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. This article proposes a framework for nurses which includes AI principles, skills, competencies, and curriculum development focused on the practical use of AI, with an emphasis on care that aims to achieve health equity. By adopting this educational framework, nurses will be prepared to make substantial contributions to reducing health disparities and fostering a health-care system that is more efficient and equitable.

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. RESULTS: An Implementation Guide articulates evaluation criteria used during review of algorithmic technologies and details what evidence supports the implementation of ethical and quality principles for trustworthy health AI. Application of the processes described in the Implementation Guide can lead to algorithms that are safer as well as more effective, fair, and equitable upon implementation, as illustrated through 4 examples of technologies at different phases of the algorithmic lifecycle that underwent evaluation at our academic medical center. DISCUSSION: By providing clear descriptions/definitions of evaluation criteria and embedding them within standardized processes, we streamlined oversight processes and educated communities using and developing algorithmic technologies within our institution. CONCLUSIONS: We developed a scalable, adaptable framework for translating principles into evaluation criteria and specific requirements that support trustworthy implementation of algorithmic technologies in patient care and healthcare operations.

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. Our scoping review encompassed 109 articles comprising 45 empirical health care applications that included tools tested in health care settings, 16 frameworks, and 48 reviews and perspectives. We identified a wide range of technical, operational, and systemwide bias mitigation strategies for clinical algorithms, but there was no consensus in the literature on a single best practice that covered entities could employ to meet the HHS requirements. Future research should identify optimal bias mitigation methods for various scenarios, depending on factors such as patient population, clinical setting, algorithm design, and types of bias to be addressed.

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. We conducted a secondary data analysis of 2018-2022 electronic health record data for older adults aged ≥50 years, in 1 large academic health system to determine the source, magnitude, and correlates of missing sexual orientation and gender identity (SOGI) data among hospitalized older adults. Among 153 827 older adults discharged from the hospital, SOGI data missingness was 67.6% for sexual orientation and 63.0% for gender identity. SOGI data are underreported, leading to bias findings when studying health disparities. Without complete SOGI data, healthcare systems will not fully understand the unique needs of SGM individuals and develop tailored interventions and programs to reduce health disparities among these populations.

Machine Learning Algorithms to Predict Mortality and Allocate Palliative Care for Older Patients With Hip Fracture.

OBJECTIVES: To evaluate a machine learning model designed to predict mortality for Medicare beneficiaries aged >65 years treated for hip fracture in Inpatient Rehabilitation Facilities (IRFs). DESIGN: Retrospective design/cohort analysis of Centers for Medicare & Medicaid Services Inpatient Rehabilitation Facility-Patient Assessment Instrument data. SETTING AND PARTICIPANTS: A total of 17,140 persons admitted to Medicare-certified IRFs in 2015 following hospitalization for hip fracture. MEASURES: Patient characteristics include sociodemographic (age, gender, race, and social support) and clinical factors (functional status at admission, chronic conditions) and IRF length of stay. Outcomes were 30-day and 1-year all-cause mortality. We trained and evaluated 2 classification models, logistic regression and a multilayer perceptron (MLP), to predict the probability of 30-day and 1-year mortality and evaluated the calibration, discrimination, and precision of the models. RESULTS: For 30-day mortality, MLP performed well [acc = 0.74, area under the receiver operating characteristic curve (AUROC) = 0.76, avg prec = 0.10, slope = 1.14] as did logistic regression (acc = 0.78, AUROC = 0.76, avg prec = 0.09, slope = 1.20). For 1-year mortality, the performances were similar for both MLP (acc = 0.68, AUROC = 0.75, avg prec = 0.32, slope = 0.96) and logistic regression (acc = 0.68, AUROC = 0.75, avg prec = 0.32, slope = 0.95). CONCLUSION AND IMPLICATIONS: A scoring system based on logistic regression may be more feasible to run in current electronic medical records. But MLP models may reduce cognitive burden and increase ability to calibrate to local data, yielding clinical specificity in mortality prediction so that palliative care resources may be allocated more effectively.

Hospital Readmission and Costs of Total Knee Replacement Surgery in 2009 and 2014: Potential Implications for Health Care Managers.

The purpose of this article is to describe changes in hospital readmissions and costs for US hospital patients who underwent total knee replacement (TKR) in 2009 and 2014. Data came from the Healthcare Cost and Utilization Project net-Nationwide Readmissions Database. Compared with 2009, overall 30-day rates of readmissions after TKR decreased by 15% in 2014. Rates varied by demographics: readmission rates were lower for younger patients, males, Medicare recipients, and those with higher incomes. Overall, costs rose 20% across TKR groups. This report is among the first to describe changes in hospital readmissions and costs for TKR patients in a national sample of US acute care hospitals. Findings offer hospital managers a mechanism to benchmark their facilities' performances.

Hospital Readmission in Total Hip Replacement Patients in 2009 and 2014.

OBJECTIVE: To document changes in 30-day hospital readmission rates and causes for returning to the hospital for care in THR patients. DESIGN: Retrospective cross-sectional descriptive design. SETTING: Community-based acute care hospitals. PARTICIPANTS: Total sample size (N=142,022) included THR patients (identified as ICD-9-CM procedure code 81.51) in 2009 (n=31,232) and (n=32,863) in 2014. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: 30-Day hospital readmission. RESULTS: The overall readmission rate decreased by 1.3% from 2009 to 2014. The decrease in readmission rates varied by groups, with lesser improvements seen in THR patients who were younger, with private insurance, and residing in lower-income and rural communities. Device complications were the leading cause of readmission in THR patients, increasing from 19.8% in 2009 to 23.9% in 2014. CONCLUSIONS: There has been little decrease in hospital 30-day readmission rates for US community hospitals between 2009 and 2014. Findings from this brief report indicate patient groups at greater risk for 30-day hospital readmission as well as leading causes for readmission in THR patients which can inform the development of tailored interventions for reduction.

Successful Community Discharge Following Postacute Rehabilitation for Medicare Beneficiaries: Analysis of a Patient-Centered Quality Measure.

OBJECTIVE: To determine the sociodemographic and clinical characteristics as well as health services use associated with successful community discharge. DATA SOURCE: Inpatient Rehabilitation Facility-Patient Assessment Instrument and Medicare Provider Analysis and Review files. STUDY DESIGN: We retrospectively examined 167,664 Medicare beneficiaries discharged from inpatient rehabilitation facilities (IRFs) in 2013 to determine the sociodemographic and clinical characteristics as well as health services use associated with successful community discharge. PRINCIPAL FINDINGS: In the multivariable model, sociodemographic (younger age, no disability, social support), clinical (higher motor and cognitive functional status at admission), and health services use (fewer acute care days and longer IRF days) variables were associated with successful community discharge. CONCLUSIONS: Remaining in the community is an important patient-centered outcome that could complement other postacute rehabilitation quality measures.

Student-Developed Simulations: Enhancing Cultural Awareness and Understanding Social Determinants of Health.

BACKGROUND: National and global initiatives to address the social determinants of health (SDH) are on the rise. On a parallel trajectory, increased cultural awareness is emerging as an integral strategy to improve the understanding of these social contributions to disease states, health inequities, and health disparities. METHOD: Undergraduate nursing students developed modalities and role-played simulations as a teaching and learning strategy. The simulations demonstrated how nurses assess patients' unique needs and offer support and resources regarding patients' socioeconomic, cultural, and environmental needs. RESULTS: The student-developed simulations were an interactive teaching and learning strategy that offered several benefits, such as improved interpersonal skills, learned specific nursing roles, and improved cultural awareness. CONCLUSION: Student-developed simulations are an innovative teaching strategy for improving cultural awareness and learning more about SDH. [J Nurs Educ. 2017;56(4):243-246.].

Self-Care and Mobility Following Postacute Rehabilitation for Older Adults With Hip Fracture: A Multilevel Analysis.

OBJECTIVE: To examine contextual (facility and community) and individual factors associated with self-care and mobility outcomes among Medicare hip fracture patients receiving inpatient rehabilitation. DESIGN: Retrospective cohort study of 3 linked data files: Inpatient Rehabilitation Facility-Patient Assessment Instrument, Provider of Services, and Area Health Resources. Multilevel modeling was used to examine the effects of contextual and individual factors on self-care and mobility outcomes. SETTING: Inpatient rehabilitation facilities (IRFs). PARTICIPANTS: Medicare hip fracture patients (N=35,264; mean age, 81y) treated in IRFs (N=1072) in 2012. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Self-care (eating, grooming, bathing, upper and lower body dressing, toileting) and mobility (walk/wheelchair, stairs) at discharge. RESULTS: Mean ± SD self-care and mobility scores at admission were 3.17±.87 and 1.24±.51, respectively; mean ± SD self-care and mobility scores at discharge were 5.03±1.09 and 3.31±1.54, respectively. Individual and contextual levels explained 44.4% and 21.6% of the variance in self-care at discharge, respectively, and 19.5% and 1.9% of the variance in mobility at discharge, respectively. At the individual level, age, race/ethnicity, cognitive and motor FIM scores at admission, and tier comorbidities explained variance in self-care and mobility; sex and length of stay explained variance only in self-care. At the contextual level, facilities' case mix (mean patient age, percent non-Hispanic white, mean self-care score at admission) and structural characteristics (rural location, freestanding, for-profit ownership) explained variance only in self-care; facilities' case mix (mean patient age, percent non-Hispanic white, percent living with social support, mean mobility score at admission) explained variance in mobility. Community variables were nonsignificant. CONCLUSIONS: Individual and facility factors were significant predictors of discharge self-care and mobility among Medicare hip fracture patients in IRFs. The findings may improve quality of IRF services to hip fracture patients and inform risk adjustment methods.

Inpatient Rehabilitation Outcomes in a National Sample of Medicare Beneficiaries With Hip Fracture.

Effects of patient characteristics on rehabilitation outcomes (functional status at discharge, discharged home) were assessed in a retrospective study of Medicare beneficiaries admitted to Medicare-certified inpatient rehabilitation facilities (IRFs) following hospitalization for hip fracture in 2009 (N = 34,984). Hierarchical regression analysis showed significantly higher functional status at discharge (p < .0001) for patients with these characteristics: White or Asian, younger, female, lived alone, higher functional status at admission, fewer comorbidities, no tier comorbidities, and longer IRF length of stay (LOS). Likelihood of discharged home was higher for patients with these characteristics: Hispanic (1.49 [1.32, 1.68]), Asian (1.35 [1.04, 1.74]), or Black (1.28 [1.12, 1.47]); younger (0.96 [0.96, 0.96]); female (1.14 [1.08, 1.20]); lived with others (2.12 [2.01, 2.23]); higher functional status at admission (1.06 [1.06, 1.06]); fewer comorbidities, no tier comorbidities; and longer LOS (1.61 [1.56, 1.67]). Functional status at admission, tier comorbidities, and race/ethnicity contributed the most to variance in functional status at discharge. Living with others contributed the most to variance in discharged home.

Changes in Payment Regulation and Acute Care Use for Total Hip Replacement: Trends in Length of Stay, Costs, and Discharge, 1997-2012.

PURPOSE: To describe trends in the length of stay (LOS), costs, mortality, and discharge destination among a national sample of total hip replacement (THR) patients between 1997 and 2012. DESIGN: Longitudinal retrospective design METHODS: Descriptive analysis of the Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample data. FINDINGS: A total of 3,516,636 procedures were performed over the study period. Most THR patients were women, and the proportion aged 44-65 years increased. LOS decreased from 5 to 3 days. Charges more than doubled, from $22,184 to $53,901. Deaths decreased from 43 to 12 deaths per 10,000 patients. THR patients discharged to an institutional setting declined, while those discharged to the community increased. CONCLUSION: We found an increase in THR patients, who were younger, women, had private insurance, and among those discharged to community-based settings. CLINICAL RELEVANCE: Findings have implications for patient profiles, workplace environments, quality improvement, and educational preparation of nurses in acute and postacute settings.

Performance-based outcomes of inpatient rehabilitation facilities treating hip fracture patients in the United States.

OBJECTIVE: To examine the influence of facility and aggregate patient characteristics of inpatient rehabilitation facilities (IRFs) on performance-based rehabilitation outcomes in a national sample of IRFs treating Medicare beneficiaries with hip fracture. DESIGN: Secondary data analysis. SETTING: U.S. Medicare-certified IRFs (N=983). PARTICIPANTS: Data included patient records of Medicare beneficiaries (N=34,364) admitted in 2009 for rehabilitation after hip fracture. INTERVENTION: Not applicable. MAIN OUTCOME MEASURES: Performance-based outcomes included mean motor function on discharge, mean motor change (mean motor score on discharge minus mean motor score on admission), and percentage discharged to the community. RESULTS: Higher mean motor function on discharge was explained by aggregate characteristics of patients with hip fracture (lower age [P=.009], lower percentage of blacks [P<.001] and Hispanics [P<.001], higher percentage of women [P=.030], higher motor function on admission [P<.001], longer length of stay [P<.001]) and facility characteristics (freestanding [P<.001], rural [P<.001], for profit [P=.048], smaller IRFs [P=.014]). The findings were similar for motor change, but motor change was also associated with lower mean cognitive function on admission (P=.008). Higher percentage discharged to the community was associated with aggregate patient characteristics (lower age [P<.001], lower percentage of Hispanics [P=.009], higher percentage of patients living with others [P<.001], higher motor function on admission [P<.001]). No facility characteristics were associated with the percentage discharged to the community. CONCLUSIONS: Performance-based measurement offers health policymakers, administrators, clinicians, and consumers a major opportunity for securing health system improvement by benchmarking or comparing their outcomes with those of other similar facilities. These results might serve as the basis for benchmarking and quality-based reimbursement to IRFs for 1 impairment group: hip fracture.