Disparities In Health Care Outcomes Research Articles

Gender-Specific Impacts of the COVID-19 Pandemic on Orthopedic and Traumatology Care: An Analysis of Hospital Admissions and Length of Stay.

Understanding gender disparities in healthcare outcomes is crucial, especially during crises like the COVID-19 pandemic. The absence of gender-specific data on hospital admissions and lengths of stay for orthopedic and traumatology patients limits the precision of current analyses, making conclusions speculative. This study aims to highlight the potential insights that could be gained from gender-disaggregated data, illustrating how a more precise gender-based analysis could reveal healthcare disparities in orthopedic and trauma care during the pandemic. A robust analysis would require gender-disaggregated data, including variables such as admission rates, lengths of stay, injury types, and access to care, along with factors like age and socioeconomic status. In the absence of such data, a hypothetical framework was developed based on known healthcare disparities, using general trends to project possible gender-specific impacts. Without gender-disaggregated data, it remains challenging to identify specific gender differences in outcomes accurately. Hypothetical scenarios suggest that disparities in admission rates, hospital stay durations, and access to care could be influenced by factors such as increased caregiving responsibilities for women or differential access to healthcare based on socioeconomic status. To accurately assess gender disparities in orthopedic and trauma care during the pandemic, future studies must prioritize the collection and use of gender-disaggregated data. This approach is essential for drawing reliable conclusions and developing targeted interventions to address healthcare inequities effectively.

B-110 Descriptive Analysis of Multiple Myeloma Participants in the NIH All of Us Research Program Cohort: Insights into Demographics Disparities

Abstract Background Multiple Myeloma (MM) is a complex hematological malignancy characterized by significant heterogeneity in participant characteristics and treatment responses. The All of Us Research Program seeks to enroll 1 million diverse participants who share multiple sources of data, providing unique opportunities for research. A comprehensive descriptive analysis of MM participants within Electronic Health Records (EHR) databases can provide valuable insights into the disease's epidemiology, participant demographics, comorbidities, and treatment outcomes. Objective Using AI/ML predictive analytics, this study conducted a detailed descriptive analysis of MM participants’ EHR data in the All of Us Research Program cohort, which is enrolling 1 million diverse participants who share multiple sources of data. Methods We extracted data for participants diagnosed with MM from an extensive EHR database. The analysis included participant demographics (age, gender, race, ethnicity), diagnostic laboratory tests (SPEP, UPEP, CBC, renal function), comorbidities (renal impairment, bone disease, anemia, cardiovascular diseases), treatment details (chemotherapy, stem cell transplantation), and genetic markers (cytogenetic abnormalities). Results The analysis revealed diverse demographic patterns and a wide range of comorbidities associated with MM (Table 1). Conclusions The analysis demonstrated marked disparities in MM prevalence among African Americans and “More than one race,” revealing social and medical disparities. Implications: By understanding the diverse profiles of MM participants, stakeholders can more effectively address disparities in healthcare outcomes (1). Reference: 1. Zeng, C., Schlueter, D. J., Tran, T. C., Babbar, A., Cassini, T., Bastarache, L. A., & Denny, J. C. (2024). Comparison of phenomic profiles in the All of Us Research Program against the US general population and the UK Biobank. Journal of the American Medical Informatics Association. Retrieved from, https://doi.org/10.1093/jamia/ocad260

Epidemiology of Patient Record Duplication.

Duplicate patient records can increase cost and medical errors. We assessed the association between demographic factors, comorbidities, healthcare usage and duplicate electronic health records. We analyzed the association between duplicate patient records and multiple demographic variables (race, Hispanic ethnicity, sex and age) as well as Charlson comorbidity index (CCI), number of diagnoses, and number of healthcare encounters. The study population included 3,018,413 patients seen at a large urban academic medical center with at least one recorded diagnosis. Duplication of patient medical records was determined by using a previously validated enterprise Master Person Index. Unknown or missing demographic data, Black race when compared to White Race (OR 1.35, p < 0.001), Hispanic compared to non-Hispanic ethnicity (OR 1.48, p < 0.001), older age (OR 1.01, p < 0.001), and "Other" sex compared to female sex (OR 4.71, p < 0.001) were associated with higher odds of having a duplicate record. Comorbidities (CCI, OR 1.10, p < 0.001) and more encounters with the health care system (OR 1.01, p < 0.001) were also associated with higher odds of having a duplicate record. In contrast, male sex compared to female sex was associated with lower odds of having a duplicate record (OR 0.88, p < 0.001). The odds of duplications in medical records were higher in Black, Hispanic, older, non-male patients with more healthcare encounters, more comorbidities, and unknown demographic data. Understanding the epidemiology of duplicate records can help guide prevention and mitigation efforts for high-risk populations. Duplicate records can contribute to disparities in health care outcomes in minority populations.

A health equity monitoring framework based on process mining.

In the United States, there is a proposal to link hospital Medicare payments with health equity measures, signaling a need to precisely measure equity in healthcare delivery. Despite significant research demonstrating disparities in health care outcomes and access, there is a noticeable gap in tools available to assess health equity across various health conditions and treatments. The available tools often focus on a single area of patient care, such as medication delivery, but fail to examine the entire health care process. The objective of this study is to propose a process mining framework to provide a comprehensive view of health equity. Using event logs which track all actions during patient care, this method allows us to look at disparities in single and multiple treatment steps, but also in the broader strategy of treatment delivery. We have applied this framework to the management of patients with sepsis in the Intensive Care Unit (ICU), focusing on sex and English language proficiency. We found no significant differences between treatments of male and female patients. However, for patients who don't speak English, there was a notable delay in starting their treatment, even though their illness was just as severe and subsequent treatments were similar. This framework subsumes existing individual approaches to measure health inequities and offers a comprehensive approach to pinpoint and delve into healthcare disparities, providing a valuable tool for research and policy-making aiming at more equitable healthcare.

Racial Disparities Exist in 90-Day Unplanned Return to the Emergency Department Following Orthopaedic Trauma Surgery.

Racial disparities in healthcare outcomes exist, including in orthopaedic trauma care. The aim of this study was to determine the impact of race, social deprivation, and payor status on 90-day emergency department (ED) revisits among orthopaedic trauma surgery patients at a Level 1 trauma academic medical center. Retrospective chart review analysis. Level 1 trauma academic center in Durham, NC. Adult patients undergoing orthopaedic trauma surgery between 2017 and 2021. The primary outcome of this retrospective cohort study was 90-day return to the ED. Logistic regression analysis was performed for variables of interest [race, social deprivation (measured by the Area Deprivation Index), and payor status] separately and combined, with each model adjusting for distance to the hospital. Results were interpreted as odds ratios (ORs) of 90-day ED revisits comparing levels of the respective variables. Statistical significance was assessed at α = 0.05. A total of 3120 adult patients who underwent orthopaedic trauma surgery between 2017 and 2021 were included in the analysis. Black race (OR = 1.47; 95% confidence interval [CI]: 1.17-1.84, P < 0.001) and Medicaid coverage (OR = 1.63, 95% CI: 1.20-2.21, P = 0.002) were significantly associated with higher odds of return to ED compared with non-Black or non-Medicaid-covered patients. While ethnic minority (Hispanic/Latino or non-White) was statistically significant while adjusting only for distance to the hospital (OR = 1.23, 95% CI: 1.00-1.50, P = 0.047), it was no longer significant after adjusting for the other sociodemographic variables (OR = 1.13, 95% CI: 0.91-1.39, P = 0.27). The weighted Area Deprivation Index was not associated with a difference in odds of return to ED in any adjusted models. The results highlight the presence of racial and socioeconomic disparities in ED utilization, with Black race and Medicaid coverage significantly associated with higher odds of return to the ED. Future research should delve deeper into comprehending the root causes contributing to these racial and socioeconomic utilization disparities and evaluate the effectiveness of targeted interventions to reduce them. Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Exploring the Socio-economic Ramifications of Health Literacy and Medication Adherence on Hypertensive Patients

"This analysis examines the intricate interactions that exist link medication adherence, health literacy, and the socio-economic effects on individuals with hypertension. Hypertension, one of the most prevalent chronic conditions worldwide, requires in-depth understanding of the intricate relationships that exist between patients’ access to health information, adherence to prescribed treatment plans, and the broader socio-economic context. The appraisal reviews recent studies on the health literacy’s effect on hypertension patients’ adherence to medicine, with a focus on the contributions of social, institutional, and personal factors. It also examines the socio-economic consequences of low medication adherence and health literacy, emphasizing disparities in healthcare outcomes, increased medical costs, and worse life quality. This study looks at different methods to raise the level of health literacy and medication adherence in hypertensive populations, both individual and systemic. It emphasizes the significance of patient education programs, tailored communication strategies, and system innovations to address the unique challenges confronted by people with differing degrees of health knowledge. Furthermore, the study investigates the potential financial benefits of enhancing medication compliance and health literacy, illustrating how targeted interventions could reduce medical expenses, prevent problems, and foster a more robust community. It emphasizes the need for collaboration between lawmakers, communities, and medical professionals in order to enact workable policies and decrease the socio-economic toll that hypertension has. The intricate interactions between medication adherence, health literacy, and socio-economic determinants in relation to hypertension are highlighted in the analysis’s conclusion. By understanding and addressing these characteristics, healthcare stakeholders can develop targeted treatments to improve outcomes for patients with hypertension, advance health equity, and improve societal well-being."

Closing the gap on healthcare quality for equity-deserving groups: a scoping review of equity-focused quality improvement interventions in medicine

IntroductionQuality improvement (QI) efforts are critical to promoting health equity and mitigating disparities in healthcare outcomes. Equity-focused QI (EF-QI) interventions address the unique needs of equity-deserving groups and the root...

The impact of artificial intelligence on medical diagnostics: A letter to the editor

Madam, Artificial intelligence (AI) describes the generation of intelligent machines that are capable of carrying out activities that usually call for human intellect. (1) It involves creating algorithms and models that enable computers to learn from and analyze vast amounts of data, recognize patterns, make decisions, and even engage in natural language processing. (2) AI has become increasingly important in various fields due to its potential to automate complex processes, enhance efficiency, and drive innovation. It can transform industries, improve decision-making, and revolutionize how we live and work. In medical diagnostics, AI has had a profound impact on improving accuracy, efficiency, and patient outcomes. By leveraging machine learning algorithms, AI systems can process and analyze large volumes of medical data, including patient records, laboratory results, medical images, and genomic data. This allows for more accurate and timely diagnoses, as AI algorithms can detect subtle patterns and anomalies that may not be visible to human observers. AI-powered diagnostics can assist healthcare professionals in detecting diseases, predicting patient outcomes, and designing personalized treatment plans. (3) Furthermore, AI can contribute to the early detection of diseases, thereby enabling timely interventions and improving patient survival rates. For example, AI algorithms analyze medical imaging data, such as X-rays, MRIs, and CT scans, to detect abnormalities and potential signs of diseases like cancer. This helps radiologists and clinicians identify and diagnose conditions early when treatment options are more effective. (4) Additionally, AI aids in interpreting genetic data, allowing for the identification of genetic markers associated with specific diseases or drug responses. This information guides clinicians in selecting the most suitable treatment options for individual patients, leading to improved therapeutic outcomes. (5) AI in medical diagnostics also faces hurdles with data privacy and accessibility, as patient information must be handled securely. Ensuring AI algorithms are unbiased, and fair is a challenge to avoid disparities in healthcare outcomes. The interpretability of AI models is vital to building trust with healthcare professionals and facilitating their adoption. Regulatory compliance and ethical considerations are also significant factors that need to be addressed for the responsible and effective integration of AI in the medical field. In conclusion, Artificial Intelligence (AI) is a transformative technology with the potential to revolutionize various industries, including medical diagnostics. Its ability to analyze vast amounts of data, recognize patterns, and make intelligent decisions has proven invaluable in improving diagnostic processes accuracy, efficiency, and effectiveness. ---Continue

Challenges of artificial intelligence in medicine and dermatology

Artificial intelligence (AI) in medicine and dermatology brings additional challenges related to bias, transparency, ethics, security, and inequality. Bias in AI algorithms can arise from biased training data or decision-making processes, leading to disparities in health care outcomes. Addressing bias requires careful examination of the data used to train AI models and implementation of strategies to mitigate bias during algorithm development. Transparency is another critical challenge, as AI systems often operate as black boxes, making it difficult to understand how decisions are reached. Ensuring transparency in AI algorithms is vital to gaining trust from both patients and health care providers. Ethical considerations arise when using AI in health care, including issues such as informed consent, privacy, and the responsibility for the decisions made by AI systems. It is essential to establish clear guidelines and frameworks that govern the ethical use of AI, including maintaining patient autonomy and protecting sensitive health information. Security is a significant concern in AI systems, as they rely on vast amounts of sensitive patient data. Protecting these data from unauthorized access, breaches, or malicious attacks is paramount to maintaining patient privacy and trust in AI technologies. Lastly, the potential for inequality arises if AI technologies are not accessible to all populations, leading to a digital divide in health care. Efforts should be made to ensure that AI solutions are affordable, accessible, and tailored to the needs of diverse communities, mitigating the risk of exacerbating existing health care disparities. Addressing these challenges is crucial for AI's responsible and equitable integration in medicine and dermatology.

Ethnic disparities in the incidence of gynecologic malignancies among Israeli Women of Arab and Jewish Ethnicity: a 10-year study (2010-2019).

Ethnic disparities in healthcare outcomes persist, even when populations share the same environmental factors and healthcare infrastructure. Gynecologic malignancies are a significant health concern, making it essential to explore how these disparities manifest in terms of their incidence among different ethnic groups. To investigate ethnic disparities in the incidence of gynecologic malignancies incidence among Israeli women of Arab and Jewish ethnicity. Our research employs a longitudinal, population-based retrospective cohort design. Data on gynecologic cancer diagnoses among the Israeli population from 2010 to 2019 was obtained from a National Registry. Disease incidence rates and age standardization were calculated. A comparison between Arab and Jewish patients was performed, with Poisson regression models being used to analyze significant rate changes. Among Jewish women, the age-standardized ratio (ASR) for gynecologic malignancies decreased from 288 to 251 (p < 0.001) between 2014 and 2019. However, there was no significant change in the ASR among Arab women during the same period, with rates going from 192 to 186 (p = 0.802). During the study period, the incidence of ovarian cancer decreased significantly among Jewish women (p = 0.042), while the rate remained stable among Arab women (p = 0.102). A similar trend was observed for uterine cancer. The ASR of CIN III (Cervical Intraepithelial Neoplasia Grade 3) in Jewish women notably increased from 2017 to 2019, with an annual growth rate of 43.3% (p < 0.001). A similar substantial rise was observed among Arab women, with an annual growth rate of 40.5% (p < 0.001). In contrast, the incidence of invasive cervical cancer remained stable from 2010 to 2019 among women of both ethnic backgrounds. Our findings indicate that Arab women in Israel have a lower incidence rate of gynecologic cancers, warranting further investigation into protective factors. Both ethnic groups demonstrate effective utilization of cervical screening.

Predictors of Readmission and Reoperation Following Shoulder Arthroplasty in Patients Under 45 Years of Age.

The use of shoulder arthroplasty has increased among all age groups, albeit most prominently in older patients. While previous studies have investigated predictors of short-term readmission and reoperation in the general population, there is a paucity of literature available on these in patients under 45 years of age. This study aimed to identify the predictors of 30-day readmission and reoperation following shoulder arthroplasty in patients under 45 years of age. A retrospective query in the American College of Surgeons National Surgical Quality Improvement Program database from 2011 to 2019 was used to identify patients who underwent primary reverse and anatomic total shoulder arthroplasty and hemiarthroplasty. Multivariate logistic regression was used to identify predictors of 30-day readmission and reoperation. A total of 530 patients were included. Multivariate regression revealed that Black race and Hispanic ethnicity were independent predictors of readmission. Functional dependence, hypertension requiring medication, and prolonged length of stay predicted reoperation. Finally, low hematocrit and prolonged length of stay predicted morbidity. Identifying and accounting for these risk factors for poor outcomes may help improve perioperative risk stratification. As a result, these findings have the potential to reduce healthcare costs associated with readmission and reoperation following shoulder arthroplasty in young patients. Our results also highlight the underlying disparities in healthcare outcomes among racial and ethnic groups that must be considered.

Racial Disparities in Clinical Outcomes of Emergency Colectomies for Diverticulitis.

The literature suggests that there are ongoing racial disparities in healthcare outcomes between patients in White and non-White populations. As such, we examined the outcomes of patients who underwent an emergency colectomy for diverticulitis. We identified 4841 White and 590 non-White patients, which include Black/African American and Asian patients, using the 2016-2019 American College of Surgeons National Surgical Quality Improvement Program databases. We compared Black/African American and Asian patients with White patients for differences in surgical outcomes. Non-White patients had more comorbidities than White patients (P < 0.05). These patients underwent longer operations, developed more postoperative complications, and were more likely to have lengths of stay >30 days. When controlling for all of the covariates in multivariate logistic regression models, White race was independently associated with a 22.14% lower odds of a hospital stay >30 days compared with non-White patients (P = 0.001). In this study, non-White patients developed more complications than did White patients and had longer hospitalizations. These disparities represent a more complex societal issue that cannot be managed perioperatively alone.

The Effect of Implementing a Colorimetric Quantitative Blood Loss System for Identification of Postpartum Hemorrhage [ID: 1377803

INTRODUCTION: Maternal mortality rates have increased to 23.8 per 100,000 live births in 2020, with the rate for non-Hispanic Black patients 2.9 times greater than non-Hispanic White patients in 2020. Postpartum hemorrhage (PPH) is responsible for approximately half of maternal morbidity. Many PPHs are preventable, and are due to delay in recognition. Disparities in health care outcomes are related to systemic racism, and implicit bias. Improvement requires developing and implementing standardized protocols. The California Maternal Quality Care Collaborative (CMQCC) developed a hemorrhage tool kit, featuring accurate quantitative assessment of blood loss (QBL) as a cornerstone to address these issues. Our main objective was whether implementation of a colorimetric-based QBL would identify PPH at earlier stages and improve maternal outcomes. METHODS: This is a retrospective case–control study comparing incidence of PPH, stage of PPH, maternal morbidity and length of stay, stratified by race and ethnicity, 1 year before and after implementation of a colorimetric-based QBL system. RESULTS: There was a 178% increase in overall identification of PPH from 5.1% to 14.2%. There was an increase in identification of stage I PPH, and decrease in stage II and stage III PPH. Total intensive care unit (ICU) admissions decreased from nine to zero. In non-Hispanic Black patients, PPH increased from 3.6% to 13.8%, with increased identification of stage I PPH. CONCLUSION: An unbiased colorimetric-based system for QBL during delivery and postpartum leads to earlier identification of postpartum hemorrhage in all patients regardless of ethnicity or race, a decrease in total ICU admissions, and shorter length of stay, overall increasing maternal outcomes.

Executive summary of the SAEM 2022 consensus conference to address racism in emergency medicine clinical research, training, and leadership.

Racism has not only contributed to disparities in health care outcomes, but also has negatively impacted the recruitment, retention, and promotion of historically excluded groups in academic medicine. The 2022 Society for Academic Emergency Medicine (SAEM) consensus conference, "Diversity, Equity, and Inclusion: Developing a Research Agenda for Addressing Racism in Emergency Medicine," convened a diverse group of researchers, educators, administrative leaders, and health care providers to help address the impact of racism in three domains in academic emergency medicine: clinical research, education and training, and academic leadership. The main goals of the consensus process were to identify current knowledge gaps and create a research agenda within each domain using an iterative consensus-building methodology. The planning committee identified three fundamental domains to develop a research agenda and created workgroups who completed a literature search to identify gaps in knowledge. After a consensus building process, potential questions were presented at the in-person consensus conference. Ninety SAEM members representing faculty and trainees participated in breakout groups in each domain to generate consensus recommendations for priority research. For clinical research, three research gaps with six questions (n) were identified: remedies for bias and systematic racism (3), biases and heuristics in clinical care (2), and racism in study design (1). For education and training, three research gaps with seven questions were identified: curriculum and assessment (2), recruitment (1), and learning environment (4). For academic leadership, three research gaps with five questions were identified: understanding the current diversity, equity, and inclusion (DEI) landscape and culture (1), analyzing programs that improve DEI and identifying factors that lead to improved diversity (3), and quantifying the value of professional stewardship activities (1). This article reports the results of the consensus conference with the goal of influencing emergency care research, education, and policy and facilitating collaborations, grant funding, and publications in these domains.

Racial and ethnic differences in patients enrolled in the national bronchiectasis and nontuberculous mycobacteria research registry

Demographic and socioeconomic factors are recognized to contribute to disparities in healthcare outcomes. Originally, bronchiectasis was described in a population of predominantly White ethnic group of patients in which racial disparity could not be identified. The U.S. Bronchiectasis Research Registry (BRR), a centralized database of adult patients with bronchiectasis and/or NTM from 18 clinical institutions across the U.S., was created to support the research of this condition. The aim of this study is to describe the racial and ethnic distribution of patients enrolled in the BRR and evaluate factors associated with healthcare disparities within manifestations of and/or the care delivered to this population.At the time of this study, 3600 patients with bronchiectasis and/or NTM were enrolled in the BRR. Of those, 3510 participants were included in these analyses. The population was predominantly non-HispanicWhite (n = 3143, 89.5%), followed by Hispanic or Latino (n = 149, 4.3%), Asian (n = 130, 3.7%) and non-Hispanic Black (n = 88, 2.5%) participants. Testing for cystic fibrosis, immunoglobulin deficiency, and mycobacteria was not different between races, but non-Hispanic Black patients were tested less frequently for alpha-1 antitrypsin (A1AT) deficiency compared to other groups (P = 0.01). The four groups did not differ in the proportion of Pseudomonas aeruginosa or Hemophilus influenzae. There was no statistically significant difference in use of high-frequency chest wall oscillation, pulmonary rehabilitation services, or suppressive macrolide treatment across the groups (P > 0.05).There is a disproportionately high percentage of non-Hispainc White patients compared to non-Hispanic Black patients and Hispanic or Latino patients in the BRR. However, we found an overall similarity of care of BRR patients, regardless of racial and ethnic group.

Identifying Risk Factors for Blindness From Glaucoma at First Presentation to a Tertiary Clinic

Glaucoma is the leading cause of irreversible blindness, a crippling disability resulting in higher risks of chronic health conditions. To better understand disparities in blindness risk, we identified risk factors of blindness on first presentation to a glaucoma clinic using a large clinical database. Retrospective cross-sectional study. We used electronic health records of glaucoma patients from the Duke Ophthalmic Registry. International Classification of Diseases codes were used to identify glaucoma and exclude concurrent diseases. Blindness classification was based on the definition of legal blindness. Risk factors included gender, race, marital status, age, intraocular pressure, diabetes history, income level, and education. Odds ratios (ORs) and 95% CIs were calculated for risk factors using univariable and multivariable logistic regression. Our cohort consisted of 3753 patients, with 192 (5%) blind on first presentation. In univariable models, African American / Black race (OR 2.48, 95% CI 1.83-3.36), single marital status (1.74, 95% CI 1.25-2.44), prior diabetes diagnosis (2.23, 95% CI 1.52-3.27), and higher intraocular pressure (1.29 per 1 SD higher, 95% CI 1.13-1.46) were associated with increased risk of presenting blind, whereas higher annual income (0.75, 95% CI 0.65-0.86) and education (0.77, 95% CI 0.69-0.85) were associated with lower risk. These associations remained significant and in the same direction in a multivariable model apart from income, which became insignificant. Using a large real-world clinical database, we identified risk factors associated with presentation with blindness among glaucoma patients. Our results highlight disparities in health care outcomes and indicate the importance of targeted education to reduce disparities in blindness.

"I Think [Western] Healthcare Fails Them": Qualitative Perspectives of State-recognized Women Tribal Members on Elders' Healthcare Access Experiences.

Elder tribal members are important cultural and spiritual leaders and experts among many American Indian and Alaska Native (AI/AN) cultures. AI/AN Elders play a key role in the maintenance and transmission of traditional cultural knowledge and practices and are highly valued members of AI/AN communities. AI/AN populations face disparities in healthcare outcomes, and the healthcare needs of AI/AN Elders remain an understudied area of research, particularly among tribes in the South and for tribes who do not have federal recognition. Qualitative data was collected through semi-structured interviews among 31 women, all of whom are members of a state-recognized Tribe in the Southern United States. While the interview questions were specific to their own reproductive healthcare experiences, repeated concerns were voiced by the women regarding the health of the Elders in their community. Key findings captured several concerns/barriers regarding Elders' healthcare experiences including: (a) Language and communication barriers between Elders and healthcare workers; (b) Prior negative experiences with Western medicine; (c) Lasting impacts of educational discrimination; (d) Concerns over self-invalidation; (e) Transportation barriers; and (f) Need for community programs. Issues related to these barriers have resulted in a concern that Elders are not receiving the full benefit of and access to Western healthcare systems. The purpose of this analysis was to highlight the concerns voiced by women tribal members on the health and wellbeing of Elders in their community. Opportunities related to the importance of prioritizing and improving AI/AN Elders' healthcare experiences and access are also described.

Promoting Clinical Trial Diversity: A Highlight of Select US FDA Initiatives.

Although the population in the United States is diverse, there are disparities in healthcare outcomes in some populations, for example, based on characteristics such as race, ethnicity, sex, gender, age, socioeconomic status, and geographic location. Despite disproportionate healthcare outcomes, certain populations are frequently under-represented in clinical trials intended to support applications requesting US Food and Drug Administration (FDA) approval to market a drug or biologic. Additionally, safety and efficacy of therapeutic products may vary based on intrinsic (e.g., sex, age, race, and ethnicity) and/or extrinsic (e.g., drug interactions and medical practice) factors. Enrolling diverse populations in clinical trials can aid in addressing disparities and better inform the use of medical products in all patients who will use them upon approval. Herein, we outline a few initiatives and activities, such as policy development, regulatory review, regulatory research, and stakeholder engagement, that the FDA has undertaken to promote diversity in clinical trials, to support submission of such information in marketing applications for subgroup analyses, and to communicate information to the public.

Abstract 12969: Impact of Race and Ethnicity on Hospital Morbidity and Resource Utilization in Acute Care Pediatric Cardiology Patients

Introduction: Disparities in healthcare outcomes are well described among patients of different races and ethnicities including pediatric cardiology. Multicenter studies examining these outcomes are lacking in pediatric acute care cardiology. We hypothesize that Black and Hispanic patients admitted to pediatric acute care cardiology units have increased hospital and acute care encounter length of stay (LOS) and complication rates compared to their White and non-Hispanic peers. Methods: Utilizing the Pediatric Acute Care Cardiology Collaborative registry, we examined all acute care cardiology unit encounters from 2/1/2019 to 7/30/2021 ending in discharge to home or death. Hospitalizations were categorized by race and ethnicity. In-hospital complications included health-care acquired infections, iatrogenic incidents, pneumonia, sepsis, seizures and stroke. Data were analyzed for differences in LOS and complication rates using chi-square and ANOVA testing. We used Bonferroni correction to establish a significance threshold of 0.007. Results: Analysis included 30,404 hospitalizations from 29 centers. There were 16,233 White (70%), 4,533 Black (19%), 919 Asian (4%) and 1,629 other races (7%) encounters. There were 23,592 (78%) non-Hispanic and 4,583 (15%) Hispanic encounters. Black patients had higher rates of premature birth (21.4%) and low birth weight (10.7%), compared to White patients (15.6% and 5.9% respectively, p&lt;0.0001). Both non-Hispanic Black and Hispanic patients had longer total hospital and acute care LOS than non-Hispanic White patients. Complication rates analyzed by race trended towards significance between Black and White patients, and Hispanic patients had a higher complication rate than non-Hispanics. ( Table 1 ) Conclusions: Despite improved outcomes for patients with congenital and acquired heart disease, significant racial and ethnic disparities continue to exist. Directed efforts are needed to achieve equitable results.

Innovation in recruitment and curricular design for diversity, equity, and inclusion (DEI) education for hematology-oncology (HO) trainees.

179 Background: Alongside persistent disparities in healthcare outcomes in HO, there is an inability to adequately recruit, maintain and promote a diverse and inclusive work force nationwide. To our knowledge, a structured approach to DEI education/recruitment in HO training is lacking. We sought to establish a longitudinal curriculum aimed at educating HO trainees in structural barriers impacting cancer equity and developing tools to enhance Underrepresented in Medicine (URiM) recruitment. Methods: Trainee-led DEI framework was presented to program leadership and officially adopted into the curriculum for the 2021-22 academic year. This consisted of initiatives across 4 domains: 1. Curricular Development (emphasis on disparities during trainee orientation, didactic lectures on cancer disparities, financial toxicity, workforce diversity, pandemic impact on cancer inequities) ; 2. Recruitment &amp; Retention (implicit bias training, targeted recruitment from HBCUs, trainee-led discussions on enhancing recruitment); 3. Engagement &amp; Mentorship (local community mentorship within institution, external mentorship through ASCO URM MSR program); 4. Disparities Research (career guidance sessions with invited faculty, development of registry-based studies to evaluate disparities). Impact of new curriculum was measured through anonymous surveys, at 1, 7, and 12 months during the academic year. A 5-point Likert scale (strongly disagree to strongly agree) was utilized. Results: At baseline, surveyed trainees were predominantly PGY5 (33%), ages 31-40 (66%), and self-identified as White or Caucasian (47%). Over the academic year, trainee recognition of structural barriers that prevented oncologic care delivery increased. More trainees felt departmental/fellowship-wide DEI efforts were transparent and impactful leading to quantifiable changes, and creation of new mentorship opportunities. Trainees rated the following as most helpful to address biases in the workplace: opportunities to mentor minority high school/college-level students, implicit bias training, and formal lectures. Anonymous qualitative feedback from fellows favored small group discussions and encouraged a top-down approach to promoting diversity in leadership. One trainee-mentored URiM medical student presented work at the ASCO annual conference on cancer disparities, while program leadership efforts led to incoming trainee class comprised of 25% URiM. Conclusions: We demonstrate feasibility of a longitudinal DEI curriculum in HO trainee education and recruitment that raises awareness and creates opportunity for URiM. Future efforts will build on this curriculum utilizing trainee feedback and departmental buy-in with the goal of building an oncologic workforce that better reflects the patients we care for.