Faculty Bibliography

BACKGROUND:The COVID-19 pandemic had a significant impact on healthcare delivery. Older adults with multimorbidities were at risk of healthcare disruptions for the management of their chronic conditions. OBJECTIVE:To characterize healthcare disruptions during the COVID-19 healthcare shutdown and recovery period (March 7, 2020-October 6, 2020) and their effects on disease management among older adults with multimorbidities who were patients of NYC Health + Hospitals (H + H), the largest municipal safety-net system in the United States. DESIGN/METHODS:Observational. PATIENTS/METHODS:Patients aged 50 + with hypertension or diabetes and at least one other comorbidity, at least one H + H ambulatory visit in the six months before COVID-19 pandemic onset (March 6, 2020), and at least one visit in the post-acute shutdown period (October 7, 2020 to December 31, 2023). MAIN MEASURES/METHODS:We characterized disruption in care (defined as no ambulatory or telehealth visits during the acute shutdown) and estimated the effect of disruption on blood pressure control, hemoglobin A1c (HbA1c), and low-density lipoprotein (LDL) cholesterol using difference-in-differences models. KEY RESULTS/RESULTS:Out of 73,889 individuals in the study population, 12.5% (n = 9,202) received no ambulatory or telehealth care at H + H during the acute shutdown. Low pre-pandemic healthcare utilization, Medicaid insurance, and self-pay were independent predictors of care disruption. In adjusted analyses, the disruption group had a 3.0-percentage point (95% CI: 1.2-4.8) greater decrease in blood pressure control compared to those who received care. Disruption did not have a significant impact on mean HbA1c or LDL. CONCLUSIONS:Care disruption was associated with declines in blood pressure control, which while clinically modest, could impact risk of cardiovascular outcomes if sustained. Disruption did not affect HbA1c or LDL. Telehealth mitigated impacts of the pandemic on care disruption and subsequent disease management. Targeted outreach to those at risk of care disruption is needed during future crises.

OBJECTIVE:While timely interventions can improve medication adherence, it is challenging to identify which patients are at risk of nonadherence at point-of-care. We aim to develop and validate flexible machine learning (ML) models to predict a continuous measure of adherence to guideline-directed medication therapies (GDMTs) for heart failure (HF). MATERIALS AND METHODS/METHODS:We utilized a large electronic health record (EHR) cohort of 34,697 HF patients seen at NYU Langone Health with an active prescription for ≥1 GDMT between April 01, 2021 and October 31, 2022. The outcome was adherence to GDMT measured as proportion of days covered (PDC) at 6 months following a clinical encounter. Over 120 predictors included patient-, therapy-, healthcare-, and neighborhood-level factors guided by the World Health Organization's model of barriers to adherence. We compared performance of several ML models and their ensemble (superlearner) for predicting PDC with traditional regression model (OLS) using mean absolute error (MAE) averaged across 10-fold cross-validation, % increase in MAE relative to superlearner, and predictive-difference across deciles of predicted PDC. RESULTS:Superlearner, a flexible nonparametric prediction approach, demonstrated superior prediction performance. Superlearner and quantile random forest had the lowest MAE (mean [95% CI] = 18.9% [18.7%-19.1%] for both), followed by MAEs for quantile neural network (19.5% [19.3%-19.7%]) and kernel support vector regression (19.8% [19.6%-20.0%]). Gradient boosted trees and OLS were the 2 worst performing models with 17% and 14% higher MAEs, respectively, relative to superlearner. Superlearner demonstrated improved predictive difference. CONCLUSION/CONCLUSIONS:This development phase study suggests potential of linked EHR-pharmacy data and ML to identify HF patients who will benefit from medication adherence interventions. DISCUSSION/CONCLUSIONS:Fairness evaluation and external validation are needed prior to clinical integration.

BACKGROUND:Nonadherence to antihypertensive medications is common. Mobile health (mHealth)-based behavioral economic interventions may improve adherence, but remain largely untested, especially in vulnerable populations. OBJECTIVE:The study sought to test whether an mHealth incentive lottery would lower systolic blood pressure (SBP) and improve adherence. METHODS:BETTER-BP (Behavioral Economics Trial To Enhance Regulation of Blood Pressure) was a randomized trial conducted in 3 safety-net clinics in New York City. Eligible participants were adults with hypertension prescribed at least 1 antihypertensive medication, with SBP >140 mm Hg, and poor self-reported adherence. In the intervention arm, an incentive lottery was administered via SMS messaging. All participants received passive adherence monitoring. The intervention lasted 6 months, with continued monitoring until 12 months. The primary clinical endpoint was change in SBP at 6 months. The primary process endpoint was adequate antihypertensive medication adherence (≥80% days adherent) from baseline to 6 months. RESULTS:Four-hundred participants (265 intervention:135 control) were enrolled with median age 57 years, 60.5% women, 61.5% Hispanic, and 20.3% non-Hispanic Black. Over 70% had Medicaid or no insurance. At 6 months, intervention arm participants were twice as likely to achieve adequate adherence (71% vs 34%; adjusted risk ratio: 2.04; 95% CI: 1.58-2.63), but there was no significant change in mean SBP (-6.7 mm Hg intervention vs -5.8 mm Hg control; P = 0.62). From 6 to 12 months, adherence was similar (31% intervention vs 26% control; adjusted risk ratio: 1.17; 95% CI: 0.83-1.65). CONCLUSIONS:In a diverse safety-net population, the BETTER-BP intervention doubled the rate of adequate antihypertensive medication adherence but did not reduce SBP at 6 months.

BACKGROUND:Infliximab (IFX) is commonly used in the management of acute severe ulcerative colitis (ASUC), yet up to 30% of individuals still require colectomy within 1 year. Clinical data characterizing these patients, however, are limited. AIMS/OBJECTIVE:We aimed to determine risk factors for colectomy among patients with ASUC who received in-hospital IFX treatment. METHODS:We performed a retrospective analysis of patients with ASUC who were treated with at least one dose of IFX while admitted between 2014 and 2022. Cox proportional hazards (PH) models were used to assess demographic, clinical, and laboratory risk factors for colectomy within 30 days and 1 year of IFX initiation. RESULTS:Overall, 36/170 (21.2%) patients underwent colectomy within 1 year of IFX initiation, with 22 (12.9%) individuals requiring colectomy within 30 days. On univariable analysis, concomitant Clostridioides difficile infection during admission, a ≤50% decrease in C-reactive protein (CRP) and experiencing 3 or more bowel movements per day within 48 hours after an initial IFX dose were significantly associated with 1-year colectomy. On multivariable Cox PH analysis, C. difficile infection during admission (aHR=2.92, 95% CI: 1.12-7.58) and a higher CRP/albumin ratio on admission (aHR=1.13, 95% CI: 1.01-1.27) were associated with increased colectomy risk within 1 year of IFX initiation. CONCLUSIONS:C. difficile infection and a higher CRP/albumin ratio on admission are associated with decreased time to colectomy within 1 year of IFX among patients presenting with ASUC. These factors may aid in early risk stratification to minimize delays in JAK-inhibitor initiation or surgical referral.

BACKGROUND:Data on patient-centered outcomes of mobile health cardiac rehabilitation (mHealth-CR) for older adults with ischemic heart disease are limited. The RESILIENT (Rehabilitation at Home Using Mobile Health in Older Adults After Hospitalization for Ischemic Heart Disease) trial, the largest randomized study of mHealth-CR in this population, found no significant improvements in functional capacity, health status, angina, or disability compared with usual care. OBJECTIVES/OBJECTIVE:The purpose of this study was to evaluate whether mHealth-CR affects personalized goal attainment-a prespecified secondary endpoint of RESILIENT-using goal attainment scaling (GAS). METHODS:A total of 400 patients (≥65 years) with ischemic heart disease were randomized to mHealth-CR or usual care. Participants specified goals for CR at baseline using the five-category goal attainment scale: much-less-than-expected (-2), less-than-expected (-1), expected (0), better-than-expected (+1), and much-better-than-expected (+2). Goal attainment was assessed at 3 months. RESULTS:Of 400 patients (median age, 71.0 years [range 65.0-91.0]; 72.8% male; 65.2% prefrail/frail) randomized to mHealth-CR (n = 298) or usual care (n = 102), 353 (88.3%) completed GAS. Most goals addressed physical activity (54.0% mHealth-CR vs 59.0% usual care), health care behaviors (14.4% vs 11.9%), or symptom management (13.1% vs 9.0%). Rates of attaining or exceeding goals (GAS ≥0) were similar between groups (80.5% vs 77.6%; P = 0.492). However, in the intervention arm, there was a higher rate of exceeding expected level of goal attainment (GAS +1, +2) compared with usual care (52.6% vs 34.2%; P = 0.006). CONCLUSIONS:In a trial that did not demonstrate differences on traditional endpoints, those receiving mHealth-CR were more likely to exceed personalized CR goals. These findings suggest the intervention facilitated greater progress toward individualized goals and underscore the importance of patient-centered outcomes in CR.

IMPORTANCE/UNASSIGNED:Hypertension is often underrecognized, leading to preventable morbidity and mortality. Tailored data systems combined with care augmented by trained nonphysicians have the potential to improve cardiovascular care. OBJECTIVE/UNASSIGNED:To determine whether previously collected cardiovascular imaging data could be harnessed to improve the detection and treatment of hypertension through a system-level intervention. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:The NOTIFY-LVH trial was a 2-arm, pragmatic randomized clinical trial conducted from March 2023 through June 2024 within the Mass General Brigham health care system, a multi-institutional network serving the greater Boston, Massachusetts, area. The study included individuals with a Mass General Brigham primary care affiliation who had left ventricular hypertrophy (LVH) on a prior echocardiogram, had no established cardiomyopathy diagnosis, and were not being treated with antihypertensive medications. Patients were followed for 12 months postintervention. INTERVENTION/UNASSIGNED:Population health coordinators contacted clinicians of patients randomized to the intervention, notifying them of LVH and offering assistance with follow-up care. A clinical support pathway-including 24-hour ambulatory blood pressure monitoring or cardiology referrals-was provided to aid LVH evaluation. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The primary outcome was the initiation of an antihypertensive medication. Secondary outcomes included new hypertension and cardiomyopathy diagnoses. RESULTS/UNASSIGNED:A total of 648 patients were randomized-326 to the intervention and 322 to the control. Mean (SD) patient age was 59.4 (10.8) years and 248 patients (38.3%) were female. A total of 102 patients (15.7%) had a baseline diagnosis of hypertension and 109 patients (20.1%) had a mean outpatient blood pressure of 130/80 mm Hg or higher. Over 12 months, 53 patients (16.3%) in the intervention arm were prescribed an antihypertensive medication vs 16 patients (5.0%) in the control arm (adjusted odds ratio [OR], 3.76; 95% CI, 2.09-6.75; P < .001). Individuals in the intervention group were also more likely to be diagnosed with hypertension (adjusted OR, 4.43; 95% CI, 2.36-8.33; P < .001). Cardiomyopathy diagnoses did not significantly differ between groups. CONCLUSIONS AND RELEVANCE/UNASSIGNED:In the NOTIFY-LVH randomized clinical trial, a centralized population health coordinator-led notification and clinical support pathway for individuals with LVH on prior echocardiograms increased the initial treatment of hypertension. This work highlights the potential benefit of leveraging preexisting but potentially underutilized cardiovascular data to improve health care delivery through mechanisms augmenting the traditional ambulatory care system. TRIAL REGISTRATION/UNASSIGNED:ClinicalTrials.gov Identifier: NCT05713916.

BACKGROUND:Sarcopenia has been associated with adverse postoperative outcomes in older age cohorts, but has not been assessed in older adults with inflammatory bowel disease (IBD). Further, current assessments of sarcopenia among all aged individuals with IBD have used various measures of muscle mass as well as cutoffs to define its presence, leading to heterogeneous findings. METHODS:In this single-institution, multihospital retrospective study, we identified all patients aged 60 years and older with IBD who underwent disease-related intestinal resection between 2012 and 2022. Skeletal Muscle Index (SMI) and Total Psoas Index (TPI) were measured at the superior L3 endplate on preoperative computed tomography scans and compared through receiver operating characteristic curve. We then performed multivariable logistic regression to assess risk factors associated with an adverse 30-day postoperative outcome. Our primary outcome included a 30-day composite of postoperative mortality and complications, including infection, bleeding, cardiac event, cerebrovascular accident, acute kidney injury, venous thromboembolism, reoperation, all-cause rehospitalization, and need for intensive care unit-level care. RESULTS:A total of 120 individuals were included. Overall, 52% were female, 40% had ulcerative colitis, 60% had Crohn's disease, and median age at time of surgery was 70 years (interquartile range: 65-75). Forty percent of older adults had an adverse 30-day postoperative outcome, including infection (23%), readmission (17%), acute kidney injury (13%), bleeding (13%), intensive care unit admission (10%), cardiac event (8%), venous thromboembolism (7%), reoperation (6%), mortality (5%), and cerebrovascular accident (2%). When evaluating the predictive performance of SMI vs TPI for an adverse 30-day postoperative event, SMI had a significantly higher area under the curve of 0.66 (95% CI, 0.56-0.76) as compared to 0.58 (95% CI, 0.48-0.69) for TPI (P = .02). On multivariable logistic regression, prior IBD-related surgery (adjusted odds ratio [adjOR] 6.46, 95% CI, 1.85-22.51) and preoperative sepsis (adjOR 5.74, 95% CI, 1.36-24.17) significantly increased the odds of adverse postoperative outcomes, whereas increasing SMI was associated with a decreased risk of an adverse postoperative outcome (adjOR 0.88, 95% CI, 0.82-0.94). CONCLUSIONS:Sarcopenia, as measured by SMI, is associated with an increased risk of postoperative complications among older adults with IBD. Measurement of SMI from preoperative imaging can help risk stratify older adults with IBD undergoing intestinal resection.

OBJECTIVE:To compare anonymized and non-anonymized approaches for imputing race and ethnicity in descriptive studies of chronic disease burden using electronic health record (EHR)-based datasets. STUDY SETTING AND DESIGN/METHODS:In this New York City-based study, we first conducted simulation analyses under different missing data mechanisms to assess the performance of Bayesian Improved Surname Geocoding (BISG), single imputation using neighborhood majority information, random forest imputation, and multiple imputation with chained equations (MICE). Imputation performance was measured using sensitivity, precision, and overall accuracy; agreement with self-reported race and ethnicity was measured with Cohen's kappa (κ). We then applied these methods to impute race and ethnicity in two EHR-based data sources and compared chronic disease burden (95% CIs) by race and ethnicity across imputation approaches. DATA SOURCES AND ANALYTIC SAMPLE/UNASSIGNED:Our data sources included EHR data from NYU Langone Health and the INSIGHT Clinical Research Network from 3/6/2016 to 3/7/2020 extracted for a parent study on older adults in NYC with multiple chronic conditions. PRINCIPAL FINDINGS/RESULTS: = 0.33). When these methods were applied to the NYU and INSIGHT cohorts, however, racial and ethnic distributions and chronic disease burden were consistent across all imputation methods. Slight improvements in the precision of estimates were observed under all imputation approaches compared to a complete case analysis. CONCLUSIONS:BISG imputation may provide a more accurate racial and ethnic classification than single or multiple imputation using anonymized covariates, particularly if the missing data mechanism is MNAR. Descriptive studies of disease burden may not be sensitive to methods for imputing missing data.