Integrating Artificial Intelligence Into Cancer Care: Enhancing Nursing Practice and Bridging Disparities.

Artificial intelligence (AI) in cancer care has the potential to transform nursing practice, reduce cancer disparities, and enhance patient outcomes across the continuum of care from prevention, screening, and treatment to su.

Building competency in artificial intelligence and bias mitigation for nurse scientists and aligned health researchers.

Healthcare systems are increasingly integrating artificial intelligence and machine learning (AI/ML) tools into patient care, potentially influencing clinical decisions for millions. However, concerns are growing about these tools reinforcing systemic inequities. To address bias in AI/ML tools and promote equitable outcomes, guidelines for mitigating this bias and comprehensive workforce training programs are necessary.

Algorithm-Based Clinical Decision Support: Evolving Regulatory Landscape and Best Practices for Local Oversight.

The potential of algorithm-based clinical decision support (CDS) in healthcare continues to increase with the growing field of artificial intelligence (AI)-enabled CDS. The use of these technologies to support clinicians, patients, and health systems is still quite new, and to date, implementors and regulators are still identifying the best processes and practices to ensure the effective, safe, and equitable use of these technology solutions. To assist individuals and organizations interested in implementation of algorithm-based CDS and AI-enabled CDS in healthcare, this article reviews the important regulatory decisions that form the landscape within which algorithm-based CDS has emerged, modern governance frameworks used to oversee these CDS systems, nuances in evaluation and monitoring throughout the CDS life cycle, best practices for real-world implementation, safety and equity considerations, and avenues for future collaboration and innovation.

Preparedness for care transitions to home and acute care use of skilled nursing facility patients.

Background: The purpose of this study was two-fold: (1) describe the relationship between patient or caregiver reported preparedness for care transitions, and acute care use in 30 days after discharge from a skilled nursing facility (SNF); and (2) explore how this relationship is influenced by patient, Charlson index, race and social determinants.

Method: The design was a secondary analysis of data collected as part of a cluster randomized trial of the Connect-Home transitional care intervention. The setting was 6 skilled nursing facilities located in the US state of North Carolina.

"ROLE" Out of the Network of Black Male Nursing Leaders Mentorship Program.

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.

State of Black men in nursing: An oral history of the challenges and the benefits of five Black male nurse leaders.

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.

A roadmap for the nursing scientific workforce to eliminate health and healthcare inequities.

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.

Empowering nurses to champion Health equity & BE FAIR: Bias elimination for fair and responsible AI in healthcare.

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.

Skilled nursing facility staffing shortages: Sources, strategies, and impacts on staff who stayed.

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.

Enhancing Clinical Decision Support in Nephrology: Addressing Algorithmic Bias Through Artificial Intelligence Governance.

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.

Efforts to Support the Mental Health and Well-being of Nursing Home Staff: Insights From Leaders.

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.

Advancing Health Equity Through Artificial Intelligence: An Educational Framework for Preparing Nurses in Clinical Practice and Research.

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.

Psychosocial stressors associated with frailty in community-dwelling older adults in the United States.

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).

A Qualitative Study of the Social Relationship Experiences Across the Life Course Among Black/African American Women Aging With HIV in the South.

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.

Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare.

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.

Mitigating Racial And Ethnic Bias And Advancing Health Equity In Clinical Algorithms: A Scoping Review.

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.

Structural determinants and cardiometabolic typologies related to frailty in community-dwelling older adults.

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.

A call to action to improve the completeness of older adult sexual and gender minority data in electronic health records.

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.

Does cumulative psychosocial stress explain frailty disparities in community-dwelling older adults?

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.

Gendered Consequences of COVID-19 Among Professional Tennis Players.

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.

Predictive Accuracy of Stroke Risk Prediction Models Across Black and White Race, Sex, and Age Groups.

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.

Hospital Utilization for Coronary Artery Disease, 1997-2014.

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.

Do heavy-duty and passenger vehicle emissions standards reduce per capita emissions of oxides of nitrogen? Evidence from Europe.

Oxides of nitrogen are among the most dangerous emissions to human health and to the environment. In European nations, road transportation contributes to approximately 40% of emissions of oxides of nitrogen with the dominant share coming from passenger and freight transport. To help mitigate emissions of oxides of nitrogen, the European Union (EU) has implemented vehicular emissions standards.

The Association Between Cardiometabolic Risk Factors and Frailty in Older Adults: A Systematic Review.

Background And Objectives: Enhanced management and prevention of frailty depend on our understanding of the association between potentially modifiable risk factors and frailty. However, the associations between potentially modifiable cardiometabolic risk factors and frailty are not clear. The purpose of this review was to appraise and synthesize the current evidence examining the associations between the cardiometabolic risk factors and frailty.

Telemedicine versus in-Person Primary Care: Impact on Visit Completion Rate in a Rural Appalachian Population.

Introduction: The use of telemedicine increased during the global Coronavirus disease 2019 (COVID-19) pandemic. Rural populations often struggle with adequate access to care while simultaneously experiencing multiple health disparities. Yet, telemedicine use during the COVID-19 pandemic has been understudied on its effect on visit completion in rural populations.