Nature and Mental Health in Urban Texas: A NatureScore-Based Study.

In this cross-sectional study, we examined the impact of access to nature on mental health utilization in urban neighborhoods using Texas outpatient encounters data merged with NatureScoreTM (0-100; low to high nature levels) and US census data (household income, education, employment, poverty, and insurance coverage) at the zipcode level. Our sample size included 61 million outpatient encounters across 1169 zipcodes, with 63% women and 30% elderly. A total of 369,344 mental health encounters were identified, with anxiety/stress and depression encounters representing 68.3% and 23.6%, respectively. We found that neighborhoods with a NatureScore of 60+ had lower overall mental health utilization than those below 40 (RR 0.51, 95%CI 0.38-0.69). This relationship persisted for depression, bipolar disorder, and anxiety/stress and in neighborhoods with a NatureScore above 80 (p < 0.001). Compared to neighborhoods with a NatureScore below 40, those above 80 had significantly lower depression (aRR 0.68, 95%CI 0.49-0.95) and bipolar (aRR 0.59, 95%CI 0.36-0.99) health encounters after adjusting for demographic and socioeconomic factors. This novel approach, utilizing NatureScore as a proxy for urban greenness, demonstrates the correlation between a higher NatureScore and reduced mental health utilization. Our findings highlight the importance of integrating nature into our healthcare strategies to promote well-being and mental health.

Race, Social Determinants of Health, and Risk of All-Cause and Cardiovascular Mortality in the United States.

OBJECTIVE: To examine the independent and interdependent effects of race and social determinants of health (SDoH) and risk of all-cause and cardiovascular disease (CVD) mortality in the US. DATA SOURCE/STUDY DESIGN: Secondary analysis of pooled data for 252,218 participants of the 2006-2018 National Health Interview Survey, linked to the National Death Index. METHODS: Age-adjusted mortality rates (AAMR) were reported for non-Hispanic White (NHW) and non-Hispanic Black (NHB) individuals overall, and by quintiles of SDoH burden, with higher quintiles representing higher cumulative social disadvantage (SDoH-Qx). Survival analysis was used to examine the association between race, SDoH-Qx, and all-cause and CVD mortality. FINDINGS: AAMRs for all-cause and CVD mortality were higher for NHB and considerably higher at higher levels of SDoH-Qx, however, with similar mortality rates at any given level of SDoH-Qx. In multivariable models, NHB experienced 20-25% higher mortality risk relative to NHW (aHR = 1.20-1.26); however, no association was observed after adjusting for SDoH. In contrast, higher SDoH burden was associated with up to nearly threefold increased risk of all-cause (aHR, Q5 vs Q1 = 2.81) and CVD mortality (aHR, Q5 vs Q1 = 2.90); the SDoH effect was observed similarly for NHB (aHR, Q5:all-cause mortality = 2.38; CVD mortality = 2.58) and NHW (aHR, Q5:all-cause mortality = 2.87; CVD mortality = 2.93) subgroups. SDoH burden mediated 40-60% of the association between NHB race and mortality. CONCLUSIONS: These findings highlight the critical role of SDoH as upstream drivers of racial inequities in all-cause and CVD mortality. Population level interventions focused on addressing adverse SDoH experienced by NHB individuals may help mitigate persistent disparities in mortality in the US.

Clinical and Economic Profile of Homeless Young Adults with Stroke in the United States, 2002-2017.

Homelessness is a major social determinant of health. We studied the clinical and economic profile of homeless young adults hospitalized with stroke. We studied the National Inpatient Sample database (2002-2017) to evaluate trends of stroke hospitalization, clinical outcomes, and health expenditure in homeless vs non-homeless young adults (<45 years). We identified 3134 homeless individuals out of 648,944 young adults. Homeless patients were more likely to be men, Black adults and had a higher prevalence of cardiometabolic risk factors and psychiatric disorders than non-homeless adults. Both homeless and non-homeless adults had a similar prevalence of ischemic and hemorrhagic stroke. Between 2002 and 2017, hospitalization rates per million increased for both non-homeless (295.8-416.8) and homeless adults (0.5-3.6) (P ≤ 0.01). Between 2003 and 2017, the decline in in-hospital mortality was limited to non-homeless adults (11%-9%), while it has increased in homeless adults (3%-11%) (P < 0.01). The prevalence of acute myocardial infarction (6.8% vs 3.3%, P < 0.01), and acute kidney injury (13.1% vs 9.4%, P < 0.01) was also higher in homeless vs. non-homeless adults. The length of stay and inflation-adjusted care cost were comparable between both study groups. Finally, a higher proportion of homeless patients left the hospital against medical advice than non-homeless adults. Homeless young stroke patients had significant comorbidities, increased hospitalization rates, and adverse clinical outcomes. Therefore, public health interventions should focus on multidisciplinary care to reduce health care disparities among young homeless adults.

Investigating burn-out contributors and mitigators among intensive care unit nurses during COVID-19: a focus group interview study.

OBJECTIVE: Past literature establishes high prevalence of burn-out among intensive care unit (ICU) nurses, and the influence of the COVID-19 pandemic in intensifying burn-out. However, the specific pandemic-related contributors and practical approaches to address burn-out have not been thoroughly explored. To address this gap, this work focuses on investigating the effect of the COVID-19 pandemic on the burn-out experiences of ICU nurses and identifying practical approaches for burn-out mitigation. DESIGN: Semistructured focus group interviews were conducted via convenience sampling and qualitatively analysed to identify burn-out contributors and mitigators. Maslach Burnout Inventory for Medical Personnel (MBI-MP) and Post-traumatic Stress Disorder Checklist (PCL-5) were employed to quantify the prevalence of burn-out of the participants at the time of study. SETTING: Two ICUs designated as COVID-19 ICUs in a large metropolitan tertiary care hospital in the Greater Houston area (Texas, USA). PARTICIPANTS: Twenty registered ICU nurses (10 from each unit). RESULTS: Participants experienced high emotional exhaustion (MBI-MP mean score 32.35, SD 10.66), moderate depersonalisation (M 9.75, SD 7.10) and moderate personal achievement (M 32.05, SD 7.59) during the pandemic. Ten out of the 20 participants exhibited post-traumatic stress disorder symptoms (PCL-5 score >33). Regarding contributors to burn-out in nurses during the pandemic, five thematic levels emerged-personal, patient related, coworker related, organisational and societal-with each factor comprising several subthemes (eg, emotional detachment from patients, constant need to justify motives to patients' family, lack of staffing and resources, and politicisation of COVID-19 and vaccination). Participants revealed several practical interventions to help overcome burn-out, ranging from mental health coverage to educating public on the severity of the pandemic and importance of vaccination. CONCLUSIONS: By identifying the contributors to burn-out in ICU nurses at a systems level, the study findings inform the design and implementation of effective interventions to prevent or mitigate pandemic-related burn-out among nurses.

Does hospital location matter? Association of neighborhood socioeconomic disadvantage with hospital quality in US metropolitan settings.

An aspect of a hospital's location, such as its degree of socioeconomic disadvantage, could potentially affect quality ratings of the hospital; yet, few studies have granularly explored this relationship in United States (US) metropolitan areas characterized by a wide breadth of socioeconomic disparities across neighborhoods. An understanding of the effect of neighborhood socioeconomic disadvantage on hospital quality of care is informative for targeting resources in poor neighborhoods. We assessed the association of neighborhood socioeconomic disadvantage with hospital quality of care across several areas of quality (including mortality, readmission, safety, patient experience, effectiveness of care, summary and overall star rating) in US metropolitan areas. Hospitals in the most disadvantaged neighborhoods, compared to hospitals in the least disadvantaged neighborhoods, had worse mortality scores, readmission scores, safety of care scores, patient experience of care scores, effectiveness of care scores, summary scores and overall star rating. Timeliness of care and efficient use of imaging scores were not strongly associated with neighborhood socioeconomic disadvantage; although, future studies are needed to validate this finding. Policymakers could target innovative strategies for improving neighborhood socioeconomic conditions in more disadvantaged areas, as this may improve hospital quality.

COVID-19 and communication: A sentiment analysis of US state governors' official press releases.

OBJECTIVES: This study examines the contents of official communication from United States governors' offices related to the COVID-19 pandemic to assess patterns in communication and to determine if they correlate with trends for COVID cases and deaths. METHODS: We collected text data for all COVID-19 related press releases between March 1 and December 31, 2020 from the US governors' office websites in all 50 states. An automated parsing and sentiment analyzer assessed descriptive statistics and trends in tone, including positivity and negativity. RESULTS: We included a total of 7,720 press releases in this study. We found that both positive and negative sentiments were homogenous across states at the beginning of the pandemic but became heterogeneous as the pandemic evolved. The same trend applied to the frequency and tone of press releases. Sentiments across states were overall positive with a small level of negativity. We observed a reactive official communication to the evolution of the number of COVID-19 cases rather than responsive or preventive. CONCLUSIONS: The findings of both positivity and negativity in press communications suggest that the effect of discounted importance was present in official communications. Our findings support a state-dependent optimal communication frequency and tone, agreeing with the curvilinear communication model of organizational theory and implying that feedback cycles between government officials and public response should be shortened to rapidly maximize communication efficacy during the pandemic. Future research should identify and evaluate the drivers of the large differences in communication tone across states and validate the reactive characteristics of COVID-19 official communications.

Rural Hospital Closures: Effects on Utilization and Medical Spending Among Commercially Insured Individuals.

BACKGROUND: Access to health care continues to be a challenge, especially in remote areas. Since 2013, 70 rural hospitals have closed in the United States further exacerbating barriers to health care access in rural areas. OBJECTIVE: The objective of this study is to identify the impact of rural hospital closures on total medical spending and utilization among the commercially insured rural population. RESEARCH DESIGN: We use a pre-post study design with a comparison group. Individual-level Texas commercial claims data in 2014-2019 were linked to the Centers for Medicare & Medicaid Services (CMS) Provider of Services Current Files, Area Health Resource File, and Census American Community Survey. We performed an event study to test for pre-trends. SUBJECTS: Analysis sample included commercially insured individuals 19-64 years of age residing in Texas. MEASURES: Total medical spending and counts of health care encounters. RESULTS: Individuals residing in rural Texas areas affected by a hospital closure experienced decreases in outpatient and emergency department (ED) utilization and no statistically significant changes in total medical spending relative to the unaffected individuals. Outpatient and ED utilization decreased by 0.133 (<0.1) and 0.015 (7<0.05) visits, respectively. Heterogeneity analysis showed that individuals residing in urban Texas experienced increases in total medical spending by $12.2 per month (<0.01) as well as individual spending subcategories. CONCLUSIONS: Rural hospital closures led to significant decreases in outpatient and ED utilization while having no effect on health care spending. Close attention must be paid to rural hospital closures to ensure equitable health care access, especially for underserved populations.

Elevated hemoglobin A1c level and bariatric surgery complications.

INTRODUCTION: In cardiac and orthopedic surgery, elevated glycosylated hemoglobin (HbA1c) is a modifiable risk factor for postoperative complications. However, in bariatric surgery, there is insufficient evidence to assess the effectiveness of preoperative HbA1c assessment and its association with postoperative complications. The objective of this study was to assess the impact of HbA1c on early postoperative outcomes in bariatric surgery patients. METHODS: Patients who underwent laparoscopic sleeve gastrectomy and laparoscopic Roux-En-Y Gastric Bypass between 2017 and 2018 were selected for a retrospective review from the metabolic and bariatric surgery accreditation and quality improvement program (MBSAQIP) database. The study population of 118,742 patients was analyzed for our primary outcome which was defined as a composite of any postoperative complications occurring within 30 days. Two groups were defined by HbA1c cutoff: comparison point A (≤ 8% vs > 8%) and comparison point B (≤ 10% vs > 10%). Procedure-related complications were also examined on subgroup analysis. Propensity score matching (PSM) was used with one-to-one matching. The complication rates before and after PSM were calculated and assessed by Fisher's exact test and conditional logistic regression, respectively. RESULTS: After PSM, demographic and clinical characteristics were all balanced and elevated HbA1C was not associated with worse outcomes. After adjusting for underlying comorbidities, there was no statistically significant difference seen in the composite outcome for comparison point A HbA1C ≤ 8 and HbA1C > 8 (p = 0.22). For comparison point B, patients with HbA1C ≤ 10 had more composite complications compared to patients with HbA1C > 10 (p < 0.001). Also, on subgroup analysis after PSM for procedure-specific complications, patients above the cutoff threshold of 8 did not have worsened composite outcomes (p = 0.58 and 0.89 for sleeve and bypass, respectively). Again, at cutoff threshold of 10, patients in HbA1C ≤ 10 had more composite complications (p = 0.001 and 0.007 for sleeve and bypass, respectively). CONCLUSION: In this study of bariatric patients, elevated HbA1c > 8% or 10% was not associated with increased postoperative complications. HbA1c lower than 10% was associated with some types of adverse outcomes in this bariatric dataset. More studies are needed to investigate these findings further. A high HbA1c alone may not disqualify a patient from proceeding with bariatric surgery.

Pediatric asthma hospitalization: individual and environmental characteristics of high utilizers in South Texas.

Objective: Few studies have examined factors affecting the high frequency of hospitalization for pediatric asthma. This study identifies individual and environmental characteristics of children with asthma from a low-income community with a high number of hospitalizations.Methods: The study population included 902 children admitted at least once to a children's hospital in South Texas because of asthma from 2010 to 2016. The population was divided into three groups by utilization frequency (high: ≥4 times, medium: 2-3 times, or low: 1 time). Individual-level factors at index admission and environmental factors were included for the analysis. Unadjusted and adjusted multivariate ordered logistic regression models were applied to identify significant characteristics of high hospital utilizers.Results: The high utilization group comprised 2.4% of total patients and accounted for substantial hospital resource utilization: 10.8% of all admissions and 13.5% of days stayed in the hospital. Patients in the high utilization group showed longer length of stay (LOS) and shorter time between admissions on average than the other two groups. The multivariate ordered logistic regression models revealed that age of 5-11 years (OR = 0.57, 95%CI = 0.35-0.93), longer LOS (2 days: OR = 1.80, 95%CI = 1.15-2.84; ≥3 days: OR = 3.38, 95%CI = 2.10-5.46), warm season at index admission (OR = 1.49, 95%CI = 1.01-2.20), and higher average ozone level in children's residential neighborhoods (OR = 1.78, 95%CI = 1.01-3.14) were significantly associated with a higher number of asthma hospitalizations.Conclusions: The findings suggest the importance of monitoring high hospital utilizers and establishing strategies for such patients based on their characteristics to reduce repeated hospitalizations and to increase optimal use of hospital resources.

Comparison of LACE and HOSPITAL Readmission Risk Scores for CMS Target and Nontarget Conditions.

This study evaluated the utility and performance of the LACE index and HOSPITAL score with consideration of the type of diagnoses and assessed the accuracy of these models for predicting readmission risks in patient cohorts from 2 large academic medical centers. Admissions to 2 hospitals from 2011 to 2015, derived from the Vizient Clinical Data Base and regional health information exchange, were included in this study (291 886 encounters). Models were assessed using Bayesian information criterion and area under the receiver operating characteristic curve. They were compared in CMS diagnosis-based cohorts and in 2 non-CMS cancer diagnosis-based cohorts. Overall, both models for readmission risk performed well, with LACE performing slightly better (area under the receiver operating characteristic curve 0.73 versus 0.69; P ≤ 0.001). HOSPITAL consistently outperformed LACE among 4 CMS target diagnoses, lung cancer, and colon cancer. Both LACE and HOSPITAL predict readmission risks well in the overall population, but performance varies by salient, diagnosis-based risk factors.

Comprehensive cost-effectiveness of diabetes management for the underserved in the United States: A systematic review.

BACKGROUND: Diabetes mellitus affects almost 10% of U.S. adults, leading to human and financial burden. Underserved populations experience a higher risk of diabetes and related complications resulting from a combination of limited disposable income, inadequate diet, and lack of insurance coverage. Without the requisite resources, underserved populations lack the ability to access healthcare and afford prescription drugs to manage their condition. The aim of this systematic review is to synthesize the findings from cost-effectiveness studies of diabetes management in underserved populations. METHODS: Original, English, peer-reviewed cost-effectiveness studies of diabetes management in U.S. underserved populations were obtained from 8 databases, and PRISMA 2009 reporting guidelines were followed. Evidence was categorized as strong or weak based on a combination of GRADE and American Diabetes Association guidelines. Internal validity was assessed by the Cochrane methodology. Studies were classified by incremental cost-effectiveness ratio as very cost-effective (ICER≤US$25,000), cost-effective (US$25,000US$100,000). Reporting and quality of economic evaluations was assessed using the CHEERS guidelines and Recommendations of Second Panel for Cost-Effectiveness in Health and Medicine, respectively. FINDINGS: Fourteen studies were included. All interventions were found to be cost-effective or very cost-effective. None of the studies reported all 24 points of the CHEERS guidelines. Given the considered cost categories vary significantly between studies, assessing cost-effectiveness across studies has many limitations. Program costs were consistently analyzed, and a third of the included studies (n = 5) only examined these costs, without considering other costs of diabetes care. INTERPRETATION: Cost-effectiveness studies are not based on a standardized methodology and present incomplete or limited analyses. More accurate assessment of all direct and indirect costs could widen the gap between intervention and usual care. This demonstrates the urgent need for a more standardized and comprehensive cost-effectiveness framework for future studies.

Validating Visual Stimuli of Nature Images and Identifying the Representative Characteristics.

This study fills a void in the literature by both validating images of nature for use in future research experiments and examining which characteristics of these visual stimuli are found to be most representative of nature. We utilized a convenience sample of university students to assess 129 different nature images on which best represented nature. Participants (n = 40) viewed one image per question (n = 129) and were asked to rate images using a 5-point Likert scale, with the anchors "best represents nature" (5) and "least represents nature" (1). Average ratings across participants were calculated for each image. Canopies, mountains, bodies of water, and unnatural elements were identified as semantic categories of interest, as well as atmospheric perspectives and close-range views. We conducted the ordinary least squares (OLS) regression and the ordered logistic regression analyses to identify semantic categories highly representative of nature, controlling for the presence/absence of other semantic categories. The results showed that canopies, bodies of water, and mountains were found to be highly representative of nature, whereas unnatural elements and close-range views were inversely related. Understanding semantic categories most representative of nature is useful in developing nature-centered interventions in behavioral performance research and other neuroimaging modalities. All images are housed in an online repository and we welcome the use of the final 10 highly representative nature images by other researchers, which will hopefully prompt and expedite future examinations of nature across multiple research formats.

Development and validation of a polysocial risk score for atherosclerotic cardiovascular disease.

OBJECTIVE: To date, the extent to which social determinants of health (SDOH) may help identify individuals with atherosclerotic cardiovascular disease (ASCVD) - beyond traditional risk factors - has not been quantified using a cumulative social disadvantage approach. The objective of this study was to develop, and validate, a polysocial risk score (PsRS) for prevalent ASCVD in a nationally representative sample of adults in the United States (US). METHODS: We used data from the 2013-2017 National Health Interview Survey. A total of 38 SDOH were identified from the database. Stepwise and criterion-based selection approaches were applied to derive PsRS, after adjusting for traditional risk factors. Logistic regression models were fitted to assign risk scores to individual SDOH, based on relative effect size magnitudes. PsRS was calculated by summing risk scores for individual SDOH, for each participant; and validated using a separate validation cohort. RESULTS: Final sample comprised 164,696 adults. PsRS included 7 SDOH: unemployment, inability to pay medical bills, low income, psychological distress, delayed care due to lack of transport, food insecurity, and less than high school education. PsRS ranged from 0-20 and exhibited excellent calibration and discrimination. Individuals with the highest PsRS (5th quintile) had nearly 4-fold higher ASCVD prevalence, relative to those with the lowest risk scores (1st quintile). Area under receiver operating curve (AU-ROC) for PsRS with SDOH alone was 0.836. Addition of SDOH to the model with only demographic and clinical risk factors (AU-ROC=0.852) improved overall discriminatory power, with AU-ROC for final PsRS (demographics + clinical + SDOH) = 0.862. CONCLUSIONS: Cumulatively, SDOH may help identify individuals with ASCVD, beyond traditional cardiovascular risk factors. In this study, we provide a unique validated PsRS for ASCVD in a national sample of US adults. Future study should target development of similar scores in diverse populations, and incorporate longitudinal study designs.

Disparities in COVID-19 hospitalizations and mortality among black and Hispanic patients: cross-sectional analysis from the greater Houston metropolitan area.

BACKGROUND: Disparate racial/ethnic burdens of the Coronavirus Disease 2019 (COVID-19) pandemic may be attributable to higher susceptibility to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) or to factors such as differences in hospitalization and care provision. METHODS: In our cross-sectional analysis of lab-confirmed COVID-19 cases from a tertiary, eight-hospital healthcare system across greater Houston, multivariable logistic regression models were fitted to evaluate hospitalization and mortality odds for non-Hispanic Blacks (NHBs) vs. non-Hispanic Whites (NHWs) and Hispanics vs. non-Hispanics. RESULTS: Between March 3rd and July 18th, 2020, 70,496 individuals were tested for SARS-CoV-2; 12,084 (17.1%) tested positive, of whom 3536 (29.3%) were hospitalized. Among positive cases, NHBs and Hispanics were significantly younger than NHWs and Hispanics, respectively (mean age NHBs vs. NHWs: 46.0 vs. 51.7 years; p < 0.001 and Hispanic vs. non-Hispanic: 44.0 vs. 48.7 years; p < 0.001). Despite younger age, NHBs (vs. NHWs) had a higher prevalence of diabetes (25.2% vs. 17.6%; p < 0.001), hypertension (47.7% vs. 43.1%; p < 0.001), and chronic kidney disease (5.0% vs. 3.3%; p = 0.001). Both minority groups resided in lower median income (median income [USD]; NHBs vs. NHWs: 63,489 vs. 75,793; p < 0.001, Hispanic vs. non-Hispanic: 59,104 vs. 68,318; p < 0.001) and higher population density areas (median population density [per square mile]; NHBs vs. NHWs: 3257 vs. 2742; p < 0.001, Hispanic vs. non-Hispanic: 3381 vs. 2884; p < 0.001). In fully adjusted models, NHBs (vs. NHWs) and Hispanics (vs. non-Hispanic) had higher likelihoods of hospitalization, aOR (95% CI): 1.42 (1.24-1.63) and 1.61 (1.46-1.78), respectively. No differences were observed in intensive care unit (ICU) utilization or treatment parameters. Models adjusted for demographics, vital signs, laboratory parameters, hospital complications, and ICU admission vital signs demonstrated non-significantly lower likelihoods of in-hospital mortality among NHBs and Hispanic patients, aOR (95% CI): 0.65 (0.40-1.03) and 0.89 (0.59-1.31), respectively. CONCLUSIONS: Our data did not demonstrate racial and ethnic differences in care provision and hospital outcomes. Higher susceptibility of racial and ethnic minorities to SARS-CoV-2 and subsequent hospitalization may be driven primarily by social determinants.

Social Determinants of Health and Cardiovascular Disease: Current State and Future Directions Towards Healthcare Equity.

PURPOSE OF REVIEW: We sought to examine the role of social and environmental conditions that determine an individual's behaviors and risk of disease-collectively known as social determinants of health (SDOH)-in shaping cardiovascular (CV) health of the population and giving rise to disparities in risk factors, outcomes, and clinical care for cardiovascular disease (CVD), the leading cause of death in the United States (US). RECENT FINDINGS: Traditional CV risk factors have been extensively targeted in existing CVD prevention and management paradigms, often with little attention to SDOH. Limited evidence suggests an association between individual SDOH (e.g., income, education) and CVD. However, inequities in CVD care, risk factors, and outcomes have not been studied using a broad SDOH framework. We examined existing evidence of the association between SDOH-organized into 6 domains, including economic stability, education, food, neighborhood and physical environment, healthcare system, and community and social context-and CVD. Greater social adversity, defined by adverse SDOH, was linked to higher burden of CVD risk factors and poor outcomes, such as stroke, myocardial infarction (MI), coronary heart disease, heart failure, and mortality. Conversely, favorable social conditions had protective effects on CVD. Upstream SDOH interact across domains to produce cumulative downstream effects on CV health, via multiple physiologic and behavioral pathways. SDOH are major drivers of sociodemographic disparities in CVD, with a disproportionate impact on socially disadvantaged populations. Efforts to achieve health equity should take into account the structural, institutional, and environmental barriers to optimum CV health in marginalized populations. In this review, we highlight major knowledge gaps for each SDOH domain and propose a set of actionable recommendations to inform CVD care, ensure equitable distribution of healthcare resources, and reduce observed disparities.

Effectiveness of Bariatric Surgery in Increasing Kidney Transplant Eligibility in Patients with Kidney Failure Requiring Dialysis.

PURPOSE: Severe obesity can increase risk of complications after kidney transplantation. There is a paucity of literature on bariatric surgery outcomes in renal transplant candidates. The objective of this study was to analyze outcomes of bariatric surgery as a weight reduction strategy for patients with kidney failure to enhance eligibility for kidney transplantation. MATERIALS AND METHODS: We performed a retrospective analysis of the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program database at a single institution for patients with chronic kidney disease receiving hemodialysis therapy (CKD G5D) undergoing bariatric surgery between 2011 and 2018. RESULTS: Of 2363 patients who underwent bariatric surgery, 38 (1.6%) had CKD G5D; median age (range) was 49 years (33; 69), 52.6% were female, and mean BMI was 44.2 kg/m2. Twenty-four patients underwent laparoscopic Roux-en-Y gastric bypass (LRYGB), and 14 patients underwent laparoscopic sleeve gastrectomy. Seventeen patients (46%, n=37) had a BMI≤35 at 6 months, while 25 patients (75.8%, n=33) achieved a BMI≤35 at 12 months. Of these, 18 patients (47%) were listed for kidney transplant, and 8 patients (21%) received kidney transplant. There was no statistically significant difference between sleeve and LRYGB procedures in patients who reached BMI of 35 at 12 months (P=0.58). Median length of stay was 2.3 days. Thirty-day readmission rate was 2 patients (5.3%), and 2 patients (5.3%) required reoperation (one for bleeding, one for acute recurrent hiatal hernia). No mortality occurred. CONCLUSION: Laparoscopic bariatric surgery offers effective weight loss for CKD G5D patients to achieve transplant eligibility with acceptable outcomes.

Factors Affecting Adoption of a Technology-Based Tool for Diabetes Self-Management Education and Support Among Adult Patients with Type 2 Diabetes in South Texas.

PURPOSE: The purpose of this study is to describe a novel computerized diabetes education tool and explore factors influencing self-selection and use among primarily Hispanic patients diagnosed with type 2 diabetes in south Texas. METHODS: Study participants included 953 adult patients with type 2 diabetes enrolled in a diabetes education program between July 1, 2016, and June 30, 2017. Participants were asked to choose either a new technology-based diabetes education tool with a touch-screen device or a traditional face-to-face education method. Multivariate logistic regression analysis was applied to identify factors associated with adopting the computerized diabetes education tool among the patients. RESULTS: When comparing technology-based tool adopters and nonadopters, several demographic and health-related factors differentiated technology use in bivariate analyses. The multivariate logistic regression model showed that Hispanic patients were less likely to choose a technology-based tool. Patients who perceived their health status as excellent/good were more likely to adopt the technologic education method than those with fair/poor perceived health status. A1C level was negatively associated with self-selection of technology. CONCLUSIONS: Specific demographic and health-related characteristics are significant contributing factors to patients' adoption of a technology-based diabetes education tool. Health care providers can utilize these findings to target and refer specific patients to a computerized diabetes education tool for more effective diabetes care and to optimize technology adoption success.

Social Determinants of Adherence to COVID-19 Risk Mitigation Measures Among Adults With Cardiovascular Disease.

BACKGROUND: Social determinants of health (SDOH) may limit the practice of coronavirus disease 2019 (COVID-19) risk mitigation guidelines with health implications for individuals with underlying cardiovascular disease (CVD). Population-based evidence of the association between SDOH and practicing such mitigation strategies in adults with CVD is lacking. We used the National Opinion Research Center's COVID-19 Household Impact Survey conducted between April and June 2020 to evaluate sociodemographic disparities in adherence to COVID-19 risk mitigation measures in a sample of respondents with underlying CVD representing 18 geographic areas of the United States. METHODS: CVD status was ascertained by self-reported history of receiving heart disease, heart attack, or stroke diagnosis. We built de novo, a cumulative index of SDOH burden using education, insurance, economic stability, 30-day food security, urbanicity, neighborhood quality, and integration. We described the practice of measures under the broad strategies of personal protection (mask, hand hygiene, and physical distancing), social distancing (avoiding crowds, restaurants, social activities, and high-risk contact), and work flexibility (work from home, canceling/postponing work). We reported prevalence ratios and 95% CIs for the association between SDOH burden (quartiles of cumulative indices) and practicing these measures adjusting for age, sex, race/ethnicity, comorbidity, and interview wave. RESULTS: Two thousand thirty-six of 25 269 (7.0%) adults, representing 8.69 million in 18 geographic areas of the United States, reported underlying CVD. Compared with the least SDOH burden, fewer individuals with the greatest SDOH burden practiced all personal protection (75.6% versus 89.0%) and social distancing measures (41.9% versus 58.9%) and had any flexible work schedule (26.2% versus 41.4%). These associations remained statistically significant after full adjustment: personal protection (prevalence ratio, 0.83 [95% CI, 0.73-0.96]; P=0.009), social distancing (prevalence ratio, 0.69 [95% CI, 0.51-0.94]; P=0.018), and work flexibility (prevalence ratio, 0.53 [95% CI, 0.36-0.79]; P=0.002). CONCLUSIONS: SDOH burden is associated with lower COVID-19 risk mitigation practices in the CVD population. Identifying and prioritizing individuals whose medical vulnerability is compounded by social adversity may optimize emerging preventive efforts, including vaccination guidelines.

Improving Psychiatric Care Through Integrated Digital Technologies.

This manuscript provides an overview of our efforts to implement an integrated electronic monitoring and feedback platform to increase patient engagement, improve care delivery and outcome of treatment, and alert care teams to deterioration in functioning. Patients First utilizes CareSense, a digital care navigation and data collection system, to integrate traditional patient-reported outcomes monitoring with novel biological monitoring between visits to provide patients and caregivers with real-time feedback on changes in symptoms such as stress, anxiety, and depression. The next stage of project development incorporates digital therapeutics (computerized therapeutic interventions) for patients, and video resources for primary care physicians and nurse practitioners who serve as the de facto front line for psychiatric care. Integration of the patient-reported outcomes monitoring with continuous biological monitoring, and digital supports is a novel application of existing technologies. Video resources pushed to care providers whose patients trigger a symptom severity alert is, to our knowledge, an industry first.

Rapid Response to Drive COVID-19 Research in a Learning Health Care System: Rationale and Design of the Houston Methodist COVID-19 Surveillance and Outcomes Registry (CURATOR).

BACKGROUND: The COVID-19 pandemic has exacerbated the challenges of meaningful health care digitization. The need for rapid yet validated decision-making requires robust data infrastructure. Organizations with a focus on learning health care (LHC) systems tend to adapt better to rapidly evolving data needs. Few studies have demonstrated a successful implementation of data digitization principles in an LHC context across health care systems during the COVID-19 pandemic. OBJECTIVE: We share our experience and provide a framework for assembling and organizing multidisciplinary resources, structuring and regulating research needs, and developing a single source of truth (SSoT) for COVID-19 research by applying fundamental principles of health care digitization, in the context of LHC systems across a complex health care organization. METHODS: Houston Methodist (HM) comprises eight tertiary care hospitals and an expansive primary care network across Greater Houston, Texas. During the early phase of the pandemic, institutional leadership envisioned the need to streamline COVID-19 research and established the retrospective research task force (RRTF). We describe an account of the structure, functioning, and productivity of the RRTF. We further elucidate the technical and structural details of a comprehensive data repository-the HM COVID-19 Surveillance and Outcomes Registry (CURATOR). We particularly highlight how CURATOR conforms to standard health care digitization principles in the LHC context. RESULTS: The HM COVID-19 RRTF comprises expertise in epidemiology, health systems, clinical domains, data sciences, information technology, and research regulation. The RRTF initially convened in March 2020 to prioritize and streamline COVID-19 observational research; to date, it has reviewed over 60 protocols and made recommendations to the institutional review board (IRB). The RRTF also established the charter for CURATOR, which in itself was IRB-approved in April 2020. CURATOR is a relational structured query language database that is directly populated with data from electronic health records, via largely automated extract, transform, and load procedures. The CURATOR design enables longitudinal tracking of COVID-19 cases and controls before and after COVID-19 testing. CURATOR has been set up following the SSoT principle and is harmonized across other COVID-19 data sources. CURATOR eliminates data silos by leveraging unique and disparate big data sources for COVID-19 research and provides a platform to capitalize on institutional investment in cloud computing. It currently hosts deeply phenotyped sociodemographic, clinical, and outcomes data of approximately 200,000 individuals tested for COVID-19. It supports more than 30 IRB-approved protocols across several clinical domains and has generated numerous publications from its core and associated data sources. CONCLUSIONS: A data-driven decision-making strategy is paramount to the success of health care organizations. Investment in cross-disciplinary expertise, health care technology, and leadership commitment are key ingredients to foster an LHC system. Such systems can mitigate the effects of ongoing and future health care catastrophes by providing timely and validated decision support.