Shared Decision-Making Communication and Prognostic Misunderstanding in the ICU.

Importance: Surrogate misunderstanding of patient survival prognosis in the intensive care unit (ICU) is associated with poor patient and surrogate outcomes. Shared decision-making (SDM) may reduce misunderstanding. Objective: To evaluate the association between SDM-aligned communication and prognostic misunderstanding. Design, Setting, and Participants: This retrospective cohort study was conducted at 13 medical and surgical ICUs at 5 hospitals in North Carolina, Pennsylvania, and Washington between December 2012 and January 2017. Participants were surrogates of adult patients receiving prolonged mechanical ventilation and ICU physicians. Analysis was performed May to November 2023. Exposure: SDM-aligned communication during ICU family meetings, defined as the presence of high-quality serious illness communication behaviors aligned with SDM principles. Main Outcomes and Measures: The primary outcome was postmeeting surrogate prognostic misunderstanding, defined as the absolute difference between the physician's estimate of survival prognosis and the surrogate's perception of that estimate (range, 0-100 percentage points). The secondary outcome was postmeeting physician misunderstanding, defined as the absolute difference between a surrogate's estimate of survival prognosis and the physician's perception of that estimate (range, 0-100 percentage points). Prognostic misunderstanding of 20 percentage points or greater was considered clinically significant as in prior work. Results: Of 137 surrogates, most were female (102 [74.5%]), and there were 22 (16.1%) Black surrogates, 107 (78.1%) White surrogates, and 8 surrogates (5.8%) with other race and ethnicity. Of 100 physicians, most were male (64 [64.0%]), with 11 (11.0%) Asian physicians, 4 (4.0%) Black physicians, and 75 (75.0%) White physicians. Median (IQR) surrogate prognostic misunderstanding declined significantly after family meetings (before: 22.0 [10.0 to 40.0] percentage points; after: 15.0 [5.0 to 34.0] percentage points; P = .002), but there was no significant change in median (IQR) physician prognostic misunderstanding (before: 12.0 [5.0 to 30.0] percentage points; after: 15.0 [5.0 to 29.0] percentage points; P = .99). In adjusted analyses, SDM-aligned communication was not associated with prognostic misunderstanding among surrogates or physicians (surrogates: ß = -0.74; 95% CI, -1.81 to 0.32; P = .17; physicians: ß = -0.51; 95% CI, -1.63 to 0.62; P = .38). In a prespecified subgroup analysis of 78 surrogates (56.9%) with clinically significant premeeting prognostic misunderstanding, SDM-aligned communication was associated with reduced surrogate postmeeting prognostic misunderstanding (ß = -1.71; 95% CI, -3.09 to -0.34; P = .01). Conclusions and Relevance: In this retrospective cohort study, SDM-aligned communication was not associated with changes in prognostic misunderstanding for all surrogates or physicians, but it was associated with reduced prognostic misunderstanding among surrogates with clinically significant misunderstanding at baseline.

Analyzing missingness patterns in real-world data using the SMDI toolkit: application to a linked EHR-claims pharmacoepidemiology study.

BACKGROUND: Missing data in confounding variables present a frequent challenge in generating evidence using real-world data, including electronic health records (EHR). Our objective was to apply a recently published toolkit for characterizing missing data patterns and based on the toolkit results about likely missingness mechanisms, illustrate the decision-making process for analyses in an empirical case example. METHODS: We utilized the Structural Missing Data Investigations (SMDI) toolkit to characterize missing data patterns in the context of a pharmacoepidemiology study comparing cardiovascular outcomes of initiating sodium-glucose-cotransporter-2 inhibitors (SGLT2i) and dipeptidyl peptidase-4 inhibitors (DPP-4i) among older adults. The study used a linked EHR-Medicare claims dataset from Duke Health patients (2015-2017), focusing on partially observed confounders from EHR data (HbA1c lab and body mass index [BMI] values). Our analysis incorporated SMDI's descriptive functions and diagnostic tests to explore missingness patterns and determine missingness mitigation approaches. We used findings from these investigations to inform estimation of adjusted hazard ratios comparing the two classes of medications. RESULTS: High levels of missingness were noted for important confounding variables including HbA1c (63.6%) and BMI (16.5%). Diagnostic tests resulted in output that described: 1) the distributions of patient characteristics, exposure, and outcome between patients with or without an observed value of the partially observed covariate, 2) the ability to predict missingness based on observed covariates, and 3) estimate if the missingness of a partially observed covariate is differential with respect to the outcome. There was evidence that missingness could be sufficiently described using observed data, which allowed multiple imputation by chained equations using random forests to address missing confounder data in estimating treatment effects. Multiple imputation resulted in improved alignment of effect estimates with previous studies. CONCLUSIONS: We were able to demonstrate the practical application of the SMDI toolkit in a real-world setting. Application of the SMDI toolkit and the resulting insights of potential missingness patterns can inform the choice of appropriate analytic methods and increase transparency of research methods in handling missing data. This type of approach can inform analytic decision making and may increase our ability to generate evidence from real-world data.

Neighborhood Socioeconomic Disadvantage and 30-Day Outcomes for Common Cardiovascular Conditions.

BACKGROUND: Understanding the relationship between neighborhood environment and cardiovascular outcomes is important to achieve health equity and implement effective quality strategies. We conducted a population-based cohort study to determine the association of neighborhood socioeconomic deprivation and 30-day mortality and readmission rate for patients admitted with common cardiovascular conditions. METHODS AND RESULTS: We examined claims data from fee-for-service Medicare beneficiaries aged ≥65 years between 2017 and 2019 admitted for heart failure, valvular heart disease, ischemic heart disease, or cardiac arrhythmias. The primary exposure was the Area Deprivation Index; outcomes were 30-day all-cause death and unplanned readmission. More than 2 million admissions were included. After sequential adjustment for patient characteristics (demographics, dual eligibility, comorbidities), area health care resources (primary care clinicians, specialists, and hospital beds per capita), and admitting hospital characteristics (ownership, size, teaching status), there was a dose-dependent association between neighborhood socioeconomic deprivation and 30-day mortality rate for all conditions. In the fully adjusted model for death, estimated effect sizes of residence in the most disadvantaged versus least disadvantaged neighborhoods ranged from adjusted odds ratio 1.29 (95% CI, 1.22-1.36) for the heart failure group to adjusted odds ratio 1.63 (95% CI, 1.36-1.95) for the valvular heart disease group. Neighborhood deprivation was associated with increased adjusted 30-day readmission rates, with estimated effect sizes from adjusted odds ratio 1.09 (95% CI, 1.05-1.14) for heart failure to adjusted odds ratio 1.19 (95% CI, 1.13-1.26) for arrhythmia. CONCLUSIONS: Neighborhood socioeconomic disadvantage was associated with 30-day mortality rate and readmission for patients admitted with common cardiovascular conditions independent of individual demographics, socioeconomic status, medical risk, care access, or admitting hospital characteristics.

The Effect of Social Drivers of Health on 90-Day Readmission Rates and Costs After Primary Total Hip and Total Knee Arthroplasty.

INTRODUCTION: The effect of social drivers of health (SDOH) on readmissions and costs after total hip arthroplasty (THA) and total knee arthroplasty (TKA) is poorly understood. Policies such as the Hospital Readmissions Reduction Program have targeted overall readmission reduction, using value-based strategies to improve healthcare quality. However, the implications of SDOH on these outcomes are not yet understood. We hypothesized that the area deprivation index (ADI) as a surrogate for SDOH would markedly influence readmission rates and healthcare costs in the 90-day postprocedural period for THA and TKA. METHODS: We used the 100% US fee-for-service Medicare claims data from 2019 to 2021. Patients were identified using diagnosis-related groups. Our primary outcomes included 90-day unplanned readmission after hospital discharge and cost of care, treated as "high cost" if > 1 standard deviation above the mean. The relationships between ADI and primary outcomes were estimated with logistic regression models. RESULTS: A total of 628,399 patients were included in this study. The mean age of patients was 75.6, 64% were female, and 7.8% were dually eligible for Medicaid. After full covariate adjustment, readmission was higher for patients in more deprived areas (high Area Deprivation Index (ADI)) (low socioeconomic status (SES) group OR: 1.30 [95% confidence intervals 1.23, 1.38]). ADI was associated with high cost before adjustment (low SES group odds ratio 1.08 [95% confidence intervals 1.04, 1.11], P < 0.001), although, after adjustment, this association was lost. DISCUSSION: This analysis highlights the effect of SDOH on readmission rates after THA and TKA. A nuanced understanding of neighborhood-level disparities may facilitate targeted strategies to reduce avoidable readmissions in orthopaedic surgery. Regarding cost, although there is some association between ADI and cost, this study may illustrate that ADI for THA and TKA is not sufficiently granular to identify the contribution of social drivers to elevated costs.

Contribution of Clinical Trial Event Data by Data Source: A Prespecified Analysis of the ADAPTABLE Randomized Clinical Trial.

Importance: Pragmatic randomized clinical trials (RCTs) often use multiple data sources to examine clinical events, but the relative contribution of data sources to clinical end-point rates is understudied. Objective: To assess the contribution of data sources (electronic health records [EHRs], public/private insurance claims, and/or participant-reported data) to clinical end points among ADAPTABLE participants who had available data. Design, Setting, and Participants: The ADAPTABLE study was an open-label, pragmatic RCT from April 2016 through June 2019 conducted in research networks within clinical practice. Participants had existing atherosclerotic cardiovascular disease and available data to analyze. The characteristics of patients by combinations of data source availability were compared to examine the contribution of each of the data sources to end-point ascertainment. Data for this prespecified analysis were examined from January 2022 to June 2023. Exposures: Randomized exposure to 81 mg or 325 mg of aspirin daily. Main Outcomes and Measures: Number of events for the primary end point (composite of death, hospitalization for myocardial infarction, and hospitalization for stroke) that were contributed by EHR or claims data and then number of events contributed by each additional data source. Results: Of 15 006 participants randomized with at least 1 other source of data available beyond participant-reported data, there were 8756 (58.3%) with participant-reported and EHR data; 4291 (28.6%) with participant-reported, EHR, and claims data; 1412 (9.4%) with EHR-only data; 262 (1.7%) with participant-reported and claims data; 202 (1.3%) with EHR and claims data; and 83 (0.6%) with claims-only data. Participants with EHR-only data were younger (median age, 63.7 years; IQR, 55.8-71.4) compared with the other groups (range, 65.6-71.9 years). Among participants with both EHR and claims data, with or without participant-reported data (n = 4493), for each outcome, most events (92%-100%) were identified in the EHR or in claims data. For all clinical end points, participant-reported data contributed less than 10% of events not otherwise available from claims or EHR data. Conclusions and Relevance: In this analysis of a pragmatic RCT, claims and EHR data provided the most clinical end-point data when compared with participant-reported events. These findings provide a framework for collecting end points in pragmatic clinical trials. Further work is needed to understand the data source combinations that most effectively provide clinical end-point data in RCTs.

A Principled Approach to Characterize and Analyze Partially Observed Confounder Data from Electronic Health Records.

Objective: Partially observed confounder data pose challenges to the statistical analysis of electronic health records (EHR) and systematic assessments of potentially underlying missingness mechanisms are lacking. We aimed to provide a principled approach to empirically characterize missing data processes and investigate performance of analytic methods. Methods: Three empirical sub-cohorts of diabetic SGLT2 or DPP4-inhibitor initiators with complete information on HbA1c, BMI and smoking as confounders of interest (COI) formed the basis of data simulation under a plasmode framework. A true null treatment effect, including the COI in the outcome generation model, and four missingness mechanisms for the COI were simulated: completely at random (MCAR), at random (MAR), and two not at random (MNAR) mechanisms, where missingness was dependent on an unmeasured confounder and on the value of the COI itself. We evaluated the ability of three groups of diagnostics to differentiate between mechanisms: 1)-differences in characteristics between patients with or without the observed COI (using averaged standardized mean differences [ASMD]), 2)-predictive ability of the missingness indicator based on observed covariates, and 3)-association of the missingness indicator with the outcome. We then compared analytic methods including "complete case", inverse probability weighting, single and multiple imputation in their ability to recover true treatment effects. Results: The diagnostics successfully identified characteristic patterns of simulated missingness mechanisms. For MAR, but not MCAR, the patient characteristics showed substantial differences (median ASMD 0.20 vs 0.05) and consequently, discrimination of the prediction models for missingness was also higher (0.59 vs 0.50). For MNAR, but not MAR or MCAR, missingness was significantly associated with the outcome even in models adjusting for other observed covariates. Comparing analytic methods, multiple imputation using a random forest algorithm resulted in the lowest root-mean-squared-error. Conclusion: Principled diagnostics provided reliable insights into missingness mechanisms. When assumptions allow, multiple imputation with nonparametric models could help reduce bias.

Age and Aspirin Dosing in Secondary Prevention of Atherosclerotic Cardiovascular Disease.

BACKGROUND: In patients with atherosclerotic cardiovascular disease, increasing age is concurrently associated with higher risks of ischemic and bleeding events. The objectives are to determine the impact of aspirin dose on clinical outcomes according to age in atherosclerotic cardiovascular disease. METHODS AND RESULTS: In the ADAPTABLE (Aspirin Dosing: A Patient-Centric Trial Assessing Benefits and Long-Term Effectiveness) trial, patients with atherosclerotic cardiovascular disease were randomized to daily aspirin doses of 81 mg or 325 mg. The primary effectiveness end point was death from any cause, hospitalization for myocardial infarction, or hospitalization for stroke. The primary safety end point was hospitalization for bleeding requiring transfusion. A total of 15 076 participants were randomized to aspirin 81 mg (n=7540) or 325 mg (n=7536) daily (median follow-up: 26.2 months; interquartile range: 19.0-34.9 months). Median age was 67.6 years (interquartile range: 60.7-73.6 years). Among participants aged <65 years (n=5841 [38.7%]), a primary end point occurred in 226 (7.54%) in the 81 mg group, and in 191 (6.80%) in the 325 mg group (adjusted hazard ratio [HR], 1.23 [95% CI, 1.01-1.49]). Among participants aged ≥65 years (n=9235 [61.3%]), a primary end point occurred in 364 (7.12%) in the 81 mg group, and in 378 (7.96%) in the 325 mg group (adjusted HR, 0.95 [95% CI, 0.82-1.10]). The age-dose interaction was not significant (P=0.559). There was no significant interaction between age and the randomized aspirin dose for the secondary effectiveness and the primary safety bleeding end points (P>0.05 for all). CONCLUSIONS: Age does not modify the impact of aspirin dosing (81 mg or 325 mg daily) on clinical end points in secondary prevention of atherosclerotic cardiovascular disease.

Incorporating Acute Conditions into Risk-Adjustment for Provider Profiling: The Case of the US News and World Report Best Hospitals Rankings Methodology.

Several years ago, the US News and World Report changed their risk-adjustment methodology, now relying almost exclusively on chronic conditions for risk adjustment. The impacts of adding selected acute conditions like pneumonia, sepsis, and electrolyte disorders ("augmented") to their current risk models ("base") for 4 specialties-cardiology, neurology, oncology, and pulmonology-on estimates of hospital performance are reported here. In the augmented models, many acute conditions were associated with substantial risks of mortality. Compared to the base models, the discrimination and calibration of the augmented models for all specialties were improved. While estimated hospital performance was highly correlated between the 2 models, the inclusion of acute conditions in risk-adjustment models meaningfully improved the predictive ability of those models and had noticeable effects on hospital performance estimates. Measures or conditions that address disease severity should always be included when risk-adjusting hospitalization outcomes, especially if the goal is provider profiling.

smdi: an R package to perform structural missing data investigations on partially observed confounders in real-world evidence studies.

Objectives: Partially observed confounder data pose a major challenge in statistical analyses aimed to inform causal inference using electronic health records (EHRs). While analytic approaches such as imputation are available, assumptions on underlying missingness patterns and mechanisms must be verified. We aimed to develop a toolkit to streamline missing data diagnostics to guide choice of analytic approaches based on meeting necessary assumptions. Materials and methods: We developed the smdi (structural missing data investigations) R package based on results of a previous simulation study which considered structural assumptions of common missing data mechanisms in EHR. Results: smdi enables users to run principled missing data investigations on partially observed confounders and implement functions to visualize, describe, and infer potential missingness patterns and mechanisms based on observed data. Conclusions: The smdi R package is freely available on CRAN and can provide valuable insights into underlying missingness patterns and mechanisms and thereby help improve the robustness of real-world evidence studies.

Correlations Between Relative Prevalence of Celiac Disease and Sociodemographic Variables in the United States.

INTRODUCTION: We evaluated the associations between celiac disease (CD) prevalence and regional sociodemographic variables in the United States. METHODS: The outcome was CD relative prevalence, defined as number of patients with CD among those in a Medicare registry per 3-digit ZIP code. Linear regression models assessed associations between relative prevalence of CD and sociodemographic variables. RESULTS: CD relative prevalence was positively correlated with median income, urban area, and proximity to a CD specialty center and negatively correlated with Black race, Latino/Hispanic ethnicity, and median social deprivation index score ( P < 0.01, all). DISCUSSION: CD relative prevalence is associated with indicators of economic advantage.

Linking Medicare-Medicaid Claims for Patient-Centered Outcomes Research Among Dual-Eligible Beneficiaries.

BACKGROUND: Evaluation of Medicare-Medicaid integration models' effects on patient-centered outcomes and costs requires multiple data sources and validated processes for linkage and reconciliation. OBJECTIVE: To describe the opportunities and limitations of linking state-specific Medicaid and Centers for Medicare & Medicaid Services administrative claims data to measure patient-centered outcomes for North Carolina dual-eligible beneficiaries. RESEARCH DESIGN: We developed systematic processes to (1) validate the beneficiary ID linkage using sex and date of birth in a beneficiary ID crosswalk, (2) verify dates of dual enrollment, and (3) reconcile Medicare-Medicaid claims data to support the development and use of patient-centered outcomes in linked data. PARTICIPANTS: North Carolina Medicaid beneficiaries with full Medicaid benefits and concurrent Medicare enrollment (FBDE) between 2014 and 2017. MEASURES: We identified need-based subgroups based on service use and eligibility program requirements. We calculated utilization and costs for Medicaid and Medicare, matched Medicaid claims to Medicare service categories where possible, and reported outcomes by the payer. Some services were covered only by Medicaid or Medicare, including Medicaid-only covered home and community-based services (HCBS). RESULTS: Of 498,030 potential dual enrollees, we verified the linkage and FBDE eligibility of 425,664 (85.5%) beneficiaries, including 281,174 adults enrolled in Medicaid and Medicare fee-for-service. The most common need-based subgroups were intensive behavioral health service users (26.2%) and HCBS users (10.8%) for adults under age 65, and HCBS users (20.6%) and nursing home residents (12.4%) for adults age 65 and over. Medicaid funded 42% and 49% of spending for adults under 65 and adults 65 and older, respectively. Adults under 65 had greater behavioral health service utilization but less skilled nursing facility, HCBS, and home health utilization compared with adults 65 and older. CONCLUSIONS: Linkage of Medicare-Medicaid data improves understanding of patient-centered outcomes among FBDE by combining Medicare-funded acute and ambulatory services with Medicaid-funded HCBS. Using linked Medicare-Medicaid data illustrates the diverse patient experience within FBDE beneficiaries, which is key to informing patient-centered outcomes, developing and evaluating integrated Medicare and Medicaid programs, and promoting health equity.

Optimizing data integration in trials that use EHR data: lessons learned from a multi-center randomized clinical trial.

BACKGROUND: Despite great promise, trials that ascertain patient clinical data from electronic health records (EHR), referred to here as "EHR-sourced" trials, are limited by uncertainty about how existing trial sites and infrastructure can be best used to operationalize study goals. Evidence is needed to support the practical use of EHRs in contemporary clinical trial settings. MAIN TEXT: We describe a demonstration project that used EHR data to complement data collected for a contemporary multi-center pharmaceutical industry outcomes trial, and how a central coordinating center supported participating sites through the technical, governance, and operational aspects of this type of activity. We discuss operational considerations related to site selection, data extraction, site performance, and data transfer and quality review, and we outline challenges and lessons learned. We surveyed potential sites and used their responses to assess feasibility, determine the potential capabilities of sites and choose an appropriate data extraction strategy. We designed a flexible, multimodal approach for data extraction, enabling each site to either leverage an existing data source, create a new research datamart, or send all data to the central coordinating center to produce the requisite data elements. We evaluated site performance, as reflected by the speed of contracting and IRB approval, total patients enrolled, enrollment yield, data quality, and compared performance by data collection strategy. CONCLUSION: While broadening the type of sites able to participate in EHR-sourced trials may lead to greater generalizability and improved enrollment, sites with fewer technical resources may require additional support to participate. Central coordinating center support is essential to facilitate the execution of operational processes. Future work should focus on sharing lessons learned and creating reusable tools to facilitate participation of heterogeneous trial sites.

Non-overdose acute care hospitalizations for opioid use disorder among commercially-insured adults: a retrospective cohort study.

BACKGROUND: Acute care inpatient admissions outside of psychiatric facilities have been increasingly identified as a critical touchpoint for opioid use disorder (OUD) treatment. We sought to describe non-opioid overdose hospitalizations with documented OUD and examine receipt of post-discharge outpatient buprenorphine. METHODS: We examined acute care hospitalizations with an OUD diagnosis in any position within US commercially-insured adults age 18-64 years (IBM MarketScan claims, 2013-2017), excluding opioid overdose diagnoses. We included individuals with ≥ 6 months of continuous enrollment prior to the index hospitalization and ≥ 10 days following discharge. We described demographic and hospitalization characteristics, including outpatient buprenorphine receipt within 10 days of discharge. RESULTS: Most (87%) hospitalizations with documented OUD did not include opioid overdose. Of 56,717 hospitalizations (49,959 individuals), 56.8% had a primary diagnosis other than OUD, 37.0% had documentation of an alcohol-related diagnosis code, and 5.8% end in a self-directed discharge. Where opioid use disorder was not the primary diagnosis, 36.5% were due to other substance use disorders, and 23.1% were due to psychiatric disorders. Of all non-overdose hospitalizations who had prescription medication insurance coverage and who were discharged to an outpatient setting (n = 49, 237), 8.8% filled an outpatient buprenorphine prescription within 10 days of discharge. CONCLUSIONS: Non-overdose OUD hospitalizations often occur with substance use disorders and psychiatric disorders, and very few are followed by timely outpatient buprenorphine. Addressing the OUD treatment gap during hospitalization may include implementing medication for OUD for inpatients with a broad range of diagnoses.

Neighborhood socioeconomic deprivation, healthcare access, and 30-day mortality and readmission after sepsis or critical illness: findings from a nationwide study.

BACKGROUND: To determine if neighborhood socioeconomic deprivation independently predicts 30-day mortality and readmission for patients with sepsis or critical illness after adjusting for individual poverty, demographics, comorbidity burden, access to healthcare, and characteristics of treating healthcare facilities. METHODS: We performed a nationwide study of United States Medicare beneficiaries from 2017 to 2019. We identified hospitalized patients with severe sepsis and patients requiring prolonged mechanical ventilation, tracheostomy, or extracorporeal membrane oxygenation (ECMO) through Diagnosis Related Groups (DRGs). We estimated the association between neighborhood socioeconomic deprivation, measured by the Area Deprivation Index (ADI), and 30-day mortality and unplanned readmission using logistic regression models with restricted cubic splines. We sequentially adjusted for demographics, individual poverty, and medical comorbidities, access to healthcare services; and characteristics of treating healthcare facilities. RESULTS: A total of 1,526,405 admissions were included in the mortality analysis and 1,354,548 were included in the readmission analysis. After full adjustment, 30-day mortality for patients was higher for those from most-deprived neighborhoods (ADI 100) compared to least deprived neighborhoods (ADI 1) for patients with severe sepsis (OR 1.35 95% [CI 1.29-1.42]) or with prolonged mechanical ventilation with or without sepsis (OR 1.42 [95% CI 1.31, 1.54]). This association was linear and dose dependent. However, neighborhood socioeconomic deprivation was not associated with 30-day unplanned readmission for patients with severe sepsis and was inversely associated with readmission for patients requiring prolonged mechanical ventilation with or without sepsis. CONCLUSIONS: A strong association between neighborhood socioeconomic deprivation and 30-day mortality for critically ill patients is not explained by differences in individual poverty, demographics, measured baseline medical risk, access to healthcare resources, or characteristics of treating hospitals.

Neighborhood Socioeconomic Disadvantage, Healthcare Access, and Outcomes of Hospitalizations for Common Pulmonary Conditions: A National Study of Medicare Beneficiaries.

Rationale: Understanding how systemic forces and environmental exposures impact patient outcomes is critical to advancing health equity and improving population health for patients with pulmonary disease. This relationship has not yet been assessed at the population level nationally. Objectives: To determine whether neighborhood socioeconomic deprivation is independently associated with 30-day mortality and readmission for hospitalized patients with pulmonary conditions, after controlling for demographics, access to healthcare resources, and characteristics of admitting healthcare facilities. Methods: This was a retrospective, population-level cohort study of 100% of United States nationwide Medicare inpatient and outpatient claims from 2016-2019. Patients were admitted for one of four pulmonary conditions (pulmonary infections, chronic lower respiratory disease, pulmonary embolism, and pleural and interstitial lung diseases), defined by diagnosis-related group. The primary exposure was neighborhood socioeconomic deprivation, measured by the area deprivation index. The main outcomes were 30-day mortality and 30-day unplanned readmission, defined by Centers for Medicare and Medicaid Services methodologies. Generalized estimating equations were used to estimate logistic regression models for the primary outcomes, addressing clustering by hospital. A sequential adjustment strategy was first adjusted for age, legal sex, Medicare-Medicaid dual eligibility, and comorbidity burden, then adjusted for metrics of access to healthcare resources, and finally adjusted for characteristics of the admitting healthcare facility. Results: After full adjustment, patients from low socioeconomic status neighborhoods had greater 30-day mortality after admission for pulmonary embolism (odds ratio [OR], 1.26; 95% confidence interval [CI], 1.13-1.40), respiratory infections (OR, 1.20; 95% CI, 1.16-1.25), chronic lower respiratory disease (OR, 1.31; 95% CI, 1.22-1.41), and interstitial lung disease (OR, 1.15; 95% CI, 1.04-1.27) when compared to patients from the highest SES neighborhoods. Low neighborhood socioeconomic status was also associated with 30-day readmission for all groups except the interstitial lung disease group. Conclusions: Neighborhood socioeconomic deprivation may be a key factor driving poor health outcomes for patients with pulmonary diseases.

Pragmatic evaluation of events and benefits of lipid lowering in older adults (PREVENTABLE): Trial design and rationale.

Whether initiation of statins could increase survival free of dementia and disability in adults aged ≥75 years is unknown. PREVENTABLE, a double-blind, placebo-controlled randomized pragmatic clinical trial, will compare high-intensity statin therapy (atorvastatin 40 mg) with placebo in 20,000 community-dwelling adults aged ≥75 years without cardiovascular disease, disability, or dementia at baseline. Exclusion criteria include statin use in the prior year or for >5 years and inability to take a statin. Potential participants are identified using computable phenotypes derived from the electronic health record and local referrals from the community. Participants will undergo baseline cognitive testing, with physical testing and a blinded lipid panel if feasible. Cognitive testing and disability screening will be conducted annually. Multiple data sources will be queried for cardiovascular events, dementia, and disability; survival is site-reported and supplemented by a National Death Index search. The primary outcome is survival free of new dementia or persisting disability. Co-secondary outcomes are a composite of cardiovascular death, hospitalization for unstable angina or myocardial infarction, heart failure, stroke, or coronary revascularization; and a composite of mild cognitive impairment or dementia. Ancillary studies will offer mechanistic insights into the effects of statins on key outcomes. Biorepository samples are obtained and stored for future study. These results will inform the benefit of statins for increasing survival free of dementia and disability among older adults. This is a pioneering pragmatic study testing important questions with low participant burden to align with the needs of the growing population of older adults.

Outcomes among patients with peripheral artery disease in the Aspirin Dosing: A Patient-Centric Trial Assessing Benefits and Long-Term Effectiveness (ADAPTABLE) study.

BACKGROUND: We aimed to understand the effects of aspirin dose on outcomes in patients with peripheral artery disease (PAD) as well as their participation in a pragmatic randomized controlled trial. METHODS: In a subanalysis of the Aspirin Dosing: A Patient-Centric Trial Assessing Benefits and Long-Term Effectiveness (ADAPTABLE) study, we compared aspirin doses (81 vs 325 mg) among participants with PAD and study participation metrics in patients with and without PAD. The primary outcome composite was all-cause mortality, nonfatal myocardial infarction, and nonfatal stroke. RESULTS: Among 14,662 participants enrolled in ADAPTABLE with PAD status available, 3493 (23.8%) had PAD. Participants with PAD were more likely to experience the primary composite (13.76% vs 5.31%, p < 0.001), all-cause mortality (7.55% vs 3.01%, p < 0.001), myocardial infarction (5.71% vs 2.09%, p < 0.001), stroke (2.45% vs 0.86%, p < 0.001), and major bleeding (1.19% vs 0.44%, p < 0.001). A higher aspirin dose did not reduce the primary outcome in patients with PAD (13.68% vs 13.84% in 81 mg and 325 mg groups; OR 1.05, 95% CI 0.88-1.25). Participants with PAD were less likely to enroll via email (33.0% vs 41.9%, p < 0.0001), less likely to choose internet follow-up (79.2% vs 89.5%, p < 0.0001), and were more likely to change their aspirin doses (39.7% vs 30.7%, p < 0.0001). CONCLUSIONS: ADAPTABLE participants with PAD did not benefit from a higher dose of aspirin and participated in the study differently from those without PAD. These results reinforce the need for additional PAD-specific research and suggest that different trial strategies may be needed for optimal engagement of patients with PAD. (ClinicalTrials.gov Identifier: NCT02697916).

Association Between Neighborhood Socioeconomic Status and 30-Day Mortality and Readmission for Patients With Common Neurologic Conditions.

BACKGROUND AND OBJECTIVES: Patients of low individual socioeconomic status (SES) are at a greater risk of unfavorable health outcomes. However, the association between neighborhood socioeconomic deprivation and health outcomes for patients with neurologic disorders has not been studied at the population level. Our objective was to determine the association between neighborhood socioeconomic deprivation and 30-day mortality and readmission after hospitalization for various neurologic conditions. METHODS: This was a retrospective study of nationwide Medicare claims from 2017 to 2019. We included patients older than 65 years hospitalized for the following broad categories based on diagnosis-related groups (DRGs): multiple sclerosis and cerebellar ataxia (DRG 058-060); stroke (061-072); degenerative nervous system disorders (056-057); epilepsy (100-101); traumatic coma (082-087), and nontraumatic coma (080-081). The exposure of interest was neighborhood SES, measured by the area deprivation index (ADI), which uses socioeconomic indicators, such as educational attainment, unemployment, infrastructure access, and income, to estimate area-level socioeconomic deprivation at the level of census block groups. Patients were grouped into high, middle, and low neighborhood-level SES based on ADI percentiles. Adjustment covariates included age, comorbidity burden, race/ethnicity, individual SES, and sex. RESULTS: After exclusions, 905,784 patients were included in the mortality analysis and 915,993 were included in the readmission analysis. After adjustment for age, sex, race/ethnicity, comorbidity burden, and individual SES, patients from low SES neighborhoods had higher 30-day mortality rates compared with patients from high SES neighborhoods for all disease categories except for multiple sclerosis: magnitudes of the effect ranged from an adjusted odds ratio of 2.46 (95% CI 1.60-3.78) for the nontraumatic coma group to 1.23 (95% CI 1.19-1.28) for the stroke group. After adjustment, no significant differences in readmission rates were observed for any of the groups. DISCUSSION: Neighborhood SES is strongly associated with 30-day mortality for many common neurologic conditions even after accounting for baseline comorbidity burden and individual SES. Strategies to improve health equity should explicitly consider the effect of neighborhood environments on health outcomes.