening process and identify where new strategies will fit in the clinical workflow. During this process we will work with the CSHC team to identify all resources available to assist in completion of diagnostic colonoscopy after positive FIT to determine which resources could be implemented as strategies, which resources are available but not being utilized, and where new resources may be needed. For example, if transportation is noted to be a barrier, then we might consider an escort program utilizing community health workers at the CHC or consider a ride-share program (Table 2). Our goal will be to incorporate resources already available at the CHC but not being utilized to maximize sustainability of the work. We will also explore how to incorporate patients into our workflow mapping process to better delineate the workflow of positive FIT to colonoscopy from the patient perspective.

B.2 Implementation Strategy Development: After workflow mapping, together with the CSHC team we will first rank determinants (high/medium/low). We will then develop implementation roadmaps for high-ranking determinants and identify multiple potential strategies to address the identified determinant. Multiple roadmaps will be developed based on identified determinants and we will develop a list of potential implementation strategies (Table 2), based on ranking, CHC needs, and preferences.

C. Expected Outcomes: The identification of patient and systems-level implementation strategies matched to barriers specific to CHC needs and resources.

D. Potential Problems & Alternative Strategies: Strategies may not fit into existing workflows or may add burden to CHC staff and providers. In this case, we will determine if new workflows can be created, or if a different strategy is needed. In addition, if we are unable to incorporate patients into our workflow mapping an alternative strategy would be to incorporate workflow questions from the patient perspective into patient interviews during Aim 1.

E. Timeline and Deliverables: Aim 2 activities will occur in Year 2 and will result in 3 manuscripts.

VII. AIM 3: Determine acceptability and feasibility of implementation strategies to increase uptake of timely diagnostic colonoscopy after positive FIT test using mixed methods.

A. Overview: Aim 3 will test patient- and systems-level implementation strategies (identified in Aim 2) for diagnostic colonoscopy after positive FIT test at CSHC and evaluate outcomes using mixed methods.

B. Approach:

B.1. Population: Individuals aged 45 to 75 who are average-risk for CRC will be identified using the DRVS platform. DRVS allows for population management views of individuals who are due for cancer screening. There are 7,902 patients at CSHC age 45 to 75 who are average risk for CRC and eligible for inclusion. Within this group, our analysis will focus on those who have a positive FIT test during the study period.

B.2.Study Design: We will test the 2 highest ranking barrier-strategy combinations at the patient- and system-levels (identified in Aims 1 and 2) . We will test each barrier-strategy combination separately for a total of 6 months. The most feasible and acceptable strategies will be continued, and sustainability will be measured 6 months after completion of the last cycle. Outcomes.

C. Data Collection:

C.1.Quantitative data: Data will be collected via Redcap survey and CSHC specific data on DRVS.

C.2.Qualitative data: One-on-one semi-structured interviews will be conducted with staff involved in implementation (n = 15) to further explore the acceptability and feasibility, reach, effectiveness, successes, and challenges faced. Data on maintenance of program components will be collected at 6 months post-pilot. Interviews will be 1 hour in duration and conducted in person or over Zoom video conference. Interview guides will be structured following RE-AIM and adapted to explore survey findings in greater depth using an explanatory sequential mixed methods design. Consent for surveys and in-person or video interviews will be the same as in Aim 1.

D. Data Analysis:

D.1.Quantitative data: For our primary outcome, participants will be asked to rate the acceptability and feasibility of implementation strategies using a previously validated instrument37, which we have previously used with CHC staff. This tool has demonstrated good internal consistency reliability (0.85 for acceptability and 0.89 for feasibility) and similarly good test-retest reliability (correlations: acceptability- 0.80; feasibility - 0.88) and validity in a known groups analysis. There is no established acceptability and feasibility benchmark for these measures. Quantitative data will provide a numeric summary of acceptability and feasibility which will inform the development of interview guides for qualitative data collection.

For secondary outcomes, descriptive statistics (relative frequencies, means, variability) will be used to evaluate reach (# of patients offered diagnostic colonoscopy after positive FIT and characteristics of those who were not), effectiveness (time to diagnostic colonoscopy after positive FIT measured by assessing the difference in the date FIT test resulted as positive compared to the date colonoscopy was ordered and completed pre and post intervention), and maintenance (percentage of program components maintained). We will use generalized linear models to estimate the level of effectiveness, reach, and maintenance across clinical characteristics and sociodemographics with a particular focus on characteristics around equity. We will also explore differences in equity outcomes among subgroups, recognizing that our power is limited.

D.2.Qualitative data: We will follow the same framework analysis as AIM 1, using RE-AIM domains.

Consistent with the purpose and intent of a pilot study as described in detail by Leon and Kramer and colleagues38,39, our study will evaluate feasibility, acceptability, and potential effectiveness but will not be powered to test statistical significance or to formally test a hypothesis, which will be the intent of my future R01.

Inclusion Criteria:

• Individuals aged 45-75
• Individuals who are patients at Codman Square Health Center
• Individuals that are willing and able to give verbal/written consent

Exclusion Criteria:

• Individuals with a personal history of colorectal cancer
• Individuals with a family history of colorectal cancer
• Individuals with a history of inflammatory bowel disease or high-risk cancer syndrome

Codman Square Health Center patients aged 45-75 who do not have a personal or family history of colorectal cancer, inflammatory bowel disease, or a high-risk cancer syndrome. Codman Square Health Center staff ages 18+ that are involved in colorectal cancer screening processes at Codman Square Health Center.