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. DESIGN: Qualitative, multiple-case-study design that purposively sampled NHs from 3 groups based on the Centers for Medicare & Medicaid Services NH 5-star quality performance ratings [ie, high (4-5-star), medium (3-star), and low (1-2-star)]. SETTINGS AND PARTICIPANTS: Ninety-four US NH leaders participated in semistructured interviews via phone, between January 2021 and December 2022. METHODS: A 3-step rapid qualitative analysis process was used to conduct a thematic analysis. RESULTS: Five themes emerged as NH leaders described strategies used to address the mental health and well-being of their staff, including (1) efforts to address stressors in staff's personal lives (eg, risk of COVID-19 transmission to families, finances), (2) providing mental health services (eg, counseling, Employee Assistance Program) and resources (eg, staff self-care, mindfulness), (3) appreciation initiatives to combat negative media portrayals of NHs, (4) fostering an environment that supports mental health and well-being (eg, leadership initiatives to prioritize mental health, embedding training on burnout into standing meetings), and (4) modifying staff benefits (eg, expanding mental health coverage within staff insurance plan, paid time off). CONCLUSIONS: In light of concerns about NH staffing levels and the recently proposed minimum staffing levels, there is a need to design and evaluate initiatives to recruit and retain qualified NH staff. Insights into efforts implemented by NH leaders to improve mental health and well-being can inform the design of future efforts to improve staff retention.

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. In order to properly answer this question, it is necessary to understand how algorithmic bias arises. We break down three sources of bias encountered when using electronic health record data to develop CDS tools: (1) use of proxy variables, (2) observability concerns and (3) underlying heterogeneity. We discuss how answering the question of whether to include sensitive variables like race often hinges more on qualitative considerations than on quantitative analysis, dependent on the function that the sensitive variable serves. Based on our experience with our own institution's CDS governance group, we show how health system-based governance committees play a central role in guiding these difficult and important considerations. Ultimately, our goal is to foster a community practice of model development and governance teams that emphasizes consciousness about sensitive variables and prioritizes equity.

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. DATA SOURCE AND ANALYTIC SAMPLE: Using purposive sampling (i.e., Centers for Medicare & Medicaid quality rating, region, ownership) to capture variation in SNF organizations, we conducted in-depth, semi-structured qualitative interviews, guided a priori by the Institute of Medicine's Model of Healthcare System Framework. Interviews were conducted via phone, audio-recorded, and transcribed. Rigorous rapid qualitative analysis was used to identify emergent themes, patterns, and relationships. PRINCIPAL FINDINGS: SNF leaders consistently described staffing shortages spanning all job roles, including direct care (e.g., activities, nursing, social services), support services (e.g., laundry, food, environmental services), administrative staff, and leadership. Ascribed sources of shortages were multidimensional (e.g., competing salaries, family caregiving needs, burnout). The impact of shortages was felt by all staff that stayed. In addition to existing job duties, those remaining staff experienced re-distribution of essential day-to-day operational tasks (e.g., laundry) and allocation of new COVID-19 pandemic-related activities (e.g., screening). Cross-training was used to cover a wide range of job duties, including patient care. CONCLUSIONS: Policies are needed to support SNF staff across roles beyond direct care staff. These policies must address the system-wide drivers perpetuating staffing shortages (i.e., pay differentials, burnout) and leverage strategies (i.e., cross-training, job role flexibility) that emerged from the pandemic to ensure a sustainable SNF workforce that can meet patient needs.

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.

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). Psychosocial stressors such as loneliness, low subjective social status, financial strain, poor neighborhood cohesion, everyday discrimination, and traumatic life events were measured. Frailty was defined by the Fried phenotype measure. Multivariable logistic regressions were used to examine the association of gender, race/ethnicity, and education with psychosocial stressors, psychosocial stressors associated with frailty, and the mediating psychosocial stressors pathway. RESULTS: Females experienced greater financial strain but lower discrimination (both p < 0.05). Older adults who identified as Hispanic, Black, and racially or ethnically minoritized experienced low subjective social status, high financial strain, low neighborhood cohesion, and high discrimination than their White counterparts (all p < 0.05). Those with lower education experienced high loneliness, low subjective social status, high financial strain, low neighborhood cohesion but lower traumatic life events (all p < 0.05). Psychosocial stressors: High loneliness, low subjective social status, high financial strain, and low neighborhood cohesion (all p < 0.05) independently increased the odds of frailty. The mediating pathway of psychosocial stressors was not significant.  CONCLUSION: Disparities exist in exposure to psychosocial stressors associated with frailty. Multilevel interventions are needed to reduce the influence of psychosocial stressors on frailty.

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.

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. This study was cross-sectional design and included 7984 community-dwelling older adults (65+ years) enrolled in the Health and Retirement Study (2006 and 2008). Latent class analysis was performed using seven cardiometabolic indicators (abdominal obesity, obesity, low high-density lipoprotein; and elevated blood pressure, blood sugar, total cholesterol, C-reactive protein). Frailty was indicated by ≥3 features (weakness, slowness, fatigue, low physical activity, unintentional weight loss). Logistic regression was used to examine the relationship between structural determinants (gender, race/ethnicity, and education), cardiometabolic typologies, and frailty. Three cardiometabolic subgroups were identified: insulin-resistant (n = 3547), hypertensive dyslipidemia (n = 1246), and hypertensive (n = 3191). Insulin-resistant subgroup members were more likely to be female, non-Hispanic Black, and college non-graduates; hypertensive dyslipidemia subgroup members were more likely to be non-Hispanic Others and report high school education; and hypertensive subgroup members were more likely to be male and college educated (p≤.05). Frailty risk was higher for females, Hispanic or Non-Hispanic Black older adults, and those with lower education (p≤.001). Frailty risk was greater in the insulin-resistant compared to the other subgroups (both aOR=2.0, both p<.001). Findings highlight a need to design tailored interventions targeting cardiometabolic typologies to prevent and delay frailty.

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.

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. METHODS: This cross-sectional study included 7,679 community-dwelling older adults (≥ 65) from Health and Retirement Study in the US (2006 and 2008). We used six dichotomized psychosocial stressors: a) loneliness, b) discrimination, c) financial strain, d) low subjective status, e) poor neighborhood cohesion, and f) traumatic life events to compute cumulative psychosocial stress. The Fried frailty phenotype defined frailty based on three features: slowness, poor strength, weight loss, fatigue, and low physical activity. Multivariable regressions were used to examine the structural determinants (gender, education, race, and ethnicity) frailty relationship and test whether cumulative psychosocial stress has a mediating role. RESULTS: The frailty prevalence was 22%. Females, Hispanics, Blacks, and those with less education had higher odds of frailty (p<.01). Race and ethnic minorities and non-college graduates experienced greater cumulative psychosocial stress relative to their White and college graduate counterparts (p<.05), respectively. Greater cumulative psychosocial stress was associated with increased odds of frailty (p < .001); however, it did not mediate the structural determinants and frailty relationship. CONCLUSION: Contrary to expectations, cumulative psychosocial stress did not mediate the relationship between structural determinants and frailty. Rather, high cumulative psychosocial stress was independently associated with frailty. Further research should examine other psychosocial mediators to inform interventions to prevent/delay frailty.

Predictors of cognitive gains during inpatient rehabilitation for older adults with traumatic brain injury.

INTRODUCTION: Traumatic brain injury (TBI) among older adults is increasing and can affect cognition. To effectively meet the rehabilitation needs of older adults, a clearer picture is needed of patient-, clinical-, and facility-level characteristics that affect cognitive recovery during inpatient rehabilitation facility (IRF) stays. OBJECTIVE: To identify patient, clinical, and facility factors associated with cognitive recovery among older adults with TBI who received IRF care. DESIGN: Secondary data analysis. SETTING: Uniform Data System for Medical Rehabilitation-participating IRFs in the United States. PATIENTS: Patients were 65 to 99 years of age at IRF admission for TBI. Participants received IRF care between 2002 and 2018 (N = 137,583); 56.3% were male; 84.2% were white; mean age was 78.7 years. MAIN OUTCOME MEASURE: Change in Functional Independence Measure Cognitive Score (FIM-Cognitive) from IRF admission to discharge, categorized as favorable (FIM-cognitive score gains ≥3 points) or poor (FIM-cognitive score gains <3 points) cognitive outcomes. INTERVENTIONS: Not applicable. RESULTS: Patients had greater odds of favorable cognitive recovery if they were female (adjusted odds ratio [aOR] 1.05, 95% confidence interval [CI] 1.05-1.08), had higher motor functioning at IRF admission (aOR 1.03, 95% CI 1.03-1.04), longer length of stay (aOR 1.07, 95% CI 1.06-1.07), or received care at a freestanding IRF (vs. hospital rehab unit) (aOR 1.57, 95% CI 1.52-1.61). Patients who were older (aOR 0.99, 95% CI 0.98-0.99), Black (aOR 0.79, 95% CI 0.75-0.83), Hispanic or Latino (aOR 0.97, 95% CI 0.91-1.02), or were part of another racial or ethnic group (aOR 0.85, 95% CI 0.81-0.90) (vs. White), had high-cost comorbid conditions (aOR 0.71, 95% CI 0.65-0.76), or who had higher cognitive functioning at IRF admission (aOR 0.90, 95% CI 0.90-0.91) had lower odds of favorable cognitive recovery. CONCLUSIONS: Patient (age, sex, race, ethnicity), clinical (level of functioning at IRF admission, length of stay) and facility (e.g., freestanding IRF) factors contributed to the cognitive recoveries of older adults during IRF stays.

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. Research Design and Methods: Multiple databases, including MEDLINE (via PubMed), Embase (via Elsevier), and Web of Science (via Clarivate), were searched extensively. Studies that examined cardiometabolic risk factors and frailty as main predictors and outcome of interest, respectively, among older adults (≥60 years) were included. The Joanna Briggs Institute critical appraisal tools were used to evaluate the quality of studies. PRISMA (2020) guided this review, and findings were synthesized without meta-analysis. This systematic review was registered in PROSPERO (CRD42021252565). Results: Twelve studies met the eligibility criteria and were included in the review. Abdominal obesity, hyperglycemia, and multiple co-occurring cardiometabolic risk factors were associated with the increased likelihood of frailty in older adults. There was inconsistency across the studies regarding the associations between dyslipidemia, elevated blood pressure, and frailty. Discussion and Implications: Understanding the association between cardiometabolic risk factors and frailty can have translational benefits in developing tailored interventions for the prevention and management of frailty. More studies are needed to validate predictive and clinically significant associations between single and specific combinations of co-occurring cardiometabolic risk factors and frailty.

Sex and Racial/Ethnic Differences in Within-Stay Readmissions During Inpatient Rehabilitation Among Patients With Traumatic Brain Injury.

OBJECTIVE: The aim of the study was to determine the association of sex and race/ethnicity with acute hospital readmissions ("within-stay readmissions") during inpatient rehabilitation facility care versus patients discharged home without a within-stay readmission among traumatic brain injury patients. DESIGN: The study used a secondary analysis ( N = 210,440) of Uniform Data System for Medical Rehabilitation data using multiple logistic regression. RESULTS: Within-stay readmissions occurred for 11.79% of female and 11.77% of male traumatic brain injury patients. Sex-specific models identified insurance, comorbidities, and complications factored differently in likelihood of within-stay readmissions among female than male patients but association of all other factors were similar per group. Within-stay readmissions differences were more pronounced by race/ethnicity: White, 11.63%; Black, 11.32%; Hispanic/Latino, 9.78%; and other, 10.61%. Descriptive bivariate analysis identified racial/ethnic patients with within-stay readmissions had greater days from traumatic brain injury to inpatient rehabilitation facility admission (White, 17.66; Black, 21.70; Hispanic/Latino, 23.81; other, 20.66) and lower admission cognitive and motor function. Factors differed across models predicting within-stay readmissions for race/ethnic groups; age, admission motor and cognitive function, complications, and length of stay were consistent across groups. CONCLUSIONS: This study demonstrates disparities by race/ethnicity for inpatient rehabilitation facility within-stay readmissions among traumatic brain injury patients and factors predictive of this potentially preventable outcome by sex and race/ethnicity. Findings could inform care planning and quality improvement efforts for TBI patients.

Presurgical and Postsurgical Opioid Rates in Patients Undergoing Total Shoulder Replacement Surgery.

BACKGROUND: The purpose of this study was to describe the pre- and postsurgical opioid prescription rates and average morphine milligram equivalents (MME) per day in patients undergoing total shoulder replacement (TSR) procedures. METHODS: Patients undergoing TSR were identified from the electronic health records (EMR). In addition to patient demographics, opioid prescription 12-months presurgery and postsurgery were recorded. Patients were categorized into two groups: patients with no opioid prescriptions within 12 months before surgery and patients with an opioid prescription after surgery. McNemar tests were conducted to test for significant presurgical to postsurgical changes in opioid rate changes. The Wilcoxon signed rank test was used to test for significant pre- to postsurgical changes in average MME/day/person, and bivariate logistic regression analyses and covariate-adjusted logistic regressions were used to predict postsurgical opioid prescriptions. RESULTS: Overall, 1,076 patients underwent TSR. More than 900 patients received presurgical opioid prescriptions. There was a significant increase (p = .0015) in pre-surgical to postsurgical prescription rates. Postsurgical opioid prescriptions were 4.6 times more likely to be prescribed to a pre-surgical non-opioid patient than an opioid patient (p < .0001). Among those prescribed an opioid, the median dosage was <50 MME/day and over 82% of patients were at low overdose risk. Patients with comorbidities and without pre-surgical alcohol use were more likely to receive postsurgical opioids. Postsurgical opioid prescriptions were 4.6 times more likely to be prescribed to a presurgical non-opioid patient than an opioid patient (p < .0001). More than 80% of patients undergoing TSR received presurgical opioids. Among those prescribed any opioid, the median dosage was <50 MME/day and greater than 82% of patients were at low overdose risk. CONCLUSIONS: Although presurgical non-opioid patients were more likely to receive a postsurgical opioid prescription, based on dosage, most patients were at low risk for an opioid-related overdose or death according to CDC guidelines.

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. METHODS: This was a longitudinal study with descriptive analysis of the Healthcare Cost and Utilization Project of National Inpatient Sample data. FINDINGS: During this study period, the total number of discharges was 1 333 996. Patients with CAD between 65 and 84 years old were among the highest users of inpatient hospital services, followed by those in the 45- to 64-year age group. The death rate increased from 5961 to 7217 per 10 000 patients during this time. The mean charge increased more than 5 times, from $9100 to $49 643. There was a large difference in mean hospital charges in urban ($51 666) and rural ($25 548) locations in 2014. Coronary artery disease patients with private insurance paid more than those with Medicaid and Medicare plans. The discharge to home and healthcare costs increased by 4.1% and 4.8%, respectively. CONCLUSION AND IMPLICATIONS: Future researchers should use data sets, such as Medicare claims/Medical Expenditure Panel Study, that can provide comprehensive insights into patient-level factors influencing the use of inpatient care services among patients with CAD. Healthcare providers in posthospital settings should be well skilled in providing advanced cardiac rehabilitation and education to patients with CAD.

Preoperative and Postoperative Opioid Prescription Rates in the Total Hip Replacement Surgical Patient.

The United States is facing an opioid epidemic that has only worsened with the COVID-19 pandemic. There is little evidence regarding patterns of opioid use among patients with total hip replacement (THR). Although the Centers for Disease Control and Prevention has put forward guidelines for prescribing opioids, it does not include guidance specifically for THR patients suffering from presurgical and postsurgical pain. The purpose of this study was to (1) compare presurgical and postsurgical opioid rates, (2) compare presurgical and postsurgical morphine milligram equivalents (MME), and (3) determine whether having a presurgical opioid prescription predicts the receipt of postsurgical opioid prescriptions among patients undergoing THR surgery. Retrospective cohort analysis of 4,405 patients undergoing THR at a major academic medical center in the United States from April 30, 2015, to April 30, 2018, was done. Patient characteristics, opioid rates, and average MME/day/person were described. Logistic regression was used to determine whether presurgical opioid prescription and opioid risk level predicted postsurgical opioid prescribing. Median age was 64 years (range = 18-85 years); patients were primarily Caucasian/White (78.8%) and female (54.7%). Opioid prescription rates in this sample for the 12-month presurgical and postsurgical periods were 66.1% and 95.6%, respectively. Oxycodone was the most common opioid prescribed in both periods. Among those prescribed an opioid, moderate/high risk for overdose and/or death was 6.3% presurgery and 19.8% postsurgery. Patients with a comorbidity were two times more likely to receive an opioid prescription in the postsurgical period. The median average MME/day/person was 26.5 (range = 0.3-180.0) for patients with an opioid prescribed during the presurgery period and 40.4 (range = 1.5-270.0) during the postsurgery period. Opioid use, regardless of strength, in the presurgical period as well as having one or more comorbidities predicted opioid use in the postsurgical period.

Age- and sex-specific predictors of inpatient rehabilitation facility discharge destination for adult patients with traumatic brain injury.

OBJECTIVE: : To determine age- and sex-specific predictors of discharge destination among patients with traumatic brain injury (TBI) receiving inpatient rehabilitation facility (IRF) care. DESIGN: : Secondary analysis of Uniform Data System for Medical Rehabilitation data. METHODS: : Logistic regression of patients (N = 221,961) age ≥18, TBI diagnosis, admitted to IRF between 2002 and 2018. OUTCOME: : Discharge destination (subacute vs. home/community settings). RESULTS: : Approximately 16% were discharged to subacute vs. 84% home. Younger versus older adults had lower odds of subacute discharge [OR = 0.72; 95% CI: 0.69, 0.76]. Younger females had lower odds of subacute discharge (vs. home) than older females [OR = 0.68; 95% CI: 0.63, 0.74]; younger males had lower odds of subacute discharge (vs. home) than older males [OR = 0.74; 95% CI: 0.70, 0.78]. Younger females versus younger males had lower odds of subacute discharge (vs. home) [OR = 0.83; 95% CI: 0.79, 0.87]. Older females versus older males had lower odds of subacute discharge (vs. home) [OR = 0.93; 95% CI: 0.90, 0.97]. Predictors of discharge destination for age- and sex-stratified groups varied. CONCLUSIONS: : Younger (vs. older) and female (vs. male) patients had lower odds of subacute discharge vs. home.

Adaptive Challenges and Family Support: Patient Self-Management during Treatment for Chronic Hepatitis C.

The authors describe a family's adaptive challenges and adaptive work during a family member's treatment for Chronic Hepatitis C. We audiorecorded index and final clinical visits and interviewed participants (patients and providers) following the visits. We interviewed by telephone and reviewed medical records over the course of treatment. Transcripts were analyzed using directed content analysis. Three themes were identified: family adaptive challenges, patient-described aspects of family members' adaptive challenges, and family adaptive work. There were four subthemes related to family adaptive work. The adaptive leadership framework for chronic illness provided direction for future family intervention.

Group Coaching Among African-American Individuals with Prediabetes in a Faith-Based Setting.

Roughly 88 million adults have prediabetes and over 84% are unaware that they even have prediabetes. African-Americans have an increased risk of being diagnosed with prediabetes. Faith-based organizations have a history of serving as a primary source of social support for African-Americans. Parishioners with prediabetes from four African-American churches participated in free, evidence-based group coaching to learn how to manage and control risk factors associated with type 2 diabetes. The weekly group coaching sessions took place at a local church and they were co-facilitated by two trained professionals: a lifestyle coach and a nurse practitioner. At the conclusion of the 16-week group coaching sessions, participants had a decrease in hemoglobin A1C levels, an increase in minutes of physical activity per week, and an improvement in knowledge and behavior.