Publications by authors named "Cary M"

Despite nursing being the largest segment in all of the healthcare workforce, with over five million practicing registered nurses in the United States, Black males remain significantly underrepresented, comprising merely about 0.67% to 1% of the nursing workforce. This underrepresentation extends into leadership positions, where the number of Black male leaders in nursing is described as unquantifiable.

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The underrepresentation of Black men in nursing continues to pose a significant challenge to diversity and equity in healthcare leadership. While systemic barriers, such as implicit bias, limited access to advanced education, and lack of mentorship, have been well-documented, there is little literature that highlights the specific journeys of Black male nurse leaders and the strategies that facilitated their success. This oral history presents the narratives of five Black male nurse leaders who overcame obstacles and rose to influential positions within nursing.

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Background: The National Academies of Sciences, Engineering, and Medicine's Ending Unequal Treatment report emphasizes immediate actions to eliminate health inequities (i.e., solutions-oriented health inequity research), versus incrementally advancing health equity.

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Background: The concept of health equity by design encompasses a multifaceted approach that integrates actions aimed at eliminating biased, unjust, and correctable differences among groups of people as a fundamental element in the design of algorithms. As algorithmic tools are increasingly integrated into clinical practice at multiple levels, nurses are uniquely positioned to address challenges posed by the historical marginalization of minority groups and its intersections with the use of "big data" in healthcare settings; however, a coherent framework is needed to ensure that nurses receive appropriate training in these domains and are equipped to act effectively.

Purpose: We introduce the Bias Elimination for Fair AI in Healthcare (BE FAIR) framework, a comprehensive strategic approach that incorporates principles of health equity by design, for nurses to employ when seeking to mitigate bias and prevent discriminatory practices arising from the use of clinical algorithms in healthcare.

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Objective: To examine skilled nursing facility (SNF) staffing shortages across job roles during the COVID-19 pandemic. We aimed to capture the perspectives of leaders on the breadth of staffing shortages and their implications on staff that stayed throughout the pandemic in order to provide recommendations for policies and practices used to strengthen the SNF workforce moving forward.

Study Setting And Design: For this qualitative study, we engaged a purposive national sample of SNF leaders (n = 94) in one-on-one interviews between January 2021 and December 2022.

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There has been a steady rise in the use of clinical decision support (CDS) tools to guide nephrology as well as general clinical care. Through guidance set by federal agencies and concerns raised by clinical investigators, there has been an equal rise in understanding whether such tools exhibit algorithmic bias leading to unfairness. This has spurred the more fundamental question of whether sensitive variables such as race should be included in CDS tools.

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Objectives: The sustained stress and trauma experienced by frontline nursing home (NH) staff throughout the COVID-19 pandemic has been described in health care literature and popular press. Yet, limited attention has been given to attempts to support NH staff. The objective of this study was to examine efforts to support the mental health and well-being of NH staff during the COVID-19 pandemic.

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The integration of artificial intelligence (AI) into health care offers the potential to enhance patient care, improve diagnostic precision, and broaden access to health-care services. Nurses, positioned at the forefront of patient care, play a pivotal role in utilizing AI to foster a more efficient and equitable health-care system. However, to fulfil this role, nurses will require education that prepares them with the necessary skills and knowledge for the effective and ethical application of AI.

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Background: Frailty is multifactorial; however, psychosocial stressors contributing to frailty are poorly understood. This study aimed to examine whether gender, race/ ethnicity, and education are associated with differential exposure to psychosocial stressors, determine psychosocial stressors contributing to frailty, and explore the mediating psychosocial stressors pathway.

Methods: This cross-sectional study involved 7679 community-dwelling older adults (≥65) from the Health and Retirement Study (2006 and 2008 waves).

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Black/African American women continue to be disproportionately affected by HIV, facing multiple intersecting challenges that influence how they age and effectively manage their health. Supportive social relationships have been shown to help mitigate challenges and improve health in women with HIV, but little is known about Black/African American women's perceptions of social relationships. Guided by Life Course Theory, in-depth life history interviews were conducted with 18 Black/African American women aged 50+ years.

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Objective: The complexity and rapid pace of development of algorithmic technologies pose challenges for their regulation and oversight in healthcare settings. We sought to improve our institution's approach to evaluation and governance of algorithmic technologies used in clinical care and operations by creating an Implementation Guide that standardizes evaluation criteria so that local oversight is performed in an objective fashion.

Materials And Methods: Building on a framework that applies key ethical and quality principles (clinical value and safety, fairness and equity, usability and adoption, transparency and accountability, and regulatory compliance), we created concrete guidelines for evaluating algorithmic technologies at our institution.

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In August 2022 the Department of Health and Human Services (HHS) issued a notice of proposed rulemaking prohibiting covered entities, which include health care providers and health plans, from discriminating against individuals when using clinical algorithms in decision making. However, HHS did not provide specific guidelines on how covered entities should prevent discrimination. We conducted a scoping review of literature published during the period 2011-22 to identify health care applications, frameworks, reviews and perspectives, and assessment tools that identify and mitigate bias in clinical algorithms, with a specific focus on racial and ethnic bias.

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People experiencing homelessness (PEH) are at disproportionate risk of becoming infected and having severe illness from coronavirus disease 2019 (COVID-19), especially when residing in congregate settings like homeless shelters. Behavioral health problems related to substance use disorder (SUD) and severe mental illness (SMI) may have created additional challenges for PEH to practice prevention measures like mask wearing, physical distancing, handwashing, and quarantine and isolation. The study objective was to understand the perceived barriers PEH face regarding COVID-19 non-pharmaceutical prevention strategies and identify recommendations for overcoming barriers.

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Introduction: The importance of including people affected by research (e.g., community members, citizens or patient partners) is increasingly recognized across the breadth of institutions involved in connecting research with action.

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Frailty is a geriatric syndrome linked to adverse outcomes. Co-occurring cardiometabolic factors increase frailty risk; however, their distinct combinations (typologies) associated with frailty are unclear. We aimed to identify subgroups of older adults with distinct cardiometabolic typologies and characterize their relationship with structural determinants and frailty to inform tailored approaches to prevent and delay frailty.

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There is evidence of the efficacy of collaborative health interventions with pharmacies and primary care providers but little of its real-world effectiveness. We aimed to assess the effectiveness and discuss the design and challenges of hypertension and hyperlipidemia management between pharmacies and primary care providers using real-world data exchange between providers and experimental bundled payment. This was a pragmatic, quasi-experimental controlled trial.

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Sexual and gender minority (SGM) older adults experience greater health disparities compared to non-SGM older adults. The SGM older adult population is growing rapidly. To address this disparity and gain a better understanding of their unique challenges in healthcare relies on accurate data collection.

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Objective: Frailty is a leading predictor of adverse outcomes in older adults. Although disparities in frailty are well-documented, it is unclear whether psychosocial stressors explain these disparities. This study aimed to examine the potential mediating role of psychosocial stress.

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Aim: To evaluate the impact of a collaborative screening campaign on the prevalence of pre-diabetes and diabetes among the screened population.

Methods: A Longitudinal, multicentre study was developed. The Finnish Diabetes Risk Score (FINDRISC) was applied to the eligible population in the participating community pharmacies.

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The COVID-19 pandemic increased the risk of travelling, working, and participating in public events. To test whether there were gendered differences in the response to COVID-19, we examine the behavior of male and female professional tennis players. We use data from major tennis tournaments which included a rather large number of athletes withdrawing from play.

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Importance: Stroke is the fifth-highest cause of death in the US and a leading cause of serious long-term disability with particularly high risk in Black individuals. Quality risk prediction algorithms, free of bias, are key for comprehensive prevention strategies.

Objective: To compare the performance of stroke-specific algorithms with pooled cohort equations developed for atherosclerotic cardiovascular disease for the prediction of new-onset stroke across different subgroups (race, sex, and age) and to determine the added value of novel machine learning techniques.

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Background: Coronary artery disease (CAD) is the leading cause of cardiovascular morbidity, mortality, and healthcare costs in the United States. There are few reports on how public health and payment reforms might have influenced inpatient hospital use among patients with CAD.

Objective: This study describes trends in hospital discharges, hospital charges, and discharge destinations in a national sample of patients with CAD between 1997 and 2014.

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The United States is experiencing a syndemic of homelessness, substance use disorder, and mental health conditions, which has been further exacerbated by the COVID-19 pandemic. Although it is expected that mitigation strategies will curb community transmission of COVID-19, the unintended consequences of social isolation on mental health and substance use are a growing public health concern. Awareness of changing mental health and substance use treatment needs due to the pandemic is critical to understanding what additional services and support are needed during and post-pandemic, particularly among people experiencing homelessness who have pre-existing serious mental illness or substance use disorder.

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Child and adolescent psychiatrists (CAPs) work at the intersections of families, cultures, and systems, which affect engagement in care, assessment, and treatment planning. There are several practical strategies that CAPs can apply to practice cultural humility, to join with families, to facilitate difficult conversations and to work through misalignment. Culturally inclusive family-based care can promote greater understanding and lead to stronger outcomes with families as well as help mitigate mental health impact of structural racism and social inequities.

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