Health Disparities: Impact of Health Disparities and Treatment Decision-Making Biases on Cancer Adverse Effects Among Black Cancer Survivors

The Genitourinary Medical Oncology Workforce in the United States

OBJECTIVE

To characterize the genitourinary medical oncology workforce in the United States.

METHODS

Utilizing the top cancer hospitals as ranked by US News & World Reports, genitourinary medical oncologists in each state of the United States were identified. Data including gender, race/ethnicity, site of medical education, and site of clinical practice were collected.

RESULTS

A total of 451 genitourinary medical oncologists are involved in clinical care in the United States. Of these medical oncologists, 399 (88.5%) practice in academic settings while 52 (11.5%) practice in community-based settings. 327 (72.5%) of genitourinary medical oncologists are male, while 124 (27.5%) are female. 17 (3.8%) genitourinary medical oncologists are from under-represented minority groups in medicine (Black, Hispanic, or Native American). 321 (71.2%) genitourinary medical oncologists received training at medical schools in the US, while 130 (28.8%) trained at medical schools abroad. The Northeast US has the most genitourinary medical oncologists with 150, followed by the South with 129, the West with 97, and the Midwest with 75. Of note, seven states, including Alaska, Delaware, Idaho, Maine, North Dakota, South Dakota, and Wyoming, have no identified genitourinary medical oncologist.

CONCLUSION

Disparities based off gender, race/ethnicity, and geographic location of practice exist in the genitourinary medical oncology workforce in the United States.

Association Between Social Determinants of Health and Cancer Treatment Delay in an Urban Population

PURPOSE

Delays in oncologic time to treatment initiation (TTI) independently and adversely affect disease-specific mortality. Social Determinants of Health (SDoH) are increasingly recognized as significant contributors to patients' disease management and health outcomes. Our academic center has validated a 10-item SDoH screener, and we elucidated which specific needs may be predictive of delayed TTI.

METHODS

This is a retrospective cohort study at an urban academic center of patients with a SDoH screening and diagnosis of breast, colorectal, endocrine/neuroendocrine, GI, genitourinary, gynecologic, head and neck, hematologic, hepatobiliary, lung, or pancreatic cancer from 2018 to 2022. Variables of interest included household income, tumor stage, and emergency department (ED) or inpatient admission 30 days before diagnosis. Factors associated with delayed TTI ≥45 days were assessed using multivariable logistic regression.

RESULTS

Among 2,328 patients (mean [standard deviation] age, 64.0 (12.8) years; 66.6% female), having >1 unmet social need was associated with delayed TTI (odds ratio [OR], 1.68; 95% CI, 1.54 to 1.82). The disparities most associated with delay were legal help, transportation, housing stability, and needing to provide care for others. Those with ED (OR, 0.49; 95% CI, 0.44 to 0.54) or inpatient (OR, 0.54; 95% CI, 0.50 to 0.58) admission 30 days before diagnosis were less likely to experience delay.

CONCLUSION

Delays in oncologic TTI ≥45 days are independently associated with unmet social needs. ED or inpatient admissions before diagnosis increase care coordination, leading to improved TTI. Although limitations included the retrospective nature of the study and self-reporting bias, these findings more precisely identify targets for intervention that may more effectively decrease delay. Patients with SDoH barriers are at higher risk of treatment delay and could especially benefit from legal, transportation, caregiver, and housing assistance.

Social Determinants of Health and Limitation of Life-Sustaining Therapy in Neurocritical Care: A CHoRUS Pilot Project

BACKGROUND

Social determinants of health (SDOH) have been linked to neurocritical care outcomes. We sought to examine the extent to which SDOH explain differences in decisions regarding life-sustaining therapy, a key outcome determinant. We specifically investigated the association of a patient's home geography, individual-level SDOH, and neighborhood-level SDOH with subsequent early limitation of life-sustaining therapy (eLLST) and early withdrawal of life-sustaining therapy (eWLST), adjusting for admission severity.

METHODS

We developed unique methods within the Bridge to Artificial Intelligence for Clinical Care (Bridge2AI for Clinical Care) Collaborative Hospital Repository Uniting Standards for Equitable Artificial Intelligence (CHoRUS) program to extract individual-level SDOH from electronic health records and neighborhood-level SDOH from privacy-preserving geomapping. We piloted these methods to a 7 years retrospective cohort of consecutive neuroscience intensive care unit admissions (2016-2022) at two large academic medical centers within an eastern Massachusetts health care system, examining associations between home census tract and subsequent occurrence of eLLST and eWLST. We matched contextual neighborhood-level SDOH information to each census tract using public data sets, quantifying Social Vulnerability Index overall scores and subscores. We examined the association of individual-level SDOH and neighborhood-level SDOH with subsequent eLLST and eWLST through geographic, logistic, and machine learning models, adjusting for admission severity using admission Glasgow Coma Scale scores and disorders of consciousness grades.

RESULTS

Among 20,660 neuroscience intensive care unit admissions (18,780 unique patients), eLLST and eWLST varied geographically and were independently associated with individual-level SDOH and neighborhood-level SDOH across diagnoses. Individual-level SDOH factors (age, marital status, and race) were strongly associated with eLLST, predicting eLLST more strongly than admission severity. Individual-level SDOH were more strongly predictive of eLLST than neighborhood-level SDOH.

CONCLUSIONS

Across diagnoses, eLLST varied by home geography and was predicted by individual-level SDOH and neighborhood-level SDOH more so than by admission severity. Structured shared decision-making tools may therefore represent tools for health equity. Additionally, these findings provide a major warning: prognostic and artificial intelligence models seeking to predict outcomes such as mortality or emergence from disorders of consciousness may be encoded with self-fulfilling biases of geography and demographics.

Health Literacy, Individual and Community Engagement, and Cardiovascular Risks and Disparities: JACC: CardioOncology State-of-the-Art Review

Cardiovascular and cancer outcomes intersect within the realm of cardio-oncology survivorship care, marked by disparities across ethnic, racial, social, and geographical landscapes. Although the clinical community is increasingly aware of this complex issue, effective solutions are trailing. To attain substantial public health impact, examinations of cancer types and cardiovascular risk mitigation require complementary approaches that elicit the patient's perspective, scale it to a population level, and focus on actionable population health interventions. Adopting such a multidisciplinary approach will deepen our understanding of patient awareness, motivation, health literacy, and community resources for addressing the unique challenges of cardio-oncology. Geospatial analysis aids in identifying key communities in need within both granular and broader contexts. In this review, we delineate a pathway that navigates barriers from individual to community levels. Data gleaned from these perspectives are critical in informing interventions that empower individuals within diverse communities and improve cardio-oncology survivorship.

Smartphone-Based Virtual and Augmented Reality Implicit Association Training (VARIAT) for Reducing Implicit Biases Toward Patients Among Health Care Providers: App Development and Pilot Testing

Background

Implicit bias is as prevalent among health care professionals as among the wider population and is significantly associated with lower health care quality.

Objective

The study goal was to develop and evaluate the preliminary efficacy of an innovative mobile app, VARIAT (Virtual and Augmented Reality Implicit Association Training), to reduce implicit biases among Medicaid providers.

Methods

An interdisciplinary team developed 2 interactive case-based training modules for Medicaid providers focused on implicit bias related to race and socioeconomic status (SES) and sexual orientation and gender identity (SOGI), respectively. The simulations combine experiential learning, facilitated debriefing, and game-based educational strategies. Medicaid providers (n=18) participated in this pilot study. Outcomes were measured on 3 domains: training reactions, affective knowledge, and skill-based knowledge related to implicit biases in race/SES or SOGI.

Results

Participants reported high relevance of training to their job for both the race/SES module (mean score 4.75, SD 0.45) and SOGI module (mean score 4.67, SD 0.50). Significant improvement in skill-based knowledge for minimizing health disparities for lesbian, gay, bisexual, transgender, and queer patients was found after training (Cohen d=0.72; 95% CI -1.38 to -0.04).

Conclusions

This study developed an innovative smartphone-based implicit bias training program for Medicaid providers and conducted a pilot evaluation on the user experience and preliminary efficacy. Preliminary evidence showed positive satisfaction and preliminary efficacy of the intervention.

Evaluation of Inequities in Cancer Treatment Delay or Discontinuation Following SARS-CoV-2 Infection

IMPORTANCE

There is a disproportionately greater burden of COVID-19 among Hispanic and non-Hispanic Black individuals, who also experience poorer cancer outcomes. Understanding individual-level and area-level factors contributing to inequities at the intersection of COVID-19 and cancer is critical.

OBJECTIVE

To evaluate associations of individual-level and area-level social determinants of health (SDOH) with delayed or discontinued cancer treatment following SARS-CoV-2 infection.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective, registry-based cohort study used data from 4768 patients receiving cancer care who had positive test results for SARS-CoV-2 and were enrolled in the American Society for Clinical Oncology COVID-19 Registry. Data were collected from April 1, 2020, to September 26, 2022.

EXPOSURES

Race and ethnicity, sex, age, and area-level SDOH based on zip codes of residence at the time of cancer diagnosis.

MAIN OUTCOMES AND MEASURES

Delayed (≥14 days) or discontinued cancer treatment (any cancer treatment, surgery, pharmacotherapy, or radiotherapy) and time (in days) to restart pharmacotherapy.

RESULTS

A total of 4768 patients (2756 women [57.8%]; 1558 [32.7%] aged ≥70 years at diagnosis) were included in the analysis. There were 630 Hispanic (13.2%), 196 non-Hispanic Asian American or Pacific Islander (4.1%), 568 non-Hispanic Black (11.9%), and 3173 non-Hispanic White individuals (66.5%). Compared with non-Hispanic White individuals, Hispanic and non-Hispanic Black individuals were more likely to experience a delay of at least 14 days or discontinuation of any treatment and drug-based treatment; only estimates for non-Hispanic Black individuals were statistically significant, with correction for multiple comparisons (risk ratios [RRs], 1.35 [95% CI, 1.22-1.49] and 1.37 [95% CI, 1.23-1.52], respectively). Area-level SDOH (eg, geography, proportion of residents without health insurance or with only a high school education, lower median household income) were associated with delayed or discontinued treatment. In multivariable Cox proportinal hazards regression models, estimates suggested that Hispanic (hazard ratio [HR], 0.87 [95% CI, 0.71-1.05]), non-Hispanic Asian American or Pacific Islander (HR, 0.79 [95% CI, 0.46-1.35]), and non-Hispanic Black individuals (HR, 0.81 [95% CI, 0.67-0.97]) experienced longer delays to restarting pharmacotherapy compared with non-Hispanic White individuals.

CONCLUSIONS AND RELEVANCE

The findings of this cohort study suggest that race and ethnicity and area-level SDOH were associated with delayed or discontinued cancer treatment and longer delays to the restart of drug-based therapies following SARS-CoV-2 infection. Such treatment delays could exacerbate persistent cancer survival inequities in the United States.

Antiracist symptom science: A call to action and path forward

Nurse scientists recognize the experience of racism as a driving force behind health. However, symptom science, a pillar of nursing, has rarely considered contributions of racism. Our objective is to describe findings within symptom science research related to racial disparities and/or experiences of racism and to promote antiracist symptom science within nursing research. In this manuscript, we use an antiracist lens to review a predominant symptom science theory and literature in three areas of symptom science research-oncology, mental health, and perinatal health. Finally, we make recommendations for increasing antiracist research in symptom science by altering (a) research questions, (b) recruitment methods, (c) study design, (d) data analysis, and (e) dissemination of findings. Traditionally, symptom science focuses on individual level factors rather than broader contexts driving symptom experience and management. We urge symptom science researchers to embrace antiracism by designing research with the specific intent of dismantling racism at multiple levels.

Equity in Health Care

The Oncology Nursing Society (ONS) has made marked contributions to the art and science of nursing, including establishment of resources and a community for oncology nurses across the United States. ONS's core values have evolved to innovation, excellence, advocacy, and inclusivity (ONS, 2021). While we know that these core values are, in virtue, admirable, there is a stark need to address another value-equity.