Ambient heat exposure patterns and emergency department visits and hospitalizations among medicare beneficiaries 2008-2019.

OBJECTIVE: To assess the association between ambient heat and all-cause and cause-specific emergency department (ED) visits and acute hospitalizations among Medicare beneficiaries in the conterminous United States. DESIGN: Retrospective cohort study. SETTING: Conterminous US from 2008 and 2019. PARTICIPANTS: 2% random sample of all Medicare fee-for-service beneficiaries eligible for Parts A, B, and D. MAIN OUTCOME MEASURES: All-cause and cause-specific (cardiovascular, renal, and heat-related) ED visits and unplanned hospitalizations were identified using primary ICD-9 or ICD-10 diagnosis codes. We measured the association between ambient temperature - defined as daily mean temperature percentile of summer (June through September) - and the outcomes. Hazard ratios and their associated 95% confidence intervals were estimated using multivariable Cox proportional hazards regression, adjusting for individual level demographics, comorbidities, healthcare utilization factors and zip-code level social factors. RESULTS: Among 809,636 Medicare beneficiaries (58% female, 81% non-Hispanic White, 24% <65), older beneficiaries (aged ≥65) exposed to >95th percentile temperature had a 64% elevated adjusted risk of heat-related ED visits (HR [95% CI], 1.64 [1.46,1.85]) and a 4% higher risk of all-cause acute hospitalization (1.04 [1.01,1.06]) relative to <25th temperature percentile. Younger beneficiaries (aged <65) showed increased risk of heat-related ED visits (2.69 [2.23,3.23]) and all-cause ED visits (1.03 [1.01,1.05]). The associations with heat related events were stronger in males and individuals dually eligible for Medicare and Medicaid. No significant differences were observed by climatic region. We observed no significant relationship between temperature percentile and risk of CV-related ED visits or renal-related ED visits. CONCLUSIONS: Among Medicare beneficiaries from 2008 to 2019, exposure to daily mean temperature ≥ 95th percentile was associated with increased risk of heat-related ED visits, with stronger associations seen among beneficiaries <65, males, and patients with low socioeconomic position. Further longitudinal studies are needed to understand the impact of heat duration, intensity, and frequency on cause-specific hospitalization outcomes.

Clinicians Who Practice Primarily in Nursing Homes and the Quality of End-of-Life Care Among Residents.

Importance: Clinician specialization in the care of nursing home (NH) residents or patients in skilled nursing facilities (SNFs) has become increasingly common. It is not known whether clinicians focused on NH care, often referred to as SNFists (ie, physicians, nurse practitioners, and physician assistants concentrating their practice in the NH or SNF setting), are associated with a reduced likelihood of burdensome transitions in the last 90 days of life for residents, which are a marker of poor-quality end-of-life (EOL) care. Objective: To quantify the association between receipt of care from an SNFist and quality of EOL care for NH residents. Design, Setting, and Participants: This cohort study analyzed Medicare fee-for-service claims for a nationally representative 20% sample of beneficiaries to examine burdensome transitions among NH decedents at the EOL from January 1, 2013, through December 31, 2019. Statistical analyses were conducted from December 2022 to June 2023. Exposure: Receipt of care from an SNFist, defined as physicians and advanced practitioners who provided 80% or more of their evaluation and management visits in NHs annually. Main Outcomes and Measures: This study used augmented inverse probability weighting in analyses of Medicare fee-for-service claims for a nationally representative 20% sample of beneficiaries. Main outcomes included 4 measures of burdensome transitions: (1) hospital transfer in the last 3 days of life; (2) lack of continuity in NHs after hospitalization in the last 90 days of life; (3) multiple hospitalizations in the last 90 days of life for any reason or any hospitalization for pneumonia, urinary tract infection, dehydration, or sepsis; and (4) any hospitalization in the last 90 days of life for an ambulatory care-sensitive condition. Results: Of the 2 091 954 NH decedents studied (mean [SD] age, 85.4 [8.5] years; 1 470 724 women [70.3%]), 953 722 (45.6%) received care from SNFists and 1 138 232 (54.4%) received care from non-SNFists; 422 575 of all decedents (20.2%) experienced a burdensome transition at the EOL. Receipt of care by an SNFist was associated with a reduced risk of (1) hospital transfer in the last 3 days of life (-1.6% [95% CI, -2.5% to -0.8%]), (2) lack of continuity in NHs after hospitalization (-4.8% [95% CI, -6.7% to -3.0%]), and (3) decedents experiencing multiple hospitalizations for any reason or any hospitalization for pneumonia, urinary tract infection, dehydration, or sepsis (-5.8% [95% CI, -10.1% to -1.7%]). There was not a statistically significant association with the risk of hospitalization for an ambulatory care-sensitive condition in the last 90 days of life (0.0% [95% CI, -14.7% to 131.7%]). Conclusions and Relevance: This study suggests that SNFists may be an important resource to improve the quality of EOL care for NH residents.

Building Climate Change into Medical Education: A Society of General Internal Medicine Position Statement.

Building expertise in climate and planetary health among healthcare professionals cannot come with greater urgency as the threats from climate change become increasingly apparent. Current and future healthcare professionals-particularly internists-will increasingly need to understand the interconnectedness of natural systems and human health to better serve their patients longitudinally. Despite this, few national medical societies and accreditation bodies espouse frameworks for climate change and planetary health-related education at the undergraduate (UME), graduate (GME), and continuing (CME) medical education level. As a community of medical educators with an enduring interest in climate change and planetary health, the Society of General Internal Medicine (SGIM) recognizes the need to explicitly define structured educational opportunities and core competencies in both UME and GME as well as pathways for faculty development. In this position statement, we build from the related SGIM Climate and Health position statement, and review and synthesize existing position statements made by US-based medical societies and accreditation bodies that focus on climate change and planetary health-related medical education, identify gaps using Bloom's Hierarchy, and provide recommendations on behalf of SGIM regarding the development of climate and planetary health curricula development. Identified gaps include (1) limited systematic approach to climate and planetary health medical education at all levels; (2) minimal emphasis on learner-driven approaches; (3) limited focus on physician and learner well-being; and (4) limited role for health equity and climate justice. Recommendations include a call to relevant accreditation bodies to explicitly include climate change and planetary health as a competency, extend the structural competency framework to climate change and planetary health to build climate justice, proactively include learners in curricular development and teaching, and ensure resources and support to design and implement climate and planetary health-focused education that includes well-being and resiliency.

Ambient Heat and Risk of Serious Hypoglycemia in Older Adults With Diabetes Using Insulin in the U.S. and Taiwan: A Cross-National Case-Crossover Study.

OBJECTIVE: To measure the association between ambient heat and hypoglycemia-related emergency department visit or hospitalization in insulin users. RESEARCH DESIGN AND METHODS: We identified cases of serious hypoglycemia among adults using insulin aged ≥65 in the U.S. (via Medicare Part A/B/D-eligible beneficiaries) and Taiwan (via National Health Insurance Database) from June to September, 2016-2019. We then estimated odds of hypoglycemia by heat index (HI) percentile categories using conditional logistic regression with a time-stratified case-crossover design. RESULTS: Among ∼2 million insulin users in the U.S. (32,461 hypoglycemia case subjects), odds ratios of hypoglycemia for HI >99th, 95-98th, 85-94th, and 75-84th percentiles compared with the 25-74th percentile were 1.38 (95% CI, 1.28-1.48), 1.14 (1.08-1.20), 1.12 (1.08-1.17), and 1.09 (1.04-1.13) respectively. Overall patterns of associations were similar for insulin users in the Taiwan sample (∼283,000 insulin users, 10,162 hypoglycemia case subjects). CONCLUSIONS: In two national samples of older insulin users, higher ambient temperature was associated with increased hypoglycemia risk.

Risk stratification models for predicting preventable hospitalization in commercially insured late middle-aged adults with depression.

BACKGROUND: A significant number of late middle-aged adults with depression have a high illness burden resulting from chronic conditions which put them at high risk of hospitalization. Many late middle-aged adults are covered by commercial health insurance, but such insurance claims have not been used to identify the risk of hospitalization in individuals with depression. In the present study, we developed and validated a non-proprietary model to identify late middle-aged adults with depression at risk for hospitalization, using machine learning methods. METHODS: This retrospective cohort study involved 71,682 commercially insured older adults aged 55-64 years diagnosed with depression. National health insurance claims were used to capture demographics, health care utilization, and health status during the base year. Health status was captured using 70 chronic health conditions, and 46 mental health conditions. The outcomes were 1- and 2-year preventable hospitalization. For each of our two outcomes, we evaluated seven modelling approaches: four prediction models utilized logistic regression with different combinations of predictors to evaluate the relative contribution of each group of variables, and three prediction models utilized machine learning approaches - logistic regression with LASSO penalty, random forests (RF), and gradient boosting machine (GBM). RESULTS: Our predictive model for 1-year hospitalization achieved an AUC of 0.803, with a sensitivity of 72% and a specificity of 76% under the optimum threshold of 0.463, and our predictive model for 2-year hospitalization achieved an AUC of 0.793, with a sensitivity of 76% and a specificity of 71% under the optimum threshold of 0.452. For predicting both 1-year and 2-year risk of preventable hospitalization, our best performing models utilized the machine learning approach of logistic regression with LASSO penalty which outperformed more black-box machine learning models like RF and GBM. CONCLUSIONS: Our study demonstrates the feasibility of identifying depressed middle-aged adults at higher risk of future hospitalization due to burden of chronic illnesses using basic demographic information and diagnosis codes recorded in health insurance claims. Identifying this population may assist health care planners in developing effective screening strategies and management approaches and in efficient allocation of public healthcare resources as this population transitions to publicly funded healthcare programs, e.g., Medicare in the US.

The impact of commercial health datasets on medical research and health-care algorithms.

As the health-care industry emerges into a new era of digital health driven by cloud data storage, distributed computing, and machine learning, health-care data have become a premium commodity with value for private and public entities. Current frameworks of health data collection and distribution, whether from industry, academia, or government institutions, are imperfect and do not allow researchers to leverage the full potential of downstream analytical efforts. In this Health Policy paper, we review the current landscape of commercial health data vendors, with special emphasis on the sources of their data, challenges associated with data reproducibility and generalisability, and ethical considerations for data vending. We argue for sustainable approaches to curating open-source health data to enable global populations to be included in the biomedical research community. However, to fully implement these approaches, key stakeholders should come together to make health-care datasets increasingly accessible, inclusive, and representative, while balancing the privacy and rights of individuals whose data are being collected.

Comparing Hospital Length of Stay Risk-Adjustment Models in US Value-Based Physician Payments.

BACKGROUNG AND OBJECTIVES: Under the Affordable Care Act, the US Centers for Medicare & Medicaid Services created the Physician Value-Based Payment Modifier Program and its successor, the Merit-Based Incentive Payment System, to tie physician payments to quality and cost. The addition of hospital length of stay (LOS) to these value-based physician payment models reflects its increasing importance as a metric of health care cost and efficiency and its association with adverse health outcomes. This study compared the Centers for Medicare & Medicaid Services-endorsed LOS risk-adjustment methodology with a novel methodology that accounts for pre-hospitalization clinical, socioeconomic status (SES), and admission-related factors as influential factors of hospital LOS. METHODS: Using the 2014 New York, Florida, and New Jersey State Inpatient Database, we compared the observed-to-expected LOS of 2373102 adult admissions for 742 medical and surgical diagnosis-related groups (DRGs) by 3 models: ( a ) current risk-adjustment model (CRM), which adjusted for age, sex, number of chronic conditions, Elixhauser comorbidity score, and DRG severity weight, ( b ) CRM but modeling LOS using a generalized linear model (C-GLM), and (c) novel risk-adjustment model (NRM), which added to the C-GLM covariates for race/ethnicity, SES, discharge destination, weekend admission, and individual intercepts for DRGs instead of severity weights. RESULTS: The NRM disadvantaged physicians for fewer medical and surgical DRGs, compared with both the C-GLM and CRM models (medical DRGs: 0.49% vs 13.17% and 10.89%, respectively; surgical DRGs: 0.30% vs 13.17% and 10.98%, respectively). In subgroup analysis, the NRM reduced the proportion of physician-penalizing DRGs across all racial/ethnic and socioeconomic groups, with the highest reduction among Whites, followed by low SES patients, and the lowest reduction among Hispanic patients. CONCLUSIONS: After accounting for pre-hospitalization socioeconomic and clinical factors, the adjusted LOS using the NRM was lower than estimates from the current Centers for Medicare & Medicaid Services-endorsed model. The current model may disadvantage physicians serving communities with higher socioeconomic risks.

Association Between Patient Diversity in Hospitals and Racial/Ethnic Differences in Patient Length of Stay.

BACKGROUND: Hospitals serving a disproportionate share of racial/ethnic minorities have been shown to have poorer quality outcomes. It is unknown whether efficiencies in inpatient care, measured by length of stay (LOS), differ based on the proportion patients served by a hospital who are minorities. OBJECTIVE: To examine the association between the racial/ethnic diversity of a hospital's patients and disparities in LOS. DESIGN: Retrospective cross-sectional study. PARTICIPANTS: One million five hundred forty-six thousand nine hundred fifty-five admissions using the 2017 New York State Inpatient Database from the Healthcare Cost and Utilization Project. MAIN MEASURE: Differences in mean adjusted LOS (ALOS) between White and Black, Hispanic, and Other (Asian, Pacific Islander, Native American, and Other) admissions by Racial/Ethnic Diversity Index (proportion of non-White patients admitted to total patients admitted to that same hospital) in quintiles (Q1 to Q5), stratified by discharge destination. Mean LOS was adjusted for patient demographic, clinical, and admission characteristics and for individual intercepts for each hospital. KEY RESULTS: In both unadjusted and adjusted analysis, Black-White and Other-White mean LOS differences were smallest in the most diverse hospitals (Black-White: unadjusted, -0.07 days [-0.1 to -0.04], and adjusted, 0.16 days [95% CI: 0.16 to 0.16]; Other-White: unadjusted, -0.74 days [95% CI: -0.77 to -0.71], and adjusted, 0.01 days [95% CI: 0.01 to 0.02]). For Hispanic patients, in unadjusted analysis, the mean LOS difference was greatest in the most diverse hospitals (-0.92 days, 95% CI: -0.95 to -0.89) but after adjustment, this was no longer the case. Similar patterns across all racial/ethnic groups were observed after analyses were stratified by discharge destination. CONCLUSION: Mean adjusted LOS differences between White and Black patients, and White and patients of Other race was smallest in most diverse hospitals, but not differences between Hispanic and White patients. These findings may reflect specific structural factors which affect racial/ethnic differences in patient LOS.

Association Between Racial Disparities in Hospital Length of Stay and the Hospital Readmission Reduction Program.

BACKGROUND: On average Black patients have longer LOS than comparable White patients. Longer hospital length of stay (LOS) may be associated with higher readmission risk. However, evidence suggests that the Hospital Readmission Reduction Program (HRRP) reduced overall racial differences in 30-day adjusted readmission risk. Yet, it is unclear whether the HRRP narrowed these LOS racial differences. OBJECTIVE: We examined the relationship between Medicare-insured Black-White differences in average, adjusted LOS (ALOS) and the HRRP's implementation and evaluation periods. METHODS: Using 2009-2017 data from State Inpatient Dataset from New York, New Jersey, and Florida, we employed an interrupted time series analysis with multivariate generalized regression models controlling for patient, disease, and hospital characteristics. Results are reported per 100 admissions. RESULTS: We found that for those discharged home, Black-White ALOS differences significantly widened by 4.15 days per 100 admissions (95% CI: 1.19 to 7.11, P < 0.001) for targeted conditions from before to after the HRRP implementation period, but narrowed in the HRRP evaluation period by 1.84 days per 100 admissions for every year-quarter (95% CI: -2.86 to -0.82, P < 0.001); for those discharged to non-home destinations, there was no significant change between HRRP periods, but ALOS differences widened over the study period. Black-White ALOS differences for non-targeted conditions remained unchanged regardless of HRRP phase and discharge destination. CONCLUSION: Increased LOS for Black patients may have played a role in reducing Black-White disparities in 30-day readmission risks for targeted conditions among patients discharged to home.

Racial/ethnic and socioeconomic variations in hospital length of stay: A state-based analysis.

ABSTRACT: Disparities by race/ethnicity and socioeconomic status (SES) exist in rehospitalization rates and inpatient mortality rates. Few studies have examined how length of stay (LOS, a measure of hospital efficiency/quality) differs by race/ethnicity and SES.This study's objective was to determine whether differences in risk-adjusted LOS exist by race/ethnicity and SESUsing a retrospective cohort of 1,432,683 medical and surgical discharges, we compared risk-adjusted LOS, in days, by race/ ethnicity and SES (median household income by patient ZIP code in quartiles), using generalized linear models controlling for demographic and clinical factors, and differences between hospitals and between diagnoses.White patients were on average older than both Black and Hispanic patients, had more chronic conditions, and had a higher inpatient mortality risk. In adjusted analyses, Black patients had a significantly longer LOS than White patients (0.25-day difference when discharged to home and 0.23-day difference when discharged to non-home destinations, both P<.001); there was no difference between Hispanic and White patients. Wealthier patients had a shorter LOS than poorer patients (0.16-day difference when discharged to home and 0.06-day difference when discharged to nonhome destinations, both P<.001). These differences by race/ethnicity reversed for Medicaid patients.Disparities in LOS exist based on a patient's race/ethnicity and SES. Black and poorer patients, but not Hispanic patients, have longer LOS compared to White and wealthier patients. In aggregate, these differences may be related to trust and implicit bias and have implications for use of LOS as a quality metric. Future research should examine the drivers of these disparities.

Health Care Needs in the Aftermath of Hurricane Maria in Puerto Rico: A Perspective from Federal Medical Shelter Manatí.

INTRODUCTION: On September 20, 2017, Hurricane Maria, a Category 4 hurricane, swept across Puerto Rico (PR), wreaking devastation to PR's power, water, and health care infrastructure. To address the imminent humanitarian crisis, the US government mobilized Federal Medical Shelters (FMS) to serve the needs of hurricane victims. This study's objective was to provide a description of the patients seeking emergency care at FMS and the changes in their needs over time. METHODS: This retrospective, cross-sectional study included all patients presenting to the FMS Manatí from October 6, two weeks after Hurricane Maria's landfall, to November 2, 2017. Categories were created to catalogue the nature of new acute medical issues by patients presenting to the Shelter. Descriptive, graphical analyses were performed to assess changes to presenting complaints over time, and by age groups defined as infant (age ≤1 years), child (1 year < age ≤10 years), adolescent (10 years < age ≤ 25 years), and adult (age > 25 years). RESULTS: Over the 30-day period, 5,268 patients were seen in the FMS seeking medical care (average 188.1 patients per day), spending less than five hours in the facility. The distribution of patients' age was bimodal: the first peak at one year and the second at age 50. The most common patient complaint was infection (38.8%), then musculoskeletal (MSK) complaints (11.8%) and management of chronic medical conditions (11.8%). The proportion of patients presenting with chronic disease complaints declined over the course of the period of observation (21.4% on Day 4 to 8.0% on Day 30) while the proportion of patients presenting with infection increased (31.0% on Day 4 to 48.6% on Day 30). Infection complaints were highest in all age groups, but most in infxants (80.2%), while MSK and chronic disease complaints were highest in adults (14.9% and 14.9%, respectively). CONCLUSION: Infection treatment and chronic disease management were important medical needs facing patients seeking care at FMS Manatí after Hurricane Maria. These findings suggest that basic needs related to sanitation and shelter remained important weeks after the hurricane, and a focus on access to medications, infection control, and injury prevention/management after a disaster needs to be prioritized during disaster response.

Synthesis and Biological Assessment of Pyrrolobenzoxazine Scaffold as a Potent Antioxidant.

Reduction of mitochondrial oxidative stress-mediated diseases is an important pharmaceutical objective in recent biomedical research. In this context, a series of novel pyrrolobenzoxazines (PyBs) framework with enormous diversity (compounds 5a-w) was synthesized by employing a low-temperature greener pathway, and antioxidant property of the synthesized compounds was successfully demonstrated on preclinical model goat heart mitochondria, in vitro. Copper-ascorbate (Cu-As) was utilized as an oxidative stress generator. Out of screened PyBs, the compound possessing -OH and -OMe groups on benzene nucleus along with pyrrolobenzoxazine core moiety (compound 5w) displayed magnificent antioxidant property with a minimum effective dose of 66 µM during the biochemical assessment. The ameliorative effect of synthesized pyrrolobenzoxazine moiety on levels of biomarkers of oxidative stress, antioxidant enzyme, activities of Krebs cycle and respiratory chain enzymes, mitochondrial morphology, and Ca2+ permeability of mitochondrial membrane was investigated in the presence of Cu-As. Furthermore, the binding mode of Cu-As by compound 5w was explored successfully using isothermal titration calorimetry (ITC) analysis.