Balls‐Berry, Joyce E.

Abstract Background: Black or African Americans (AA) with Parkinson’s disease (PD) are underrepresented in both care and research and experience significant health disparities. The existing literature provides limited guidance on how to enhance the engagement of AA individuals in PD care and research, particularly from the perspectives of AA patients, care partners, and healthcare providers. This project aimed to (1) describe the use of Community Engagement (CE) Studios as a community-engaged research approach to inform culturally appropriate and inclusive research and (2) examine factors influencing AA engagement in PD-related activities. Methods: We conducted three CE Studios: one with AA with PD and care partners (N = 6), one with healthcare providers of AA with PD (N = 8), and one with AA with PD, care partners, and healthcare providers (N = 4). Results: The CE Studios informed the design (e.g., cultural appropriateness) and conduct (e.g., accessibility) of the planned PD project, as well as identifying stakeholders to engage with, improving alignment between research and the AA community. We highlighted the importance of multifaceted factors, including environmental (e.g., segregation), biological (e.g., symptoms), sociocultural (e.g., not being invited), and behavioral (e.g., empowerment) domains, which influence AA engagement. Conclusions: The CE Studios method is a feasible and useful approach for understanding the perspectives of AA in PD. It is possible to conduct an in-depth exploration of community perspectives by synthesizing comprehensive analyses and leveraging additional frameworks. These efforts include identifying barriers to engagement, recognizing locally relevant individuals, and refining PD-related care to enhance cultural appropriateness.

Abstract Medical researchers are increasingly prioritizing the inclusion of underserved communities in clinical studies. However, mere inclusion is not enough. People from underserved communities frequently experience chronic stress that may lead to accelerated biological aging and early morbidity and mortality. It is our hope and intent that the medical community come together to engineer improved health outcomes for vulnerable populations. Here, we introduce Health Equity Engineering (HEE), a comprehensive scientific framework to guide research on the development of tools to identify individuals at risk of poor health outcomes due to chronic stress, the integration of these tools within existing healthcare system infrastructures, and a robust assessment of their effectiveness and sustainability. HEE is anchored in the premise that strategic intervention at the individual level, tailored to the needs of the most at-risk people, can pave the way for achieving equitable health standards at a broader population level. HEE provides a scientific framework guiding health equity research to equip the medical community with a robust set of tools to enhance health equity for current and future generations.

AbstractBackgroundAs the population ages in the United States, the prevalence of many diseases like Alzheimer disease, related dementias, and Parkinson disease disproportionately affect those already at greatest risk for premature morbidity and mortality. Aging research has an opportunity to engage and support patients, communities, and caregivers most impacted by these diseases. However, under‐resourced communities frequently lack representation in research, causing decreased generalizability of study results and health inequities among these communities.MethodsUsing a community and patient engaged framework, we conducted three community engagement studios (studios) with caregivers, patients, providers, researchers, and advocates from the St. Louis community. The studios provide community input and recommendations on project feasibility, design, and cultural appropriateness. Proposed projects were presented during each studio, followed by a facilitated discussion with a neutral facilitator. Themes were derived using traditional qualitative content analysis.ResultsStakeholders included under‐resourced community members, LGBTQIA+ participants, and those without/inadequate health insurance. The main themes included participant commitment to health, culturally appropriate research design, and incentives. In addition, participants desired collaboration between researchers and the community, including connecting with local Alzheimer’s Disease Associations, faith‐based groups, and philanthropic organizations.ConclusionOur community stakeholders provided feedback on how we could modify the research design to increase community involvement, enhance participant recruitment and commitment, and reach populations currently underrepresented in aging research, especially Alzheimer’s disease. The early inclusion of stakeholders in research design and implementation constitutes a preliminary step to building trust within under‐resourced communities and increasing the recruitment and retention of diverse populations.

Uterine fibroids are noncancerous tumors associated with significant morbidity among symptomatic patients. While medical and surgical treatments have expanded, hysterectomy remains common. We interviewed women diagnosed with uterine fibroids ( n = 47) to explore their experiences and recommendations for shared decision-making. A majority were non-Hispanic Black, highly educated (51.1%), and had graduate degrees (40.4%). Participants with both positive and negative provider experiences expressed a desire for a more proactive therapeutic approach, including a presentation by their provider of the spectrum of medical and surgical treatment options, and greater provider recognition of the impact of symptoms on quality of life. Women advocated for expanded shared decision-making that acknowledged their contribution to their own treatment plan and felt early screening and improved patient/provider education of uterine fibroid symptoms would facilitate greater congruence between treatment approaches and patient goals. Perceptions of insufficient input into their treatment plans frequently served as a barrier to care-seeking and treatment acceptance among women with uterine fibroid symptoms. Improved discussion of treatment options in the context of the unique symptom burden and values of the patient may facilitate greater provider trust and acceptance of uterine fibroid treatment.

Background . There is growing evidence that social and behavioral determinants of health (SBDH) play a substantial effect in a wide range of health outcomes. Electronic health records (EHRs) have been widely employed to conduct observational studies in the age of artificial intelligence (AI). However, there has been limited review into how to make the most of SBDH information from EHRs using AI approaches. Methods . A systematic search was conducted in six databases to find relevant peer-reviewed publications that had recently been published. Relevance was determined by screening and evaluating the articles. Based on selected relevant studies, a methodological analysis of AI algorithms leveraging SBDH information in EHR data was provided. Results . Our synthesis was driven by an analysis of SBDH categories, the relationship between SBDH and healthcare-related statuses, natural language processing (NLP) approaches for extracting SBDH from clinical notes, and predictive models using SBDH for health outcomes. Discussion . The associations between SBDH and health outcomes are complicated and diverse; several pathways may be involved. Using NLP technology to support the extraction of SBDH and other clinical ideas simplifies the identification and extraction of essential concepts from clinical data, efficiently unlocks unstructured data, and aids in the resolution of unstructured data-related issues. Conclusion . Despite known associations between SBDH and diseases, SBDH factors are rarely investigated as interventions to improve patient outcomes. Gaining knowledge about SBDH and how SBDH data can be collected from EHRs using NLP approaches and predictive models improves the chances of influencing health policy change for patient wellness, ultimately promoting health and health equity.

Abstract IntroductionRacially and ethnically diverse minorities often experience the disease burden of sexually transmitted infections or diseases (STD) more often than their White counterparts. Yet, little is known about the connection of STD systematic discrimination, racism, and social and behavioral determinants. Plus, little to no details exists related to how this information is recorded in their Electronic Health Records (EHRs). The objective of this study is to assess the completeness of social and behavioral determinants of health (SDOH) data in the EHRs of a minority cohort with STD.Materials and Methods2,993 minority patients diagnosed with a STD at the Mayo Clinic were identified for this study. A natural language processing (NLP) algorithm was applied on the Patient-Provided Information (PPI) in their EHRs to extract SDOH information in six domains that are associated with STD, namely alcohol use, substance use, sexual activity, sexual orientation, housing status, and employment status. The completeness of SDOH was assessed in terms of documentation, breadth, and density.ResultsOur study indicates that nearly half of 2,993 patients did not have SDOH-related PPI records in their EHRs whereas the patients who had SDOH-related PPI records had well-documented records for five out of six SDOH domains, including alcohol use, substance use, sexual activity, housing status, and employment status, except for sexual orientation. A total of 1,504 patients had PPI in their EHRs for at least one of six SDOH domains, which is about 50.3% of the study cohort. Most SDOH domains have a short time span of 1 year, with up to 18 years of record data. Our analysis also indicated that education and age have a significant impact on the recording of SDOH-related PPI records. Patients that are female, older, and higher educated tend to have more SDOH information available in their records.Discussion and ConclusionWe assessed the completeness of SDOH information recorded in the PPI from patients’ EHRs. Due to large amounts of missing SDOH information in the PPI, future research is needed to integrate accurate and robust SDOH related data for downstream research and the impact of systematic discrimination on how this information is collected and interpreted in the EHRs.

Health disparities and social determinants of health are directly linked to access, quality of healthcare, and increase in morbidity and mortality in minority and diverse communities. It is accepted that physicians lead healthcare teams; therefore, academic medical centers must assume the responsibility to provide training to reduce health disparities. The nation's academic medical centers and teaching hospitals have a responsibility to provide education on how healthcare disparities impacts diverse patient populations. This chapter provides a detailed overview of the curriculum development process and design of two asynchronous learning modules on health disparities and social determinants of health for graduate medical learners enrolled in multiple clinical specialty areas throughout one academic medical center's three geographic regional campuses. Formative and summative evaluation processes allowed the curriculum design team to revise the module design process, in situ and throughout the creation of the modules as well as evaluate learner growth and satisfaction.