STEPS (Study To Examine Parent, Patient/Dental Provider Systems) to Prevent Human Papillomavirus (HPV)-Related Cancers: A Piloted Dental Patient and Provider Evaluation of Current and Future HPV Education.

Oropharyngeal human papillomavirus (HPV) cancers are prevalent, but HPV education in dental clinics is uncommon. The purpose of this study was to evaluate dental provider and patient knowledge from, attitudes towards, and preferences for HPV education, then assess perceptions of existing HPV educational materials for use at dental visits. Appalachian Ohio dental patients (n = 13) and general/pediatric dental providers (n = 10) completed an initial, close-ended survey on current HPV knowledge and HPV educational attitudes, participation, and resource preferences. Select individuals reviewed existing HPV educational videos and toolkits via virtual focus groups (n = 9) or independent review surveys (n = 6). Using a discussion guide, participants responded to overall, visual, auditory, and content satisfaction statements, orally (focus groups) or with Likert scales (independent reviews). Surveys were summarized with frequencies/percentages; transcripts were qualitatively coded to identify potential material modifications. Dental providers and patients were more comfortable with HPV and oral cancer education (87% and 96%, respectively) and screening (96%) than with HPV vaccine education (74%) and referrals (61%) during dental visits. Providers were neither sharing HPV educational materials (80%) nor initiating educational conversations with dental patients (100%). The American Cancer Society videos and the "Team Maureen" toolkit were the most liked resources (i.e., fewer negative/disagree statements) by all participant groups. Findings indicate that future dental HPV educational efforts should be informed by currently available materials. Additional interventions are needed to promote dental provider discussions and sharing of educational materials with patients to increase education and promotion of the HPV vaccine and reduce oropharyngeal cancers.

Bayesian semiparametric joint modeling of longitudinal explanatory variables of mixed types and a binary outcome.

Many prospective biomedical studies collect longitudinal clinical and lifestyle data that are both continuous and discrete. In some studies, there is interest in the association between a binary outcome and the values of these longitudinal measurements at a specific time point. A common problem in these studies is inconsistency in timing of measurements and missing follow-ups which can lead to few measurements at the time of interest. Some methods have been developed to address this problem, but are only applicable to continuous measurements. To address this limitation, we propose a new class of joint models for a binary outcome and longitudinal explanatory variables of mixed types. The longitudinal model uses a latent normal random variable construction with regression splines to model time-dependent trends in mean with a Dirichlet Process prior assigned to random effects to relax distribution assumptions. We also standardize timing of the explanatory variables by relating the binary outcome to imputed longitudinal values at a set time point. The proposed model is evaluated through simulation studies and applied to data from a cancer survivor study of participants in the Women's Health Initiative.

Semi-parametric survival analysis via Dirichlet process mixtures of the First Hitting Time model.

Time-to-event data often violate the proportional hazards assumption inherent in the popular Cox regression model. Such violations are especially common in the sphere of biological and medical data where latent heterogeneity due to unmeasured covariates or time varying effects are common. A variety of parametric survival models have been proposed in the literature which make more appropriate assumptions on the hazard function, at least for certain applications. One such model is derived from the First Hitting Time (FHT) paradigm which assumes that a subject's event time is determined by a latent stochastic process reaching a threshold value. Several random effects specifications of the FHT model have also been proposed which allow for better modeling of data with unmeasured covariates. While often appropriate, these methods often display limited flexibility due to their inability to model a wide range of heterogeneities. To address this issue, we propose a Bayesian model which loosens assumptions on the mixing distribution inherent in the random effects FHT models currently in use. We demonstrate via simulation study that the proposed model greatly improves both survival and parameter estimation in the presence of latent heterogeneity. We also apply the proposed methodology to data from a toxicology/carcinogenicity study which exhibits nonproportional hazards and contrast the results with both the Cox model and two popular FHT models.

HPV vaccine coverage across Hispanic/Latinx subgroups in the United States.

PURPOSE: Research on HPV vaccine coverage in the United States has typically aggregated Hispanic/Latinx individuals into a single group for analyses, an approach that has potentially masked variation between Hispanic/Latinx subgroups. To address this limitation, we examined HPV vaccine coverage across Hispanic/Latinx subgroups. METHODS: We analyzed data on Hispanic/Latinx adolescents ages 13-17 (n = 16,335) from the 2012-2016 National Immunization Survey-Teen. Each adolescent was categorized into a subgroup: Mexican, Cuban, Puerto Rican, Central American, South American, other Spanish origin, or multi-subgroup. We examined HPV vaccine initiation (receipt of one or more doses) and completion (receipt of three doses) for males and females separately. Analyses used weighted logistic regression. RESULTS: Vaccine coverage among males was highest among Central Americans (initiation: 57.5%; completion: 31.1%) and lowest among multi-subgroup males (initiation: 46.3%; completion: 19.9%). Among females, initiation ranged from 63.4% among Cubans to 71.2% among Puerto Ricans, and completion ranged from 33.6% among multi-subgroup females to 48.7% among South Americans. Hispanic/Latinx subgroups were similar on these outcomes in regression models. However, within several subgroups, vaccine coverage was higher among adolescents whose parents' preferred language was Spanish (i.e., potentially less acculturated) compared to those whose parents' preferred language was English. CONCLUSIONS: Modest variation in HPV vaccine coverage exists across Hispanic/Latinx subgroups, with differences found by preferred language within several subgroups. Findings provide insight into HPV vaccine coverage among Hispanic/Latinx subgroups and can help guide future surveillance efforts and vaccination interventions.

Assessing the goodness of fit of logistic regression models in large samples: A modification of the Hosmer-Lemeshow test.

Evaluating the goodness of fit of logistic regression models is crucial to ensure the accuracy of the estimated probabilities. Unfortunately, such evaluation is problematic in large samples. Because the power of traditional goodness of fit tests increases with the sample size, practically irrelevant discrepancies between estimated and true probabilities are increasingly likely to cause the rejection of the hypothesis of perfect fit in larger and larger samples. This phenomenon has been widely documented for popular goodness of fit tests, such as the Hosmer-Lemeshow test. To address this limitation, we propose a modification of the Hosmer-Lemeshow approach. By standardizing the noncentrality parameter that characterizes the alternative distribution of the Hosmer-Lemeshow statistic, we introduce a parameter that measures the goodness of fit of a model but does not depend on the sample size. We provide the methodology to estimate this parameter and construct confidence intervals for it. Finally, we propose a formal statistical test to rigorously assess whether the fit of a model, albeit not perfect, is acceptable for practical purposes. The proposed method is compared in a simulation study with a competing modification of the Hosmer-Lemeshow test, based on repeated subsampling. We provide a step-by-step illustration of our method using a model for postneonatal mortality developed in a large cohort of more than 300 000 observations.

Lower patient-reported function at 2 years is associated with elevated knee cartilage T1rho and T2 relaxation times at 5 years in young athletes after ACL reconstruction.

PURPOSE: The purpose was to test the following hypotheses: (1) magnetic resonance imaging (MRI) markers of early knee cartilage degeneration would be present in the involved limb of young athletes after anterior cruciate ligament reconstruction (ACLR) and (2) poor knee function would be associated with MRI markers of cartilage degeneration. METHODS: Twenty-five young athletes after primary, unilateral ACLR (mean age, 16.7 years) were followed to 5-year post-return-to-sport (RTS) clearance, as a part of a larger, prospective cohort study in young athletes post-ACLR. At 2-year post-RTS, patient-reported knee function was evaluated using the Knee injury and Osteoarthritis Outcome Score (KOOS). At 5-year post-RTS, qualitative MRI sequences (3 T) and quantitative T1rho and T2 maps segmented into six regions at the femur and tibia were performed for the involved and uninvolved knee cartilages. Relaxation times were compared between knees using Holm-corrected paired t tests. Linear regression was used to examine the association between KOOS scores at 2 years and relaxation times at 5 years. RESULTS: Elevated T1rho and T2 relaxation times were observed in the involved knee at the anterior medial femoral condyle compared to the uninvolved knee (p = 0.006, p = 0.024, respectively). Lower KOOS-Pain, KOOS-Symptoms, KOOS-ADL, and KOOS-Sport scores at 2-year post-RTS were associated with higher T1rho or T2 relaxation times in various regions of the involved knee at 5-year post-RTS (all p < 0.05). CONCLUSIONS: MRI markers of early cartilage degeneration were identified in the medial compartment of the involved knee in young athletes 5-year post-RTS after ACLR. Lower KOOS scores at 2-year post-RTS were associated with elevated knee cartilage T1rho and T2 relaxation times at 5-year post-RTS. Evaluating patient-reported function over time after ACLR appears to provide insight into future degenerative changes in the knee cartilage matrix.

Process Evaluation of Cancer Prevention Media Campaigns in Appalachian Ohio.

The purpose of this study is to provide process data from campaigns (2009-2010) to improve colorectal cancer (CRC; intervention) screening and fruit and vegetable (F&V; comparison) consumption in 12 Appalachian Ohio counties. County-specific campaigns included one billboard, posters, and articles for local newspapers. Participants in CRC screening counties who reported seeing CRC screening billboards had greater intention to talk to a doctor/nurse about screening in the next 6 months (odds ratio [OR] = 2.92, 95% confidence interval [CI; 1.71, 4.99]) and had twice the odds of talking to a doctor/nurse about screening in the past year (OR = 2.15, 95% CI [1.29, 3.60]) compared to those who did not see the billboards. Participants in F&V counties who reported seeing F&V billboards had twice the odds (OR = 2.27, 95% CI [1.35, 3.84]) of talking to a doctor/nurse in the past year about F&Vs compared to those who did not see the billboards. Participants who reported campaign exposure lived closer to the billboards compared to those who did not report campaign exposure (mean distance in miles from home to billboard: 8.8 vs. 10.9; p < .01). Most participants reported campaign messages were clear and important. Results suggest that partnering with community members to develop campaign materials is important to ensure cultural appropriateness and that exposure to the intervention components may affect health-related outcomes.

The influence of organizational factors on patient safety: Examining successful handoffs in health care.

BACKGROUND: Although patient handoffs have been extensively studied, they continue to be problematic. Studies have shown poor handoffs are associated with increased costs, morbidity, and mortality. No prior research compared perceptions of management and clinical staff regarding handoffs. PURPOSE: Our aims were (a) to determine whether perceptions of organizational factors that can influence patient safety are positively associated with perceptions of successful patient handoffs, (b) to identify organizational factors that have the greatest influence on perceptions of successful handoffs, and (c) to determine whether associations between perceptions of these factors and successful handoffs differ for management and clinical staff. METHODOLOGY/APPROACH: A total of 515,637 respondents from 1,052 hospitals completed the Hospital Survey on Patient Safety Culture that assessed perceptions about organizational factors that influence patient safety. Using weighted least squares multiple regression, we tested seven organizational factors as predictors of successful handoffs. We fit three separate models using data collected from (a) all staff, (b) management only, and (c) clinical staff only. FINDINGS: We found that perceived teamwork across units was the most significant predictor of perceived successful handoffs. Perceptions of staffing and management support for safety were also significantly associated with perceived successful handoffs for both management and clinical staff. For management respondents, perceptions of organizational learning or continuous improvement had a significant positive association with perceived successful handoffs, whereas the association was negative for clinical staff. Perceived communication openness had a significant association only among clinical staff. PRACTICE IMPLICATIONS: Hospitals should prioritize teamwork across units and strive to improve communication across the organization in efforts to improve handoffs. In addition, hospitals should ensure sufficient staffing and management support for patient safety. Different perceptions between management and clinical staff with respect to the importance of organizational learning are noteworthy and merit additional study.

Iron and noncontrast magnetic resonance T2* as a marker of intraplaque iron in human atherosclerosis.

OBJECTIVE: Iron has been implicated in atherogenesis and plaque destabilization, whereas less is known about iron-related proteins in this disease. We compared ex vivo quantities with in vivo vessel wall T2*, which is a noncontrast magnetic resonance relaxation time that quantitatively shortens with increased tissue iron content. We also tested the hypothesis that patients with carotid atherosclerosis have abnormal T2* times vs controls that would help support a role for iron in human atherosclerosis. METHODS: Forty-six patients undergoing carotid endarterectomy and 14 subjects without carotid disease were prospectively enrolled to undergo carotid magnetic resonance imaging. Ex vivo measurements were performed on explanted plaque and 17 mammary artery samples. RESULTS: Plaques vs normal arteries had higher levels of ferritin (median, 7.3 [interquartile range (IQR), 4-13.8] vs 1.0 [IQR, 0.6-1.3] ng/mg; P < .001) and oxidized low-density lipoprotein (median, 0.17 [IQR, 0.12-0.30] vs 0.01 [IQR, 0.003-0.03] ng/mg; P < .001) as well as hepcidin (median, 8.7 [IQR, 4.6-12.4] vs 2.6 [IQR, 1.3-7.0] ng/mL; P = .03); serum hepcidin levels did not distinguish atherosclerosis patients from controls (median, 40.6 [IQR, 18.8-88.6] vs 33.9 [IQR, 17.6-55.2]; P = .42). Shorter in vivo T2* paralleled larger plaque volume (ρ = -.44; P = .01), and diseased arteries had shorter T2* values compared with controls (median, 17.7 ± 4.3 vs 23.0 ± 2.4 ms; P < .001). CONCLUSIONS: Diseased arteries have greater levels of iron-related proteins ex vivo and shorter T2* times in vivo. Further studies should help define the role of T2* as a biomarker of iron and atherosclerosis.

No association between colorectal cancer worry and screening uptake in Appalachian Ohio.

BACKGROUND: Limited data are available on the association between colorectal cancer (CRC) worry and CRC screening uptake, particularly in rural and underserved populations where there is an excess burden of CRC. METHODS: Between September 2009 and March 2010, we conducted a cross-sectional study among a randomly selected sample of Appalachian Ohio residents aged 51-75 years (n= 1084). We also reviewed their medical records. Multivariable-adjusted models examined the association between CRC worry and screening by medical record review, assessed effect modification by CRC worry and determined the correlates of higher CRC worry. RESULTS: Approximately 50% of participants were adherent to CRC screening guidelines. There was no significant association between higher CRC worry and screening adherence [odds ratio (OR) = 1.32, 95% confidence interval (CI): 0.86-2.02]. CRC worry did not modify the association between any covariate and screening adherence. Participants who were unemployed/disabled (OR = 2.15, 95% CI: 1.34-3.45) and had higher CRC risk perception (OR = 3.49, 95% CI: 2.19-5.56) had higher odds of moderate-to-extreme worry. CONCLUSIONS: These findings highlight the need for meaningful exploration of why higher CRC worry is not associated with adherence to CRC screening, particularly in rural, medically underserved populations. Development and implementation of interventions to increase CRC screening in such areas is a significant public health priority.

Ornstein-Uhlenbeck threshold regression for time-to-event data with and without a cure fraction.

In this paper we propose a threshold regression (TR) model for time to event data related to subject health using a latent Ornstein-Uhlenbeck (OU) process that fails once it hits a boundary value for the first time. Baseline covariates are incorporated into the analysis using a log-link function for the initial state of the health process. The model provides clinically meaningful covariate effects and does not require the proportional hazards assumption of the commonly used Cox model. Unlike TR models based on the Wiener process, the OU model allows increments in the health process to depend on previous values and drifts toward a state of equilibrium or homeostasis, which are present in many biological applications. We also extend our model to incorporate a cure rate for applications with improper survival functions, such as time to tumor recurrence in a cancer clinical trial. Our models are applied to overall and relapse-free survival data of melanoma patients undergoing definitive surgery.

Comparison of treadmill exercise stress cardiac MRI to stress echocardiography in healthy volunteers for adequacy of left ventricular endocardial wall visualization: A pilot study.

PURPOSE: To compare exercise stress cardiac magnetic resonance (cardiac MR) to echocardiography in healthy volunteers with respect to adequacy of endocardial visualization and confidence of stress study interpretation. MATERIALS AND METHODS: Twenty-eight healthy volunteers (age 28 ± 11 years, 15 males) underwent exercise stress echo and cardiac MR one week apart assigned randomly to one test first. Stress cardiac MR was performed using an MRI-compatible treadmill; stress echo was performed as per routine protocol. Cardiac MR and echo images were independently reviewed and scored for adequacy of endocardial visualization and confidence in interpretation of the stress study. RESULTS: Heart rate at the time of imaging was similar between the studies. Average time from cessation of exercise to start of imaging (21 vs. 31 s, P < 0.001) and time to acquire stress images (20 vs. 51 s, P < 0.001) was shorter for cardiac MR. The number of myocardial segments adequately visualized was significantly higher by cardiac MR at rest (99.8% vs. 96.4%, P = 0.002) and stress (99.8% vs. 94.1%, P = 0.001). The proportion of subjects in whom there was high confidence in the interpretation was higher for cardiac MR than echo (96% vs. 60%, P = 0.005). CONCLUSION: Exercise stress cardiac MR to assess peak exercise wall motion is feasible and can be performed at least as rapidly as stress echo.

Semiparametric Bayesian joint modeling of a binary and continuous outcome with applications in toxicological risk assessment.

Many dose-response studies collect data on correlated outcomes. For example, in developmental toxicity studies, uterine weight and presence of malformed pups are measured on the same dam. Joint modeling can result in more efficient inferences than independent models for each outcome. Most methods for joint modeling assume standard parametric response distributions. However, in toxicity studies, it is possible that response distributions vary in location and shape with dose, which may not be easily captured by standard models. To address this issue, we propose a semiparametric Bayesian joint model for a binary and continuous response. In our model, a kernel stick-breaking process prior is assigned to the distribution of a random effect shared across outcomes, which allows flexible changes in distribution shape with dose shared across outcomes. The model also includes outcome-specific fixed effects to allow different location effects. In simulation studies, we found that the proposed model provides accurate estimates of toxicological risk when the data do not satisfy assumptions of standard parametric models. We apply our method to data from a developmental toxicity study of ethylene glycol diethyl ether.

Standardizing the power of the Hosmer-Lemeshow goodness of fit test in large data sets.

The Hosmer-Lemeshow test is a commonly used procedure for assessing goodness of fit in logistic regression. It has, for example, been widely used for evaluation of risk-scoring models. As with any statistical test, the power increases with sample size; this can be undesirable for goodness of fit tests because in very large data sets, small departures from the proposed model will be considered significant. By considering the dependence of power on the number of groups used in the Hosmer-Lemeshow test, we show how the power may be standardized across different sample sizes in a wide range of models. We provide and confirm mathematical derivations through simulation and analysis of data on 31,713 children from the Collaborative Perinatal Project. We make recommendations on how to choose the number of groups in the Hosmer-Lemeshow test based on sample size and provide example applications of the recommendations.

Correlates of colorectal cancer screening among residents of Ohio Appalachia.

There is an excess burden of colorectal cancer (CRC) in the Appalachian region of the United States, which could be reduced by increased uptake of CRC screening tests. Thus, we examined correlates of screening among Appalachian residents at average-risk for CRC. Using a population-based sample, we conducted interviews with and obtained medical records of Appalachian Ohio residents 51-75 years between September 2009 and April 2010. Using multivariable logistic regression, we identified correlates of being within CRC screening guidelines by medical records. About half of participants were within CRC screening guidelines. Participants who were older (OR = 1.04, 95 % CI 1.01, 1.07), had higher income ($30,000-$60,000, OR = 1.92, 95 % CI 1.29, 2.86; ≥$60,000, OR = 1.80, 95 % CI 1.19, 2.72), a primary care provider (OR = 4.22, 95 % CI 1.33, 13.39), a recent check-up (OR = 2.37, 95 % CI 1.12, 4.99), had been encouraged to be screened (OR = 1.57, 95 % CI 1.11, 2.22), had been recommended by their doctor to be screened (OR = 6.68, 95 % CI 3.87, 11.52), or asked their doctor to order a screening test (OR = 2.24, 95 % CI 1.36, 3.69) had higher odds of being screened within guidelines in multivariable analysis. Findings suggest that access to and utilization of healthcare services, social influence, and patient-provider communication were the major factors associated with CRC screening. Researchers and healthcare providers should develop and implement strategies targeting these barriers/facilitators to improve CRC screening rates and reduce the CRC burden among residents of Appalachia.

Bayesian semiparametric joint modeling of a count outcome and inconveniently timed longitudinal predictors.

The Women's Health Initiative (WHI) Life and Longevity After Cancer (LILAC) study is an excellent resource for studying the quality of life following breast cancer treatment. At study entry, women were asked about new symptoms that appeared following their initial cancer treatment. In this article, we were interested in using regression modeling to estimate associations of clinical and lifestyle factors at cancer diagnosis (independent variables) with the number of new symptoms (dependent variable). Although clinical and lifestyle data were collected longitudinally, few measurements were obtained at diagnosis or at a consistent timepoint prior to diagnosis, which complicates the analysis. Furthermore, parametric count models, such as the Poisson and negative binomial, do not fit the symptom data well. Thus, motivated by the issues encountered in LILAC, we propose two Bayesian joint models for longitudinal data and a count outcome. Our two models differ according to the assumption on the outcome distribution: one uses a negative binomial (NB) distribution and the other a nonparametric rounded mixture of Gaussians (RMG). The mean of each count distribution is dependent on imputed values of continuous, binary, and ordinal variables at a time point of interest (e.g. diagnosis). To facilitate imputation, longitudinal variables are modeled jointly using a linear mixed model for a latent underlying normal random variable, and a Dirichlet process prior is assigned to the random subject-specific effects to relax distribution assumptions. In simulation studies, the RMG joint model exhibited superior power and predictive accuracy over the NB model when the data were not NB. The RMG joint model also outperformed an RMG model containing predictors imputed using the last value carried forward, which generated estimates that were biased toward the null. We used our models to examine the relationship between sleep health at diagnosis and the number of new symptoms following breast cancer treatment in LILAC.

Intolerance of Uncertainty and Cognition in Breast Cancer Survivors: The Mediating Role of Anxiety.

Cancer-related cognitive impairment (CRCI) is one of the most prevalent symptoms that breast cancer survivors experience. While cancer treatments are established contributors to CRCI, inter-individual differences in CRCI are not well understood. Individual differences in sensitivity to uncertainty are potential contributors to CRCI; however, no prior studies have attempted to examine this link in the context of breast cancer. To address the gap, we used preliminary findings from an ongoing cross-sectional study. A total of 38 women with stage I-III breast cancer (1-4 years post-treatment) were included in this study. Intolerance of uncertainty (IU) was assessed using the Intolerance of Uncertainty Scale. Self-reported cognitive function was assessed with the Neuro-QoL questionnaire. Anxiety was assessed using the Patient-Reported Outcomes Measurement System Bank. From this study, we found that anxiety mediates the association between IU and cognitive function of survivors. In other words, among post-menopausal breast cancer survivors, those with higher IU showed higher anxiety and consequently had lower cognitive function. This finding suggests that assessing IU may help predict the risk of CRCI. This study expands the current knowledge that addresses the importance of IU as a factor associated with cognitive health.

Self-reported symptoms among cancer survivors in the Women's Health Initiative (WHI) Life and Longevity after Cancer (LILAC) cohort.

PURPOSE: Due to cancer survivors living longer and morbidity associated with cancer treatments, it is necessary to understand symptoms experienced by cancer survivors. This study will analyze the symptom burden among a large cohort of survivors across multiple cancer sites. METHODS: Data from the Women's Health Initiative (WHI) Life and Longevity After Cancer (LILAC) study were used to examine the symptom burden of older cancer survivors. Poisson regression with robust standard errors was utilized to determine differences in symptoms by cancer site, treatment, and other covariates. RESULTS: The most frequently reported symptoms among cancer survivors were fatigue (15.8%) and feeling sad or depressed (14.1%). Multivariable analyses indicated that more symptoms were reported among survivors who were younger (p = 0.002), divorced or separated (p = 0.03), and had a combination of public and private insurance (p = 0.01). Survivors who received chemotherapy (p < 0.001), radiation (p = 0.01), or hormone therapy (p = 0.02) reported more symptoms than survivors who did not receive these treatments. Survivors diagnosed with cancer < 5 years ago reported fewer symptoms than longer-term survivors, particularly those diagnosed > 10 years ago (p = 0.02). CONCLUSIONS: Results indicate that common physical and psychological symptoms are reported across cancer types. Cancer survivors diagnosed with cancer 10 or more years ago reported more symptoms than those recently diagnosed. This suggests that symptoms may remain a problem for some survivors decades after their diagnosis. IMPLICATIONS FOR CANCER SURVIVORS: Future research should focus on implementing active surveillance of cancer survivors. Healthcare providers and those who care for cancer survivors should understand that the symptom burden associated with cancer may persist even decades following diagnosis.

Accelerating Colorectal Cancer Screening and Follow-up through Implementation Science (ACCSIS) in Appalachia: protocol for a group randomized, delayed intervention trial.

Appalachian regions of Kentucky and Ohio are hotspots for colorectal cancer (CRC) mortality in the USA. Screening reduces CRC incidence and mortality; however, screening uptake is needed, especially in these underserved geographic areas. Implementation science offers strategies to address this challenge. The aim of the current study was to conduct multi-site, transdisciplinary research to evaluate and improve CRC screening processes using implementation science strategies. The study consists of two phases (Planning and Implementation). In the Planning Phase, a multilevel assessment of 12 health centers (HC) (one HC from each of the 12 Appalachian counties) was conducted by interviewing key informants, creating community profiles, identifying HC and community champions, and performing HC data inventories. Two designated pilot HCs chose CRC evidence-based interventions to adapt and implement at each level (i.e., patient, provider, HC, and community) with evaluation relative to two matched control HCs. During the Implementation Phase, study staff will repeat the rollout process in HC and community settings in a randomized, staggered fashion in the remaining eight counties/HCs. Evaluation will include analyses of electronic health record data and provider and county surveys. Rural HCs have been reluctant to participate in research because of concerns about capacity; however, this project should demonstrate that research does not need to be burdensome and can adapt to local needs and HC abilities. If effective, this approach could be disseminated to HC and community partners throughout Appalachia to encourage the uptake of effective interventions to reduce the burden of CRC.

We conducted a multi-site study to evaluate and improve CRC screening processes using implementation science strategies at multiple levels including the patient, provider, health center, and community. Our goals were to increase rates of guideline-recommended CRC screening, follow-up, and referral-to-care in an Appalachian, medically underserved population.