Enrollment in High-Deductible Health Plans and Incident Diabetes Complications.

Importance: Preventing diabetes complications requires monitoring and control of hyperglycemia and cardiovascular risk factors. Switching to high-deductible health plans (HDHPs) has been shown to hinder aspects of diabetes care; however, the association of HDHP enrollment with microvascular and macrovascular diabetes complications is unknown. Objective: To examine the association between an employer-required switch to an HDHP and incident complications of diabetes. Design, Setting, and Participants: This retrospective cohort study used deidentified administrative claims data for US adults with diabetes enrolled in employer-sponsored health plans between January 1, 2010, and December 31, 2019. Data analysis was performed from May 26, 2022, to January 2, 2024. Exposures: Adults with a baseline year of non-HDHP enrollment who had to switch to an HDHP because their employer offered no non-HDHP alternative in that year were compared with adults who were continuously enrolled in a non-HDHP. Main Outcomes and Measures: Mixed-effects logistic regression models examined the association between switching to an HDHP and, individually, the odds of myocardial infarction, stroke, hospitalization for heart failure, lower-extremity complication, end-stage kidney disease, proliferative retinopathy, treatment for retinopathy, and blindness. Models were adjusted for demographics, comorbidities, and medications, with inverse propensity score weighting used to account for potential selection bias. Results: The study included 42 326 adults who switched to an HDHP (mean [SD] age, 52 [10] years; 19 752 [46.7%] female) and 202 729 adults who did not switch (mean [SD] age, 53 [10] years; 89 828 [44.3%] female). Those who switched to an HDHP had greater odds of experiencing all diabetes complications (odds ratio [OR], 1.11; 95% CI, 1.06-1.16 for myocardial infarction; OR, 1.15; 95% CI, 1.09-1.21 for stroke; OR, 1.35; 95% CI, 1.30-1.41 for hospitalization for heart failure; OR, 2.53; 95% CI, 2.38-2.70 for end-stage kidney disease; OR, 2.23; 95% CI, 2.17-2.29 for lower-extremity complication; OR, 1.17; 95% CI, 1.13-1.21 for proliferative retinopathy; OR, 2.35; 95% CI, 2.18-2.54 for blindness; and OR, 2.28; 95% CI, 2.15-2.41 for retinopathy treatment). Conclusions and Relevance: This study found that an employer-driven switch to an HDHP was associated with increased odds of experiencing all diabetes complications. These findings reinforce the potential harm associated with HDHPs for people with diabetes and the importance of affordable and accessible chronic disease management, which is hindered by high out-of-pocket costs incurred by HDHPs.

Disparities in Acute and Chronic Complications of Diabetes Along the U.S. Rural-Urban Continuum.

OBJECTIVE: To determine the relative hazards of acute and chronic diabetes complications among people with diabetes across the U.S. rural-urban continuum. RESEARCH DESIGN AND METHODS: This retrospective cohort study used the OptumLabs Data Warehouse, a deidentified data set of U.S. commercial and Medicare Advantage beneficiaries, to follow 2,901,563 adults (age ≥18 years) with diabetes between 1 January 2012 and 31 December 2021. We compared adjusted hazard ratios (HRs) of diabetes complications in remote areas (population <2,500), small towns (population 2,500-50,000), and cities (population >50,000). RESULTS: Compared with residents of cities, residents of remote areas had greater hazards of myocardial infarction (HR 1.06 [95% CI 1.02-1.10]) and revascularization (HR 1.04 [1.02-1.06]) but lower hazards of hyperglycemia (HR 0.90 [0.83-0.98]) and stroke (HR 0.91 [0.88-0.95]). Compared with cities, residents of small towns had greater hazards of hyperglycemia (HR 1.06 [1.02-1.10]), hypoglycemia (HR 1.15 [1.12-1.18]), end-stage kidney disease (HR 1.04 [1.03-1.06]), myocardial infarction (HR 1.10 [1.08-1.12]), heart failure (HR 1.05 [1.03-1.06]), amputation (HR 1.05 [1.02-1.09]), other lower-extremity complications (HR 1.02 [1.01-1.03]), and revascularization (HR 1.05 [1.04-1.06]) but a smaller hazard of stroke (HR 0.95 [0.94-0.97]). Compared with small towns, residents of remote areas had lower hazards of hyperglycemia (HR 0.85 [0.78-0.93]), hypoglycemia (HR 0.92 [0.87-0.97]), and heart failure (HR 0.94 [0.91-0.97]). Hazards of retinopathy and atrial fibrillation/flutter did not vary geographically. CONCLUSIONS: Adults in small towns are disproportionately impacted by complications of diabetes. Future studies should probe for the reasons underlying these disparities.

Healthy immigrant community study protocol: A randomized controlled trial of a social network intervention for cardiovascular risk reduction among Hispanic and Somali adults.

BACKGROUND: Immigrants to the United States face structural barriers that contribute to rising cardiovascular risk factors and obesity after immigration. This manuscript describes the development of the Healthy Immigrant Community protocol and baseline measures for a stepped wedge cluster randomized trial to test the effectiveness of a social network intervention for cardiovascular risk reduction among two immigrant populations. METHODS: We developed a social network-informed, community-based, participatory research-derived health promotion intervention with Hispanic and Somali immigrant communities in Minnesota consisting of mentoring, educational and motivational sessions, group activities, and a community toolkit for healthy weight loss delivered by culturally concordant health promoters (HPs) to their social networks. Using a stepped wedge cluster randomized design, social network-based groups were randomly assigned to receive the intervention either immediately or after a delay of one year. Outcomes, measured at baseline, 6 months, 12 months, and 24 months, were derived from the American Heart Association's "Life's Simple 7": BMI and waist circumference, blood pressure, fasting blood glucose, total cholesterol, physical activity level, and dietary quality. RESULTS: A total of 51 HPs were enrolled and randomized (29 Hispanic; 22 Somali). There were 475 participants enrolled in the study, representing a mean social network group size of 8 (range, 5-12). The mean BMI of the sample (32.2) was in the "obese" range. CONCLUSION: Processes and products from this Healthy Immigrant Community protocol are relevant to other communities seeking to reduce cardiovascular risk factors and negative health behaviors among immigrant populations by leveraging the influence of their social networks.

Measuring Equity in Readmission as a Distinct Assessment of Hospital Performance.

Importance: Equity is an essential domain of health care quality. The Centers for Medicare & Medicaid Services (CMS) developed 2 Disparity Methods that together assess equity in clinical outcomes. Objectives: To define a measure of equitable readmissions; identify hospitals with equitable readmissions by insurance (dual eligible vs non-dual eligible) or patient race (Black vs White); and compare hospitals with and without equitable readmissions by hospital characteristics and performance on accountability measures (quality, cost, and value). Design, Setting, and Participants: Cross-sectional study of US hospitals eligible for the CMS Hospital-Wide Readmission measure using Medicare data from July 2018 through June 2019. Main Outcomes and Measures: We created a definition of equitable readmissions using CMS Disparity Methods, which evaluate hospitals on 2 methods: outcomes for populations at risk for disparities (across-hospital method); and disparities in care within hospitals' patient populations (within-a-single-hospital method). Exposures: Hospital patient demographics; hospital characteristics; and 3 measures of hospital performance-quality, cost, and value (quality relative to cost). Results: Of 4638 hospitals, 74% served a sufficient number of dual-eligible patients, and 42% served a sufficient number of Black patients to apply CMS Disparity Methods by insurance and race. Of eligible hospitals, 17% had equitable readmission rates by insurance and 30% by race. Hospitals with equitable readmissions by insurance or race cared for a lower percentage of Black patients (insurance, 1.9% [IQR, 0.2%-8.8%] vs 3.3% [IQR, 0.7%-10.8%], P < .01; race, 7.6% [IQR, 3.2%-16.6%] vs 9.3% [IQR, 4.0%-19.0%], P = .01), and differed from nonequitable hospitals in multiple domains (teaching status, geography, size; P < .01). In examining equity by insurance, hospitals with low costs were more likely to have equitable readmissions (odds ratio, 1.57 [95% CI, 1.38-1.77), and there was no relationship between quality and value, and equity. In examining equity by race, hospitals with high overall quality were more likely to have equitable readmissions (odds ratio, 1.14 [95% CI, 1.03-1.26]), and there was no relationship between cost and value, and equity. Conclusion and Relevance: A minority of hospitals achieved equitable readmissions. Notably, hospitals with equitable readmissions were characteristically different from those without. For example, hospitals with equitable readmissions served fewer Black patients, reinforcing the role of structural racism in hospital-level inequities. Implementation of an equitable readmission measure must consider unequal distribution of at-risk patients among hospitals.

Impact of COVID-19 vaccination on symptoms and immune phenotypes in vaccine-naïve individuals with Long COVID.

Background: Long COVID contributes to the global burden of disease. Proposed root cause hypotheses include the persistence of SARS-CoV-2 viral reservoir, autoimmunity, and reactivation of latent herpesviruses. Patients have reported various changes in Long COVID symptoms after COVID-19 vaccinations, leaving uncertainty about whether vaccine-induced immune responses may alleviate or worsen disease pathology. Methods: In this prospective study, we evaluated changes in symptoms and immune responses after COVID-19 vaccination in 16 vaccine-naïve individuals with Long COVID. Surveys were administered before vaccination and then at 2, 6, and 12 weeks after receiving the first vaccine dose of the primary series. Simultaneously, SARS-CoV-2-reactive TCR enrichment, SARS-CoV-2-specific antibody responses, antibody responses to other viral and self-antigens, and circulating cytokines were quantified before vaccination and at 6 and 12 weeks after vaccination. Results: Self-report at 12 weeks post-vaccination indicated 10 out of 16 participants had improved health, 3 had no change, 1 had worse health, and 2 reported marginal changes. Significant elevation in SARS-CoV-2-specific TCRs and Spike protein-specific IgG were observed 6 and 12 weeks after vaccination. No changes in reactivities were observed against herpes viruses and self-antigens. Within this dataset, higher baseline sIL-6R was associated with symptom improvement, and the two top features associated with non-improvement were high IFN-ß and CNTF, among soluble analytes. Conclusions: Our study showed that in this small sample, vaccination improved the health or resulted in no change to the health of most participants, though few experienced worsening. Vaccination was associated with increased SARS-CoV-2 Spike protein-specific IgG and T cell expansion in most individuals with Long COVID. Symptom improvement was observed in those with baseline elevated sIL-6R, while elevated interferon and neuropeptide levels were associated with a lack of improvement.

Multilevel Implementation Strategies for Adolescent Human Papillomavirus Vaccine Uptake: A Cluster Randomized Clinical Trial.

Importance: Despite availability of a safe and effective vaccine, an estimated 36 500 new cancers in the US result from human papillomavirus (HPV) annually. HPV vaccine uptake falls short of national public health goals and lags other adolescent vaccines. Objective: To evaluate the individual and combined impact of 2 evidence-based interventions on HPV vaccination rates among 11- and 12-year-old children. Design, Setting, and Participants: The study team conducted a cluster randomized clinical trial with a stepped-wedge factorial design at 6 primary care practices affiliated with Mayo Clinic in southeastern Minnesota. Using block randomization to ensure balance of patient volumes across interventions, each practice was allocated to a sequence of four 12-month steps with the initial baseline step followed by 2 intermediate steps (none, 1, or both interventions) and a final step wherein all practices implemented both interventions. Each month, all eligible children who turned 11 or 12 years in the 2 months prior were identified and followed until the end of the step. Data were analyzed from April 2018 through March 2019. Participants included children who turned 11 or 12 years old and were due for a dose of the HPV vaccine. Interventions: Parents of eligible patients were mailed reminder/recalls following their child's birthdays. Health care professionals received confidential audit/feedback on their personal in-office success with HPV vaccine uptake via intra-campus mail. These 2 interventions were assessed separately and in combination. Main Outcomes and Measures: Eligible patients' receipt of any valid dose of HPV vaccine during the study step. Results: The cohort was comprised of 9242 11-year-olds (5165 [55.9%]) and 12-year-olds (4077 [44.1%]), and slightly more males (4848 [52.5%]). Parent reminder/recall resulted in 34.6% receiving a dose of HPV vaccine, health care professional audit/feedback, 30.4%, both interventions together resulted in 39.7%-all contrasted to usual care, 21.9%. Compared with usual care, the odds of HPV vaccination were higher for parent reminder/recall (odds ratio [OR], 1.56; 95% CI, 1.23-1.97) and for the combination of parent reminder/recall and health care professional audit/feedback (OR, 2.03; 95% CI, 1.44-2.85). Health care professional audit/feedback alone did not differ significantly from usual care (OR, 1.19; 95% CI, 0.94-1.51). Conclusions and Relevance: In this cluster randomized trial, the combination of parent reminder/recall and health care professional audit/feedback increased the odds of HPV vaccination compared with usual care. These findings underscore the value of simultaneous implementation of evidence-based strategies to improve HPV vaccination.

Why Are There So Few Women Medical School Deans? Debunking the Myth That Shorter Tenures Drive Disparities.

PURPOSE: Gender disparities among the senior echelons of academic medicine are striking and persistent. The role of medical school dean has been particularly immune to gender diversity, and limited prior research identified women's shorter decanal tenures as a potential driver. The authors assessed gender differences in tenure length of deanships in the current era to elucidate this finding. METHOD: From October 2020 to June 2021, the authors collected information about medical school deanships that were held from January 1, 2006, to June 30, 2020. All schools were members of the Association of American Medical Colleges (AAMC). The authors collected data from online public records and augmented their findings via direct outreach to medical schools. They used time-to-event analyses before and after adjustment for interim vs permanent status of the initial appointment, school ownership (public/private), and school size to assess for gender differences in length of deanship tenure during the study period. The unit of analysis was deanships, and the primary outcome was length of deanships measured in years. RESULTS: Authors included data on 528 deanships. Women held 91 (17%) of these terms. Men held the majority of permanent deanships (n = 352 [85%]). A greater percentage of the deanships held by women were interim only (n = 27 [30%]) compared with men (n = 85 [20%]). In unadjusted and adjusted analyses, there were no significant gender differences in length of deanship tenures. CONCLUSIONS: Analysis of appointments of AAMC-member medical school deans from 2006 to 2020 revealed that women have remained in their deanships as long as their male counterparts. The myth about women deans' shorter longevity should no longer be promulgated. Academic medicine should consider novel solutions to addressing women's persistent underrepresentation in the dean role, including employing the gender proportionality principle used in the business and legal communities.

Post-Vaccination Syndrome: A Descriptive Analysis of Reported Symptoms and Patient Experiences After Covid-19 Immunization.

Introduction: A chronic post-vaccination syndrome (PVS) after covid-19 vaccination has been reported but has yet to be well characterized. Methods: We included 241 individuals aged 18 and older who self-reported PVS after covid-19 vaccination and who joined the online Yale Listen to Immune, Symptom and Treatment Experiences Now (LISTEN) Study from May 2022 to July 2023. We summarized their demographics, health status, symptoms, treatments tried, and overall experience. Results: The median age of participants was 46 years (interquartile range [IQR]: 38 to 56), with 192 (80%) identifying as female, 209 (87%) as non-Hispanic White, and 211 (88%) from the United States. Among these participants with PVS, 127 (55%) had received the BNT162b2 [Pfizer-BioNTech] vaccine, and 86 (37%) received the mRNA-1273 [Moderna] vaccine. The median time from the day of index vaccination to symptom onset was three days (IQR: 1 day to 8 days). The time from vaccination to symptom survey completion was 595 days (IQR: 417 to 661 days). The median Euro-QoL visual analogue scale score was 50 (IQR: 39 to 70). The five most common symptoms were exercise intolerance (71%), excessive fatigue (69%), numbness (63%), brain fog (63%), and neuropathy (63%). In the week before survey completion, participants reported feeling unease (93%), fearfulness (82%), and overwhelmed by worries (81%), as well as feelings of helplessness (80%), anxiety (76%), depression (76%), hopelessness (72%), and worthlessness (49%) at least once. Participants reported a median of 20 (IQR: 13 to 30) interventions to treat their condition. Conclusions: In this study, individuals who reported PVS after covid-19 vaccination had low health status, high symptom burden, and high psychosocial stress despite trying many treatments. There is a need for continued investigation to understand and treat this condition.

Uncovering heterogeneous cardiometabolic risk profiles in US adults: the role of social and behavioral determinants of health.

INTRODUCTION: Social and behavioral determinants of health (SBDH) have been linked to diabetes risk, but their role in explaining variations in cardiometabolic risk across race/ethnicity in US adults is unclear. This study aimed to classify adults into distinct cardiometabolic risk subgroups using SBDH and clinically measured metabolic risk factors, while comparing their associations with undiagnosed diabetes and pre-diabetes by race/ethnicity. RESEARCH DESIGN AND METHODS: We analyzed data from 38,476 US adults without prior diabetes diagnosis from the National Health and Nutrition Examination Survey (NHANES) 1999-2018. The k-prototypes clustering algorithm was used to identify subgroups based on 16 SBDH and 13 metabolic risk factors. Each participant was classified as having no diabetes, pre-diabetes or undiagnosed diabetes using contemporaneous laboratory data. Logistic regression was used to assess associations between subgroups and diabetes status, focusing on differences by race/ethnicity. RESULTS: Three subgroups were identified: cluster 1, primarily middle-aged adults with high rates of smoking, alcohol use, short sleep duration, and low diet quality; cluster 2, mostly young non-white adults with low income, low health insurance coverage, and limited healthcare access; and cluster 3, mostly older males who were the least physically active, but with high insurance coverage and healthcare access. Compared with cluster 2, adjusted ORs (95% CI) for undiagnosed diabetes were 14.9 (10.9, 20.2) in cluster 3 and 3.7 (2.8, 4.8) in cluster 1. Clusters 1 and 3 (vs cluster 2) had high odds of pre-diabetes, with ORs of 1.8 (1.6, 1.9) and 2.1 (1.8, 2.4), respectively. Race/ethnicity was found to modify the relationship between identified subgroups and pre-diabetes risk. CONCLUSIONS: Self-reported SBDH combined with metabolic factors can be used to classify adults into subgroups with distinct cardiometabolic risk profiles. This approach may help identify individuals who would benefit from screening for diabetes and pre-diabetes and potentially suggest effective prevention strategies.

Assessing the use of observational methods and real-world data to emulate ongoing randomized controlled trials.

BACKGROUND/AIMS: There has been growing interest in better understanding the potential of observational research methods in medical product evaluation and regulatory decision-making. Previously, we used linked claims and electronic health record data to emulate two ongoing randomized controlled trials, characterizing the populations and results of each randomized controlled trial prior to publication of its results. Here, our objective was to compare the populations and results from the emulated trials with those of the now-published randomized controlled trials. METHODS: This study compared participants' demographic and clinical characteristics and study results between the emulated trials, which used structured data from OptumLabs Data Warehouse, and the published PRONOUNCE and GRADE trials. First, we examined the feasibility of implementing the baseline participant characteristics included in the published PRONOUNCE and GRADE trials' using real-world data and classified each variable as ascertainable, partially ascertainable, or not ascertainable. Second, we compared the emulated trials and published randomized controlled trials for baseline patient characteristics (concordance determined using standardized mean differences <0.20) and results of the primary and secondary endpoints (concordance determined by direction of effect estimates and statistical significance). RESULTS: The PRONOUNCE trial enrolled 544 participants, and the emulated trial included 2226 propensity score-matched participants. In the PRONOUNCE trial publication, one of the 32 baseline participant characteristics was listed as an exclusion criterion on ClinicalTrials.gov but was ultimately not used. Among the remaining 31 characteristics, 9 (29.0%) were ascertainable, 11 (35.5%) were partially ascertainable, and 10 (32.2%) were not ascertainable using structured data from OptumLabs. For one additional variable, the PRONOUNCE trial did not provide sufficient detail to allow its ascertainment. Of the nine variables that were ascertainable, values in the emulated trial and published randomized controlled trial were discordant for 6 (66.7%). The primary endpoint of time from randomization to the first major adverse cardiovascular event and secondary endpoints of nonfatal myocardial infarction and stroke were concordant between the emulated trial and published randomized controlled trial. The GRADE trial enrolled 5047 participants, and the emulated trial included 7540 participants. In the GRADE trial publication, 8 of 34 (23.5%) baseline participant characteristics were ascertainable, 14 (41.2%) were partially ascertainable, and 11 (32.4%) were not ascertainable using structured data from OptumLabs. For one variable, the GRADE trial did not provide sufficient detail to allow for ascertainment. Of the eight variables that were ascertainable, values in the emulated trial and published randomized controlled trial were discordant for 4 (50.0%). The primary endpoint of time to hemoglobin A1c ≥7.0% was mostly concordant between the emulated trial and the published randomized controlled trial. CONCLUSION: Despite challenges, observational methods and real-world data can be leveraged in certain important situations for a more timely evaluation of drug effectiveness and safety in more diverse and representative patient populations.

Comparative effectiveness of second line glucose lowering drug treatments using real world data: emulation of a target trial.

Objective: To build on the recently completed GRADE (Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study) randomised trial examining the comparative effectiveness of second line glucose lowering drugs in achieving and maintaining glycaemic control in adults with type 2 diabetes. Design: Emulation of a target trial. Setting: Medical and pharmacy claims data from the OptumLabs Data Warehouse, a de-identified US national dataset of beneficiaries of commercially insured and Medicare Advantage plans, 29 March 2013 to 30 June 2021. Participants: Adults (≥18 years) with type 2 diabetes who first started taking glimepiride, sitagliptin, liraglutide, insulin glargine, or canagliflozin between 29 March 2013 and 30 June 2021. Participants were treatment naive or were receiving metformin monotherapy at the time of starting the study drug. Main outcome measures: The main outcomes were time to primary and secondary metabolic failure of the assigned treatment, calculated as days to haemoglobin A1c levels of ≥7.0% and >7.5%, respectively. Secondary metabolic, cardiovascular, and microvascular outcomes were analysed as specified in the GRADE statistical analysis plan. Propensity scores were estimated with the gradient boosting method, and inverse propensity score weighting was used to emulate randomisation to the treatment groups, which were then compared with Cox proportional hazards regression. Results: The study cohort included participants starting treatment with glimepiride (n=20 511), liraglutide (n=5569), sitagliptin (n=13 039), insulin glargine (n=7262), and canagliflozin (n=5290). The insulin glargine arm was excluded because of insufficient control of confounding. Median times to primary metabolic failure were 439 (95% confidence interval 400 to 489) days in the canagliflozin arm, 439 (426 to 453) days in the glimepiride arm, 624 (567 to 731) days in the liraglutide arm, and 461 (442 to 482) days in the sitagliptin arm. Median time to secondary metabolic failure was also longest in the liraglutide arm. Adults receiving liraglutide had the lowest one year cumulative incidence rate of primary metabolic failure (0.37, 95% confidence interval 0.35 to 0.40) followed by sitagliptin (0.44, 0.43 to 0.45), glimepiride (0.45, 0.44 to 0.45), and canagliflozin (0.46, 0.44 to 0.48). Similarly, the one year cumulative incidence rate of secondary metabolic failure was 0.27 (0.25 to 0.29) in the canagliflozin arm, 0.28 (0.27 to 0.29) in the glimepiride arm, 0.23 (0.21 to 0.26) in the liraglutide arm, and 0.28 (0.27 to 0.29) in the sitagliptin arm. No differences were observed between the study arms in the rates of microvascular and macrovascular complications. Conclusions: In this target trial emulation of an expanded GRADE study framework, liraglutide was more effective in achieving and maintaining glycaemic control as a second line glucose lowering drug than canagliflozin, sitagliptin, or glimepiride.

Association of Population Well-Being With Cardiovascular Outcomes.

Importance: Mortality from cardiovascular disease (CVD) varies across communities and is associated with known structural and population health factors. Still, a population's well-being, including sense of purpose, social relationships, financial security, and relationship to community, may be an important target to improve cardiovascular health. Objective: To examine the association of population level measures of well-being with rates of CVD mortality in the US. Design, Setting, and Participants: This cross-sectional study linked data from the Gallup National Health and Well-Being Index (WBI) survey to county-level rates of CVD mortality from the Centers for Disease Control and Prevention Atlas of Heart Disease and Stroke. Participants were respondents of the WBI survey, which was conducted by Gallup with randomly selected adults aged 18 years or older from 2015 to 2017. Data were analyzed from August 2022 to May 2023. Main Outcomes and Measures: The primary outcome was the county-level rate of total CVD mortality; secondary outcomes were mortality rates for stroke, heart failure, coronary heart disease, acute myocardial infarction, and total heart disease. The association of population well-being (measured using a modified version of the WBI) with CVD mortality was assessed, and an analysis of whether the association was modified by county structural factors (Area Deprivation Index [ADI], income inequality, and urbanicity) and population health factors (percentages of the adult population who had hypertension, diabetes, or obesity; were currently smoking; and were physically inactive) was conducted. Population WBI and its ability to mediate the association of structural factors associated with CVD using structural equation models was also assessed. Results: Well-being surveys were completed by 514 971 individuals (mean [SD] age 54.0 [19.2] years; 251 691 [48.9%] women; 379 521 [76.0%] White respondents) living in 3228 counties. Mortality rates for CVD decreased from a mean of 499.7 (range, 174.2-974.7) deaths per 100 000 persons in counties with the lowest quintile of population well-being to 438.6 (range, 110.1-850.4) deaths per 100 000 persons in counties with the highest quintile of population well-being. Secondary outcomes showed similar patterns. In the unadjusted model, the effect size (SE) of WBI on CVD mortality was -15.5 (1.5; P < .001), or a decrease of 15 deaths per 100 000 persons for each 1-point increase of population well-being. After adjusting for structural factors and structural plus population health factors, the association was attenuated but still significant, with an effect size (SE) of -7.3 (1.6; P < .001); for each 1-point increase in well-being, the total cardiovascular death rate decreased by 7.3 deaths per 100 000 persons. Secondary outcomes showed similar patterns, with mortality due to coronary heart disease and heart failure being significant in fully adjusted models. In mediation analyses, associations of income inequality and ADI with CVD mortality were all partly mediated by the modified population WBI. Conclusions and Relevance: In this cross-sectional study assessing the association of well-being and cardiovascular outcomes, higher well-being, a measurable, modifiable, and meaningful outcome, was associated with lower CVD mortality, even after controlling for structural and cardiovascular-related population health factors, indicating that well-being may be a focus for advancing cardiovascular health.

Evaluating the feasibility of a multicenter teleneonatology clinical effectiveness trial.

BACKGROUND: Our research consortium is preparing for a prospective multicenter trial evaluating the impact of teleneonatology on the health outcomes of at-risk neonates born in community hospitals. We completed a 6-month pilot study to determine the feasibility of the trial protocol. METHODS: Four neonatal intensive care units ("hubs") and four community hospitals ("spokes") participated in the pilot-forming four hub-spoke dyads. Two hub-spoke dyads implemented synchronous, audio-video telemedicine consultations with a neonatologist ("teleneonatology"). The primary outcome was a composite feasibility score that included one point for each of the following: site retention, on-time screening log completion, no eligibility errors, on-time data submission, and sponsor site-dyad meeting attendance (score range 0-5). RESULTS: For the 20 hub-spoke dyad months, the mean (range) composite feasibility score was 4.6 (4, 5). All sites were retained during the pilot. Ninety percent (18/20) of screening logs were completed on time. The eligibility error rate was 0.2% (3/1809). On-time data submission rate was 88.4% (84/95 case report forms). Eighty-five percent (17/20) of sponsor site-dyad meetings were attended by both hub and spoke site staff. CONCLUSIONS: A multicenter teleneonatology clinical effectiveness trial is feasible. Learnings from the pilot study may improve the likelihood of success of the main trial. IMPACT: A prospective, multicenter clinical trial evaluating the impact of teleneonatology on the early health outcomes of at-risk neonates born in community hospitals is feasible. A multidimensional composite feasibility score, which includes processes and procedures fundamental to completing a clinical trial, is useful for quantitatively measuring pilot study success. A pilot study allows the investigative team to test trial methods and materials to identify what works well or requires modification. Learnings from a pilot study may improve the quality and efficiency of the main effectiveness trial.

Excess Mortality and Years of Potential Life Lost Among the Black Population in the US, 1999-2020.

Importance: Amid efforts in the US to promote health equity, there is a need to assess recent progress in reducing excess deaths and years of potential life lost among the Black population compared with the White population. Objective: To evaluate trends in excess mortality and years of potential life lost among the Black population compared with the White population. Design, setting, and participants: Serial cross-sectional study using US national data from the Centers for Disease Control and Prevention from 1999 through 2020. We included data from non-Hispanic White and non-Hispanic Black populations across all age groups. Exposures: Race as documented in the death certificates. Main outcomes and measures: Excess age-adjusted all-cause mortality, cause-specific mortality, age-specific mortality, and years of potential life lost rates (per 100 000 individuals) among the Black population compared with the White population. Results: From 1999 to 2011, the age-adjusted excess mortality rate declined from 404 to 211 excess deaths per 100 000 individuals among Black males (P for trend <.001). However, the rate plateaued from 2011 through 2019 (P for trend = .98) and increased in 2020 to 395-rates not seen since 2000. Among Black females, the rate declined from 224 excess deaths per 100 000 individuals in 1999 to 87 in 2015 (P for trend <.001). There was no significant change between 2016 and 2019 (P for trend = .71) and in 2020 rates increased to 192-levels not seen since 2005. The trends in rates of excess years of potential life lost followed a similar pattern. From 1999 to 2020, the disproportionately higher mortality rates in Black males and females resulted in 997 623 and 628 464 excess deaths, respectively, representing a loss of more than 80 million years of life. Heart disease had the highest excess mortality rates, and the excess years of potential life lost rates were largest among infants and middle-aged adults. Conclusions and relevance: Over a recent 22-year period, the Black population in the US experienced more than 1.63 million excess deaths and more than 80 million excess years of life lost when compared with the White population. After a period of progress in reducing disparities, improvements stalled, and differences between the Black population and the White population worsened in 2020.

Nonexercise machine learning models for maximal oxygen uptake prediction in national population surveys.

OBJECTIVE: Nonexercise algorithms are cost-effective methods to estimate cardiorespiratory fitness (CRF), but the existing models have limitations in generalizability and predictive power. This study aims to improve the nonexercise algorithms using machine learning (ML) methods and data from US national population surveys. MATERIALS AND METHODS: We used the 1999-2004 data from the National Health and Nutrition Examination Survey (NHANES). Maximal oxygen uptake (VO2 max), measured through a submaximal exercise test, served as the gold standard measure for CRF in this study. We applied multiple ML algorithms to build 2 models: a parsimonious model using commonly available interview and examination data, and an extended model additionally incorporating variables from Dual-Energy X-ray Absorptiometry (DEXA) and standard laboratory tests in clinical practice. Key predictors were identified using Shapley additive explanation (SHAP). RESULTS: Among the 5668 NHANES participants in the study population, 49.9% were women and the mean (SD) age was 32.5 years (10.0). The light gradient boosting machine (LightGBM) had the best performance across multiple types of supervised ML algorithms. Compared with the best existing nonexercise algorithms that could be applied to the NHANES, the parsimonious LightGBM model (RMSE: 8.51 ml/kg/min [95% CI: 7.73-9.33]) and the extended LightGBM model (RMSE: 8.26 ml/kg/min [95% CI: 7.44-9.09]) significantly reduced the error by 15% and 12% (P < .001 for both), respectively. DISCUSSION: The integration of ML and national data source presents a novel approach for estimating cardiovascular fitness. This method provides valuable insights for cardiovascular disease risk classification and clinical decision-making, ultimately leading to improved health outcomes. CONCLUSION: Our nonexercise models provide improved accuracy in estimating VO2 max within NHANES data as compared to existing nonexercise algorithms.

Adjustment for Social Risk Factors in a Measure of Clinician Quality Assessing Acute Admissions for Patients With Multiple Chronic Conditions.

Importance: Adjusting quality measures used in pay-for-performance programs for social risk factors remains controversial. Objective: To illustrate a structured, transparent approach to decision-making about adjustment for social risk factors for a measure of clinician quality that assesses acute admissions for patients with multiple chronic conditions (MCCs). Design, Setting, and Participants: This retrospective cohort study used 2017 and 2018 Medicare administrative claims and enrollment data, 2013 to 2017 American Community Survey data, and 2018 and 2019 Area Health Resource Files. Patients were Medicare fee-for-service beneficiaries 65 years or older with at least 2 of 9 chronic conditions (acute myocardial infarction, Alzheimer disease/dementia, atrial fibrillation, chronic kidney disease, chronic obstructive pulmonary disease or asthma, depression, diabetes, heart failure, and stroke/transient ischemic attack). Patients were attributed to clinicians in the Merit-Based Incentive Payment System (MIPS; primary health care professionals or specialists) using a visit-based attribution algorithm. Analyses were conducted between September 30, 2017, and August 30, 2020. Exposures: Social risk factors included low Agency for Healthcare Research and Quality Socioeconomic Status Index, low physician-specialist density, and Medicare-Medicaid dual eligibility. Main Outcomes and Measures: Number of acute unplanned hospital admissions per 100 person-years at risk for admission. Measure scores were calculated for MIPS clinicians with at least 18 patients with MCCs assigned to them. Results: There were 4 659 922 patients with MCCs (mean [SD] age, 79.0 [8.0] years; 42.5% male) assigned to 58 435 MIPS clinicians. The median (IQR) risk-standardized measure score was 38.9 (34.9-43.6) per 100 person-years. Social risk factors of low Agency for Healthcare Research and Quality Socioeconomic Status Index, low physician-specialist density, and Medicare-Medicaid dual eligibility were significantly associated with the risk of hospitalization in the univariate models (relative risk [RR], 1.14 [95% CI, 1.13-1.14], RR, 1.05 [95% CI, 1.04-1.06], and RR, 1.44 [95% CI, 1.43-1.45], respectively), but the association was attenuated in adjusted models (RR, 1.11 [95% CI 1.11-1.12] for dual eligibility). Across MIPS clinicians caring for variable proportions of dual-eligible patients with MCCs (quartile 1, 0%-3.1%; quartile 2, >3.1%-9.5%; quartile 3, >9.5%-24.5%, and quartile 4, >24.5%-100%), median measure scores per quartile were 37.4, 38.6, 40.0, and 39.8 per 100 person-years, respectively. Balancing conceptual considerations, empirical findings, programmatic structure, and stakeholder input, the Centers for Medicare & Medicaid Services decided to adjust the final model for the 2 area-level social risk factors but not dual Medicare-Medicaid eligibility. Conclusions and Relevance: This cohort study demonstrated that adjustment for social risk factors in outcome measures requires weighing high-stake, competing concerns. A structured approach that includes evaluation of conceptual and contextual factors, as well as empirical findings, with active engagement of stakeholders can be used to make decisions about social risk factor adjustment.

Using real-world data from health systems to evaluate the safety and effectiveness of a catheter to treat ischemic ventricular tachycardia.

BACKGROUND: The ThermoCool STSF catheter is used for ablation of ischemic ventricular tachycardia (VT) in routine clinical practice, although outcomes have not been studied and the catheter does not have Food and Drug Administration (FDA) approval for this indication. We used real-world health system data to evaluate its safety and effectiveness for this indication. METHODS: Among patients undergoing ischemic VT ablation with the ThermoCool STSF catheter pooled across two health systems (Mercy Health and Mayo Clinic), the primary safety composite outcome of death, thromboembolic events, and procedural complications within 7 days was compared to a performance goal of 15%, which is twice the expected proportion of the primary composite safety outcome based on prior studies. The exploratory effectiveness outcome of rehospitalization for VT or heart failure or repeat VT ablation at up to 1 year was averaged across health systems among patients treated with the ThermoCool STSF vs. ST catheters. RESULTS: Seventy total patients received ablation for ischemic VT using the ThermoCool STSF catheter. The primary safety composite outcome occurred in 3/70 (4.3%; 90% CI, 1.2-10.7%) patients, meeting the pre-specified performance goal, p = 0.0045. At 1 year, the effectiveness outcome risk difference (STSF-ST) at Mercy was - 0.4% (90% CI: - 25.2%, 24.3%) and at Mayo Clinic was 12.6% (90% CI: - 13.0%, 38.4%); the average risk difference across both institutions was 5.8% (90% CI: - 12.0, 23.7). CONCLUSIONS: The ThermoCool STSF catheter was safe and appeared effective for ischemic VT ablation, supporting continued use of the catheter and informing possible FDA label expansion. Health system data hold promise for real-world safety and effectiveness evaluation of cardiovascular devices.

Prevalence, Severity, and Co-Occurrence of SPPADE Symptoms in 31,866 Patients With Cancer.

OBJECTIVES: To examine the prevalence, severity, and co-occurrence of SPPADE symptoms as well as their association with cancer type and patient characteristics. BACKGROUND: The SPPADE symptoms (sleep disturbance, pain, physical function impairment, anxiety, depression, and low energy /fatigue) are prevalent, co-occurring, and undertreated in oncology and other clinical populations. METHODS: Baseline SPPADE symptom data were analyzed from the E2C2 study, a stepped wedge pragmatic, population-level, cluster randomized clinical trial designed to evaluate a guideline-informed symptom management model targeting the six SPPADE symptoms. Symptom prevalence and severity were measured with a 0-10 numeric rating (NRS) scale for each of the six symptoms. Prevalence of severe (NRS ≥ 7) and potential clinically relevant (NRS ≥ 5) symptoms as well as co-occurrence of clinical symptoms were determined. Distribution-based methods were used to estimate the minimally important difference (MID). Associations of cancer type and patient characteristics with a SPPADE composite score were analyzed. RESULTS: A total of 31,886 patients were assessed for SPPADE symptoms prior to, during, or soon after an outpatient medical oncology encounter. The proportion of patients with a potential clinically relevant symptom ranged from 17.5% for depression to 33.4% for fatigue. Co-occurrence of symptoms was high, with the proportion of patients with three or more additional clinically relevant symptoms ranging from 45.2% for fatigue to 68.6% for depression. The summed SPPADE composite score demonstrated good internal reliability (Cronbach's alpha of 0.86), with preliminary MID estimates of 4.1-4.3. Symptom burden differed across several types of cancer but was generally similar across most sociodemographic characteristics. CONCLUSION: The high prevalence and co-occurrence of SPPADE symptoms in patients with all types of cancer warrants clinical approaches that optimize detection and management.

Evaluation of High-Deductible Health Plans and Acute Glycemic Complications Among Adults With Diabetes.

Importance: Optimal diabetes care requires regular monitoring and care to maintain glycemic control. How high-deductible health plans (HDHPs), which reduce overall spending but may impede care by increasing out-of-pocket expenses, are associated with risks of severe hypoglycemia and hyperglycemia is unknown. Objective: To examine the association between an employer-forced switch to HDHP and severe hypoglycemia and hyperglycemia. Design, Setting, and Participants: This retrospective cohort study used deidentified administrative claims data for privately insured adults with diabetes from a single insurance carrier with multiple plans across the US between January 1, 2010, and December 31, 2018. Analyses were conducted between May 15, 2020, and November 3, 2022. Exposures: Patients with 1 baseline year of enrollment in a non-HDHP whose employers subsequently forced a switch to an HDHP were compared with patients who did not switch. Main Outcomes and Measures: Mixed-effects logistic regression models were used to examine the association between switching to an HDHP and the odds of severe hypoglycemia and hyperglycemia (ascertained using diagnosis codes in emergency department [ED] visits and hospitalizations), adjusting for patient age, sex, race and ethnicity, region, income, comorbidities, glucose-lowering medications, baseline ED and hospital visits for hypoglycemia and hyperglycemia, and baseline deductible amount, and applying inverse propensity score weighting to account for potential treatment selection bias. Results: The study population was composed of 42 326 patients who switched to an HDHP (mean [SD] age: 52 [10] years, 19 752 [46.7%] women, 7375 [17.4%] Black, 5740 [13.6%] Hispanic, 26 572 [62.8%] non-Hispanic White) and 202 729 patients who did not switch (mean [SD] age, 53 [10] years, 89 828 [44.3%] women, 29 551 [14.6%] Black, 26 689 [13.2%] Hispanic, 130 843 [64.5%] non-Hispanic White). When comparing all study years, switching to an HDHP was not associated with increased odds of experiencing at least 1 hypoglycemia-related ED visit or hospitalization (OR, 1.01 [95% CI, 0.95-1.06]; P = .85), but each year of HDHP enrollment did increase these odds by 2% (OR, 1.02 [95% CI, 1.00-1.04]; P = .04). In contrast, switching to an HDHP did significantly increase the odds of experiencing at least 1 hyperglycemia-related ED visit or hospitalization (OR, 1.25 [95% CI, 1.11-1.42]; P < .001), with each year of HDHP enrollment increasing the odds by 5% (OR, 1.05 [95% CI, 1.01-1.09]; P = .02). Conclusions and Relevance: In this cohort study, employer-forced switching to an HDHP was associated with increased odds of potentially preventable acute diabetes complications, potentially because of delayed or deferred care. These findings suggest that employers should be more judicious in their health plan offerings, and health plans and policy makers should consider allowing preventive and high-value services to be exempt from deductible requirements.

All-cause mortality after hypoglycemic and hyperglycemic emergencies among U.S. adults with diabetes, 2011-2020.

Estimated all-cause mortality within 30-days of hypoglycemic emergencies is 0.8 % in adults with type 1 diabetes and 1.7 % with type 2 diabetes; and within 30-days of hyperglycemic emergencies, it is 1.2 % with type 1 diabetes and 2.8 % with type 2 diabetes. These rates changed little between 2011 and 2020.