Nadine Barrett

BACKGROUND: Implementation methods of risk-stratified cancer screening guidance throughout a health care system remains understudied. OBJECTIVE: Conduct a preliminary analysis of the implementation of a risk-stratified prostate cancer screening algorithm in a single health care system. DESIGN: Comparison of men seen pre-implementation (2/1/2016-2/1/2017) vs. post-implementation (2/2/2017-2/21/2018). PARTICIPANTS: Men, aged 40-75 years, without a history of prostate cancer, who were seen by a primary care provider. INTERVENTIONS: The algorithm was integrated into two components in the electronic health record (EHR): in Health Maintenance as a personalized screening reminder and in tailored messages to providers that accompanied prostate-specific antigen (PSA) results. MAIN MEASURES: Primary outcomes: percent of men who met screening algorithm criteria; percent of men with a PSA result. Logistic repeated measures mixed models were used to test for differences in the proportion of individuals that met screening criteria in the pre- and post-implementation periods with age, race, family history, and PSA level included as covariates. KEY RESULTS: During the pre- and post-implementation periods, 49,053 and 49,980 men, respectively, were seen across 26 clinics (20.6% African American). The proportion of men who met screening algorithm criteria increased from 49.3% (pre-implementation) to 68.0% (post-implementation) (p < 0.001); this increase was observed across all races, age groups, and primary care clinics. Importantly, the percent of men who had a PSA did not change: 55.3% pre-implementation, 55.0% post-implementation. The adjusted odds of meeting algorithm-based screening was 6.5-times higher in the post-implementation period than in the pre-implementation period (95% confidence interval, 5.97 to 7.05). CONCLUSIONS: In this preliminary analysis, following implementation of an EHR-based algorithm, we observed a rapid change in practice with an increase in screening in higher-risk groups balanced with a decrease in screening in low-risk groups. Future efforts will evaluate costs and downstream outcomes of this strategy.

BACKGROUND: Approximately 15% of all cancers are due to infection. The bacteria Helicobacter pylori is the single leading carcinogenic infectious agent and the main cause of stomach cancer. Prevalence of H. pylori, and, correspondingly, stomach cancer incidence and mortality, is significantly greater among African Americans than whites in the United States. In the present study, we conducted a pilot community-engaged H. pylori education and screening study in partnership with a predominantly African American church in Durham, North Carolina. METHODS: Initially, we consulted with community advisory boards and convened stakeholder meetings with local community members and primary care physicians. We then developed this pilot study through an iterative collaboration with church partners. Our main outcomes were feasibility and acceptability as measured by participation in a one-day H. pylori screening initiative, and participation in follow-up for those who tested positive. We also sought to determine prevalence and determinants of active H. pylori infection in this population. RESULTS: Community engagement informed the event logistics, messaging, educational materials provided, and follow-up plans. A total of 92 individuals participated in the primary study event, 25% of whom had a current H. pylori infection. Of those, 87% returned for the follow-up events, among whom 70% had successfully cleared their infection. CONCLUSIONS: Through community engagement, community-based H. pylori screening and stomach cancer prevention is feasible and acceptable. This is a necessary step in order to move stomach cancer prevention forward to population-based precision H. pylori screening and eradication.

BACKGROUND: Engaging diverse populations in biomedical research, including biospecimen donation, remains a national challenge. This study examined factors associated with an invitation to participate in biomedical research, intent to participate in biomedical research in the future, and participation in biomedical research and biospecimen donation among a diverse, multilingual, community-based sample across 3 distinct geographic areas. METHODS: Three National Cancer Institute-designated cancer centers engaged in community partnerships to develop and implement population health assessments, reaching a convenience sample of 4343 participants spanning their respective catchment areas. Data harmonization, multiple imputation, and multivariable logistic modeling were used. RESULTS: African Americans, Hispanic/Latinos, and other racial minority groups were more likely to be offered opportunities to participate in biomedical research compared to whites. Access to care, history of cancer, educational level, survey language, nativity, and rural residence also influenced opportunity, intent, and actual participation in biomedical research. CONCLUSIONS: Traditionally underserved racial and ethnic groups reported heightened opportunity and interest in participating in biomedical research. Well-established community partnerships and long-standing community engagement around biomedical research led to a diverse sample being reached at each site and may in part explain the current study findings. However, this study illustrates an ongoing need to establish trust and diversify biomedical research participation through innovative and tailored approaches. National Cancer Institute-designated cancer centers have the potential to increase opportunities for diverse participation in biomedical research through community partnerships and engagement. Additional work remains to identify and address system-level and individual-level barriers to participation in both clinical trials and biospecimen donation for research.

Achieving cancer health equity is a national imperative. Cancer is the second leading cause of death in the United States and in North Carolina (NC), where the disease disproportionately impacts traditionally underrepresented race and ethnic groups, those who live in rural communities, the impoverished, and medically disenfranchised and/or health-disparate populations at high-risk for cancer. These populations have worse cancer outcomes and are less likely to be participants in clinical research and trials. It is critical for cancer centers and other academic health centers to understand the factors that contribute to poor cancer outcomes, the extent to which they impact the cancer burden, and develop effective interventions to address them. Key to this process is engaging diverse stakeholders in the development and execution of community and population health assessments, and the subsequent programs and interventions designed to address the need across the catchment area. This chapter describes the processes and lessons learned of the Duke Cancer Institute's (DCI) long standing community partnerships that led to Project PLACE (Population Level Approaches to Cancer Elimination), a National Cancer Institute (NCI)-funded community health assessment reaching 2315 respondents in 7 months, resulting in a community partnered research agenda to advance cancer equity within the DCI catchment area. We illustrate the application of a community partnered health assessment and offer examples of strategic opportunities, successes, lessons learned, and implications for practice.

This Longitudinal patient navigation Matrix Model was developed to overcome barriers across the cancer care continuum by offering prepatients, patients, and their families with support services. The extraordinary heterogeneity of patient needs during cancer screening, risk assessment, treatment, and survivorship as well as the vast heterogeneity of oncology care settings make it nearly impossible to follow a static navigation model. Our model of patient cancer navigation is unique as it enhances the traditional model by being highly adaptable based on both patient and family needs and scalable based on institutional needs and resources (eg, clinical volumes, financial resources, and community-based resources). This relatively new operational model for system-wide and systematic navigation incorporates a carefully cultivated supportive care program that evolved over the last decade from a bottom up approach that identified patient and family needs and developed appropriate resources. A core component of this model includes shifting away from department-centric operations. This model does not require a patient to opt in or independently be able to report their needs or ask for services-it is an opt out model. The multidisciplinary "cross-training" model can also facilitate reimbursement and sustainability by clarifying the differentiating actions that define navigation services: identification of barriers to quality care and specific actions taken to overcome those barriers, across the full continue of cancer care from community engagement to survivorship or end-of-life care.