Westfall, Erin

ABSTRACT Purpose This study assesses the association between colorectal cancer (CRC) screening and a validated, housing-based measure of individual-level socioeconomic status (SES, called HOUSES hereafter) within rural communities and determines whether HOUSES-integrated geospatial analysis can be used to tailor interventions. Methods We used CRC screening data from a subset of Mayo Clinic Midwest patients living in cities without ready access to routine care in the Mayo Clinic Health System in 2019 to represent rural communities. At the individual level, we assessed the association between CRC screening rates and the HOUSES index, adjusting for age, sex, race/ethnicity, comorbidity, distance from home address to clinic, and area deprivation index, using a multilevel mixed-effects logistic regression model. Additionally, we conducted geospatial analysis to examine the correlation between hotspots of 1) lower CRC screening rates and 2) lower SES of the subject population (HOUSES quartile 1). Findings Among 34,489 individuals (median age 64.0 years, 52.4% female), those with the lowest SES (HOUSES Q1) had 37% lower odds of being CRC screening adherent than those with the highest SES (HOUSES Q4) (adj. OR [95% CI]: 0.63 [0.58-0.69]). In the 14 identified HOUSES Q1 hotspots, there was a significant correlation in counts of HOUSES Q1 and low CRC screening (correlation coefficient=0.81). Conclusion Lower SES was significantly associated with lower CRC screening among rural populations. HOUSES-enabled geospatial analysis identified geographic hotspots with lower CRC screening rates for targeted interventions to address disparities in CRC screening in rural communities. HOUSES may be a useful digital tool for cancer preventive care and research.

Introduction/Objectives The rise in screening for social drivers of health (SDoH) in primary care settings has led to questions about effective intervention design. A large primary care practice at Mayo Clinic developed a model centered on a full-time Health Equity Coordinator (HEC) to facilitate clinic-community partnerships in 2022. The goal of this analysis was to assess the model on process outcomes, resolution of SDoH needs, and changes in healthcare utilization. Methods Using a cohort study design, we identified primary care patients with unmet SDoH needs at the intervention clinic and two comparator clinics from March 2022 to December 2023. We assessed process outcomes descriptively and resolution of SDoH needs and healthcare utilization using multivariable regression. Results The HEC contacted 348 patients and conducted 748 meetings with community-based organization staff. While there were decreases for SDoH needs and missed or late cancelled appointments in intervention group, there were no significant difference in resolution of SDoH and healthcare utilization relative to comparator groups. Conclusions The HEC model for multi-stakeholder coordination showed promise in referring patients to services and engaging key stakeholders in a primary care setting. Longer term follow up may be needed to identify changes in SDoH needs and healthcare utilization.

Abstract Context Evidence supports osteopathic manipulative medicine (OMM) as an effective manual therapy, although it remains underutilized by Doctors of Osteopathic Medicine (DOs). Objectives Understanding barriers preventing the broader adoption of OMM is essential to expanding access to it as a noninvasive treatment option. We set out to survey both DOs and non-DO clinicians to identify perceived barriers to OMM. Methods Survey items were adapted from prior studies utilizing an iterative refinement process that included cycles of pilot testing with revisions. Participants were recruited internally from Mayo Clinic Midwest – a large, multistate, healthcare system in the Midwest region of the United States – utilizing internal email. Participants were given a descriptive survey that was developed with support from the Mayo Clinic Survey Research Center. Results The survey was sent out to a total of 952 individuals, including 184 DOs and 768 non-DO clinicians (MD, Bachelor of Medicine, Bachelor of Surgery [MBBS], nurse practitioners, and physician assistants). Respondents included 76 DOs (41.3 % response rate) and 91 non-DOs (11.8 % response rate). Of the 76 DO respondents, 21 (27.6 %) reported utilizing OMM clinically. Commonly reported barriers include time limitations, poor public perception, and lack of training in residency, and time is allocated to other professional interests. Conclusions Within a large health system that includes primary care and specialty care, few DOs practice OMM, citing time constraints, lack of residency training, and competing professional interests as primary barriers. These challenges might successfully be addressed through targeted osteopathic manipulative treatment (OMT) education in residency programs, enhanced compensation, and improved referral pathways.

Purpose: The sociopolitical determinants of health drive health outcomes and inequities in the United States. Primary care practices are, increasingly, expected by payers and policy makers to assess patients’ social needs. Resource referral platforms provide physicians with information and referral systems for community resources. One commonly used platform is Aunt Bertha/Find Help (AB/FH). The American Academy of Family Physicians (AAFP) Neighborhood Navigator (NN) tool allows physicians and laypeople to search for resources using AB/FH. We sought to describe what users were searching for and to identify patterns to inform resource allocation. Methods: This was a descriptive study of the AAFP’s NN tool. Searches of NN were analyzed to describe what users were searching for. Results: From 2018 to April 2022 there were 168 135 searches. The most common searches were for food and housing insecurity (22%, 21%) and health care referral (20.6%) with 22% more searches in the winter than the spring. There was a 119% increase in searches between 2018 and 2022, and a 47% increase in searches during the COVID-19 Pandemic. In the “Health” category the top 20 subcategories accounted for over 77% of searches. Conclusions: Family physicians and their patients use NN to search AB/FH for community resources to address adverse social determinants of health (SDOH). As expected, searches increased during the COVID-19 pandemic. This type of analysis may help individual clinicians, practices, and health systems prepare for the most common social needs of their patients. Social resource platforms might serve as a robust measure for primary care practice screening and referral for SDOH.

Introduction: Primary care clinicians are presented with hundreds of new clinical recommendations and guidelines. To consider practice change clinicians must identify relevant information and develop a contextual framework. Too much attention to information irrelevant to one’s practice results in wasted resources. Too little results in care gaps. A small group of primary care clinicians in a large health system sought to address the problem of vetting new information and providing peer reviewed context. This was done by engaging colleagues across the system though a primary care learning collaborative. Methods: The collaborative was a grass roots initiative between community and academic-based clinicians. They invited all the system’s primary care clinicians to participate. They selected new recommendations or guidelines and used surveys as the principal communication instrument. Surveys shared practice experience and also invited members to give narrative feedback regarding their acceptance of variation in care relate to the topic. A description of the collaborative along with its development, processes, and evolution are discussed. Process changes to address needs during the COVID-19 pandemic including expanded information sharing was necessary. Results: Collaborative membership reached across 5 states and included family medicine, internal medicine, and pediatrics. Members found involvement with the collaborative useful. Less variation in care was thought important for public health crises: the COVID pandemic and opioid epidemic. Greater practice variation was thought acceptable for adherence to multispecialty guidelines, such as diabetes, lipid management, and adult ADHD care. Process changes during the pandemic resulted in more communications between members to avoid practice gaps. Conclusion: An internet-based learning collaborative in a health system had good engagement from its members. Using novel methods, it was able to provide members with feedback related to the importance of new practice recommendations as perceived by their peers. Greater standardization was thought necessary when adopting measures to address public health crisis, and less necessary when addressing multispecialty guidelines. By employing a learning collaborative, this group was able to keep members interested and engaged. During the first year of the COVID pandemic the collaborative also served as a vehicle to share timely information.