Patient randomized trial of a targeted navigation program to improve rates of follow-up colonoscopy in community health centers

Patient Navigation to Improve Colonoscopy Completion After an Abnormal Stool Test Result : A Randomized Controlled Trial

BACKGROUND

Patient navigation is a recommended practice of the Guide to Community Preventive Services; little is known about whether it improves colonoscopy completion for adults who have received an abnormal stool test result.

OBJECTIVE

To determine whether patient navigation delivered to persons with an abnormal stool test result increased follow-up colonoscopy completion (primary) at 1 year.

DESIGN

Randomized controlled trial. (ClinicalTrials.gov: NCT03925883).

SETTING

A federally qualified health center (n = 32 clinics) in Washington state.

PATIENTS

Persons aged 50 to 75 years with an abnormal fecal test result in the prior month.

INTERVENTION

A 6-topic, telephone-based patient navigation program delivered by bilingual (English and Spanish) clinical staff.

MEASUREMENTS

Receipt of follow-up colonoscopy at 1 year (primary); time to colonoscopy receipt (secondary); and program effectiveness by patient characteristics, including patients' probability of obtaining a colonoscopy without navigation, derived using health record data (secondary).

RESULTS

Of 985 participants enrolled (mean age, 61 years [SD, 6.8]; 170 [18%] had a Spanish-language preference listed in the medical record), 967 were included in the primary intention-to-treat analysis (479 in patient navigation, 488 in usual care). Receipt of follow-up colonoscopy was higher in the patient navigation group than in the usual care group (55.1% vs. 42.1%; risk difference, 13.0 percentage points [95% CI, 6.5 to 19.4 percentage points]). The intervention effect was not moderated by patients' probability of obtaining a colonoscopy without navigation.

LIMITATION

The study was primarily done during the height of the COVID-19 pandemic, which created additional barriers to colonoscopy at the health system and patient levels.

CONCLUSION

These findings support the effectiveness of patient navigation for follow-up colonoscopy completion.

PRIMARY FUNDING SOURCE

National Cancer Institute.

Mailed Outreach and Patient Navigation for Colorectal Cancer Screening Among Rural Medicaid Enrollees: A Cluster Randomized Clinical Trial

Importance

Approximately 60 million adults live in rural regions of the US, which historically have low rates of colorectal cancer (CRC) screening and follow-up. Rural residents enrolled in Medicaid have particularly low CRC screening and follow-up rates.

Objective

To determine the effectiveness and implementation of a collaborative Medicaid health plan-clinic program of mailed fecal immunochemical test (FIT) outreach and patient navigation to colonoscopy following an abnormal FIT result when implemented in rural clinics as part of standard care.

Design, Setting, and Participants

This cluster randomized clinical trial was conducted at 28 rural clinic units in Oregon affiliated with 3 Medicaid health plans. The clinics were randomized to the intervention (n = 14) or to usual care (n = 14). Participants were Medicaid enrollees (aged 50-75 years) due for CRC screening. The intervention was delivered from May 11, 2021, through June 4, 2022, and analyses were performed from June 2023 through September 2024.

Intervention

The stepwise intervention involved (1) mailed FIT outreach and (2) patient navigation to colonoscopy following an abnormal FIT result. Implementation support included practice facilitation, training, collaborative learning, and patient tracking tools.

Main Outcomes and Measures

The primary effectiveness outcome was completion of any CRC screening within 6 months of eligibility determination. An additional effectiveness outcome was follow-up colonoscopy completion within 6 months of an abnormal FIT result. Implementation was measured as (1) the proportion of intervention-eligible enrollees who were mailed an FIT and who were sent an advance notification or reminder and (2) the proportion with an abnormal FIT result who were offered patient navigation.

Results

This study included 5614 Medicaid enrollees (2613 in intervention clinics and 3001 in usual care clinics). Enrollees had a mean (SD) age of 58.2 (5.5) years; most (4940 [88.0%]) were aged 50 to 64 years. A total of 2948 enrollees (52.5%) were female, 325 (6.2%) were Hispanic and 3774 (67.2%) were White, and 4457 (79.4%) lived in rural regions. Compared with Medicaid enrollees in usual care clinics, enrollees in intervention clinics had a higher adjusted 6-month proportion of any CRC screening completion (11.8% vs 4.5%; difference, 7.3 [95% CI, 5.3-9.2] percentage points). Implementation was 100% (all 1489 intervention-eligible enrollees) for mailed FIT outreach, 88.5% for advance notification, 78.1% for reminders, and 57.9% for patient navigation.

Conclusions and Relevance

In this cluster randomized clinical trial of rural clinics, mailed FIT outreach and patient navigation boosted participation in CRC screening among Medicaid enrollees. More efforts are needed to address low participation in both FIT testing and follow-up colonoscopy.

Trial Registration

ClinicalTrials.gov Identifier: NCT04890054.

Randomized in error in pragmatic clinical trials

BACKGROUND

Pragmatic trials that combine electronic health record data and patient-reported data may be subject to selection bias due to the differential post-randomization exclusion of participants who are randomized in error. Such situations are often caused by inevitable reasons, such as incomplete patient medical records at the pre-randomization stage. This can lead to participants in the intervention arm being identified as ineligible after randomization, while randomized-in-error participants in the usual care are often not discernable. The differential exclusion can present analytic challenges and threaten result validity.

METHODS

Under the potential outcomes framework, we developed a Bayesian model that jointly identifies the randomized-in-error status and estimates the average treatment effect among participants not randomized in error. We designed simulation studies with hypothesized proportions of 5 %-15 % randomization in error to evaluate the performance of our model across scenarios where the outcomes of participants randomized in error were either measured or unmeasured. Comparisons were made to intention-to-treat and covariate-adjusted estimators.

RESULTS

Simulation results show satisfactory performance of our proposed models, where the estimated average treatment effects among participants not randomized in error have low bias (<1 %) and close to 95 % coverage. Estimates from the alternative approaches can exhibit notable biases and low coverage.

CONCLUSIONS

Differential exclusion in pragmatic clinical trials after randomization can lead to selection bias. Under certain assumptions, Bayesian methods provide a feasible solution to jointly identify randomized-in-error status and estimate the average treatment effect among participants not randomized in error, ensuring more reliable and valid inferences about intervention effects.

Adaptations to a patient navigation program for follow-up colonoscopy in rural primary care practices

PURPOSE

Patient navigation is a recommended practice to improve cancer screenings among underserved populations including those residing in rural areas with care access barriers. We report on patient navigation programme adaptations to increase follow-up colonoscopy rates after abnormal fecal testing in rural primary care practices.

METHODS

Participating clinics delivered a patient navigation programme to eligible patients from 28 affiliated clinics serving rural communities in Oregon clustered within 3 Medicaid health plans. Patient navigation adaptations were tracked using data sources including patient navigation training programme reflections, qualitative interviews, clinic meetings, and periodic reflections with practice facilitators.

FINDINGS

Initial, planned (proactive) adaptations were made to address the rural context; later, unplanned (reactive) adaptations were implemented to address the impact of the COVID-19 global pandemic. Initial planned adaptations to the patient navigation programme were made before the main trial to address the needs of the rural context, including provider shortages and geographic dispersion limiting both patient access to care and training opportunities for providers. Later unplanned adaptations were made primarily in response to COVID-19 care suspension and staff redeployments and shortages that occurred during implementation.

CONCLUSION

While unplanned adaptations were implemented to address the contextual impact of the COVID-19 pandemic on care access patterns and staffing, the changes to training content and context were beneficial to the rural setting overall and should be sustained. Our findings can guide future efforts to optimise the success of such programmes in other rural settings and highlight the important role of adaptations in implementation projects.

Evaluating the Reach of a Patient Navigation Program for Follow-up Colonoscopy in a Large Federally Qualified Health Center

Patient navigation (PN) has been shown to improve participation in cancer screening, including colorectal cancer screening, and is now a recommended practice by the Community Preventive Services Task Force. Despite the effectiveness of PN programs, little is known about the number of contacts needed to successfully reach patients or about the demographic and healthcare utilization factors associated with reach. PRECISE was an individual randomized study of PN versus usual care conducted as a partnership between two large health systems in the Pacific Northwest. The navigation program was a six-topic area telephonic program designed to support patients with an abnormal fecal test result to obtain a follow-up colonoscopy. We report the number of contact attempts needed to successfully reach navigated patients. We used logistic regression to report the demographic and healthcare utilization characteristics associated with patients allocated to PN who were successfully reached. We identified 1,200 patients with an abnormal fecal immunochemical test result, of whom 970 were randomized into the study (45.7% were female, 17.5% were Spanish-speaking, and the mean age was 60.8 years). Of the 479 patients allocated to the PN intervention, 382 (79.7%) were reached within 18 call attempts, and nearly all (n = 356; 93.2%) were reached within six contact attempts. Patient characteristics associated with reach were race, county of residence, and body mass index. Our findings can guide future efforts to optimize the reach of PN programs. Prevention Relevance: The findings from this large study can inform clinic-level implementation of future PN programs in Federally Qualified Health Centers to improve the reach of patients needing cancer screenings, optimize staff resources, and ultimately increase cancer screenings.

The recalibration and redevelopment of a model to calculate patients' probability of completing a colonoscopy following an abnormal fecal test

OBJECTIVES

Fecal immunochemical testing (FIT) is an effective screening tool for colorectal cancer. If an FIT is abnormal, a follow-up colonoscopy is necessary to remove polyps or find cancers. We sought to develop a usable risk prediction model to identify patients unlikely to complete a colonoscopy following an abnormal FIT test.

METHODS

We recalibrated and then redeveloped a prediction model in federally qualified health centers (FQHCs), using a retrospective cohort of patients aged 50-75 with an abnormal FIT test and clinical data. Logistic and Cox regressions were used to recalibrate and then redevelop the model.

RESULTS

The initial risk model used data from eight FQHCs (26 clinics) including 1723 patients. When we applied the model to a single large FQHC (34 clinics, 884 eligible patients), the model did not recalibrate successfully (c-statistic dropped more than 0.05, from 0.66 to 0.61). The model was redeveloped in the same FQHC in a cohort of 1401 patients with a c-statistic of 0.65.

CONCLUSIONS

The original model developed in a group of FQHCs did not adequately recalibrate in the single large FQHC. Health system, patient characteristics or data differences may have led to the inability to recalibrate the model. However, the redeveloped model provides an adequate model for the single FQHC.

Effort Required and Lessons Learned From Recruiting Health Plans and Rural Primary Care Practices for a Cancer Screening Outreach Study

INTRODUCTION

Recruiting organizations (i.e., health plans, health systems, or clinical practices) is important for implementation science, yet limited research explores effective strategies for engaging organizations in pragmatic studies. We explore the effort required to meet recruitment targets for a pragmatic implementation trial, characteristics of engaged and non-engaged clinical practices, and reasons health plans and rural clinical practices chose to participate.

METHODS

We explored recruitment activities and factors associated with organizational enrollment in SMARTER CRC, a randomized pragmatic trial to increase rates of CRC screening in rural populations. We sought to recruit 30 rural primary care practices within participating Medicaid health plans. We tracked recruitment outreach contacts, meeting content, and outcomes using tracking logs. Informed by the Consolidated Framework for Implementation Research, we analyzed interviews, surveys, and publicly available clinical practice data to identify facilitators of participation.

RESULTS

Overall recruitment activities spanned January 2020 to April 2021. Five of the 9 health plans approached agreed to participate (55%). Three of the health plans chose to operate centrally as 1 site based on network structure, resulting in 3 recruited health plan sites. Of the 101 identified practices, 76 met study eligibility criteria; 51% (n = 39) enrolled. Between recruitment and randomization, 1 practice was excluded, 5 withdrew, and 7 practices were collapsed into 3 sites for randomization purposes based on clinical practice structure, leaving 29 randomized sites. Successful recruitment required iterative outreach across time, with a range of 2 to 17 encounters per clinical practice. Facilitators to recruitment included multi-modal outreach, prior relationships, effective messaging, flexibility, and good timing.

CONCLUSION

Recruiting health plans and rural clinical practices was complex and iterative. Leveraging existing relationships and allocating time and resources to engage clinical practices in pragmatic implementation research may facilitate more diverse representation in future trials and generalizability of research findings.

Data Challenges in Identifying Patients Due for Colorectal Cancer Screening in Rural Clinics

INTRODUCTION

Colorectal cancer (CRC) incidence and mortality are disproportionately high among rural residents despite the availability of effective screening methods. Outreach activities can improve CRC screening rates but rely on accurate identification of patients due for screening. We report on data challenges in rural clinics and Medicaid health plans in Oregon in identifying patients eligible for CRC screening, in a large project implementing mailed fecal immunochemical tests (FIT) and patient navigation.

METHODS

We analyzed data from clinic intake surveys and administrative claims. Clinics were asked to identify total population numbers relevant to CRC screening and follow-up. Health plans also identified enrollees eligible for CRC screening in Spring, 2021. Clinic staff validated patient lists for eligibility using their electronic health records (EHR).

RESULTS

EHR features varied across the 29 participating and 28 responding clinics. Among the 28 responding clinics, 21 were able to report their Medicaid population (75%), 19 reported the number of patients aged 50 to 75 (68%) and the number screened for CRC in the last year (68%). Only 8 (29%) were able to report screening details such as number screened by FIT and 9 were able to report on patients with an abnormal FIT or colonoscopy completed after FIT (32%). Health plans had challenges properly identifying where enrollees received care and had missing data for race and ethnicity (range 22 to 34% unknown race, <1% to 24% unknown ethnicity).

DISCUSSION

Most participating rural primary care clinics and Medicaid health plans experienced challenges identifying the population due for a CRC screening outreach program. Better EHR functionality and data reporting capabilities could help rural clinics apply population-based strategies and ultimately attenuate disparities in cancer screening and follow-up.

Mailed fecal testing and patient navigation versus usual care to improve rates of colorectal cancer screening and follow-up colonoscopy in rural Medicaid enrollees: a cluster-randomized controlled trial

Background

Screening reduces incidence and mortality from colorectal cancer (CRC), yet US screening rates are low, particularly among Medicaid enrollees in rural communities. We describe a two-phase project, SMARTER CRC, designed to achieve the National Cancer Institute Cancer Moonshot^SM objectives by reducing the burden of CRC on the US population. Specifically, SMARTER CRC aims to test the implementation, effectiveness, and maintenance of a mailed fecal test and patient navigation program to improve rates of CRC screening, follow-up colonoscopy, and referral to care in clinics serving rural Medicaid enrollees.

Methods

Phase I activities in SMARTER CRC include a two-arm cluster-randomized controlled trial of a mailed fecal test and patient navigation program involving three Medicaid health plans and 30 rural primary care practices in Oregon and Idaho; the implementation of the program is supported by training and practice facilitation. Participating clinic units were randomized 1:1 into the intervention or usual care. The intervention combines (1) mailed fecal testing outreach supported by clinics, health plans, and vendors and (2) patient navigation for colonoscopy following an abnormal fecal test result. We will evaluate the effectiveness, implementation, and maintenance of the intervention and track adaptations to the intervention and to implementation strategies, using quantitative and qualitative methods. Our primary effectiveness outcome is receipt of any CRC screening within 6 months of enrollee identification. Our primary implementation outcome is health plan- and clinic-level rates of program delivery, by component (mailed FIT and patient navigation). Trial results will inform phase II activities to scale up the program through partnerships with health plans, primary care clinics, and regional and national organizations that serve rural primary care clinics; scale-up will include webinars, train-the-trainer workshops, and collaborative learning activities.

Discussion

This study will test the implementation, effectiveness, and scale-up of a multi-component mailed fecal testing and patient navigation program to improve CRC screening rates in rural Medicaid enrollees. Our findings may inform approaches for adapting and scaling evidence-based approaches to promote CRC screening participation in underserved populations and settings.

Trial registration

Registered at clinicaltrial.gov (NCT04890054) and at the NCI’s Clinical Trials Reporting Program (CTRP #: NCI-2021-01032) on May 11, 2021.

Follow-up colonoscopy after an abnormal stool-based colorectal cancer screening result: analysis of steps in the colonoscopy completion process

Background

Delays in receiving follow-up colonoscopy after an abnormal fecal immunochemical test (FIT) result are associated with increased colorectal cancer incidence and mortality. Little is known about patterns of follow-up colonoscopy completion in federally qualified health centers.

Methods

We abstracted the medical records of health center patients, aged 50–75 years, who had an abnormal FIT result between August 5, 2017 and August 4, 2018 (N = 711). We assessed one-year rates of colonoscopy referral, pre-procedure visit completion, colonoscopy completion, and time to colonoscopy; associations between these outcomes and patient characteristics; and reasons for non-completion found in the medical record.

Results

Of the 711 patients with an abnormal FIT result, 90% were referred to colonoscopy, but only 52% completed a pre-procedure visit, and 43% completed a colonoscopy within 1 year. Median time to colonoscopy was 83 days (interquartile range: 52–131 days). Pre-procedure visit and colonoscopy completion rates were relatively low in patients aged 65–75 (vs. 50–64), who were uninsured (vs. insured) or had no clinic visit in the prior year (vs. ≥ 1 clinic visit). Common reasons listed for non-completion were that the patient declined, or the provider could not reach the patient.

Discussion

Efforts to improve follow-up colonoscopy rates in health centers might focus on supporting the care transition from primary to specialty gastroenterology care and emphasize care for older uninsured patients and those having no recent clinic visits. Our findings can inform efforts to improve follow-up colonoscopy uptake, reduce time to colonoscopy receipt, and save lives from colorectal cancer.

Trial registration: National Clinical Trial (NCT) Identifier: NCT03925883.