Faculty Bibliography

BACKGROUND:Results from national surveys indicate that many older adults reported delayed medical care during the acute phase of the COVID-19 pandemic, yet few studies have used objective data to characterize healthcare utilization among vulnerable older adults in that period. In this study, we characterized healthcare utilization during the acute pandemic phase (March 7-October 6, 2020) and examined risk factors for total disruption of care among older adults with multiple chronic conditions (MCC) in New York City. METHODS:This retrospective cohort study used electronic health record data from NYC patients aged ≥ 50 years with a diagnosis of either hypertension or diabetes and at least one other chronic condition seen within six months prior to pandemic onset and after the acute pandemic period at one of several major academic medical centers contributing to the NYC INSIGHT clinical research network (n=276,383). We characterized patients by baseline (pre-pandemic) health status using cutoffs of systolic blood pressure (SBP) < 140mmHg and hemoglobin A1C (HbA1c) < 8.0% as: controlled (below both cutoffs), moderately uncontrolled (below one), or poorly controlled (above both, SBP > 160, HbA1C > 9.0%). Patients were then assessed for total disruption versus some care during shutdown using recommended care schedules per baseline health status. We identified independent predictors for total disruption using logistic regression, including age, sex, race/ethnicity, baseline health status, neighborhood poverty, COVID infection, number of chronic conditions, and quartile of prior healthcare visits. RESULTS:Among patients, 52.9% were categorized as controlled at baseline, 31.4% moderately uncontrolled, and 15.7% poorly controlled. Patients with poor baseline control were more likely to be older, female, non-white and from higher poverty neighborhoods than controlled patients (P < 0.001). Having fewer pre-pandemic healthcare visits was associated with total disruption during the acute pandemic period (adjusted odds ratio [aOR], 8.61, 95% Confidence Interval [CI], 8.30-8.93, comparing lowest to highest quartile). Other predictors of total disruption included self-reported Asian race, and older age. CONCLUSIONS:This study identified patient groups at elevated risk for care disruption. Targeted outreach strategies during crises using prior healthcare utilization patterns and disease management measures from disease registries may improve care continuity.

OBJECTIVES/OBJECTIVE:Despite significant therapeutic advances in psoriatic arthritis (PsA), many patients do not achieve remission and cycle through multiple biologic (b)- or targeted synthetic (ts)- DMARDs. Identifying the underlying reasons for repetitive therapeutic failure remains a knowledge gap. Here we describe prescribing patterns and characteristics of PsA patients with multi-b/tsDMARD failure at the NYU Psoriatic Arthritis Center. METHODS:Nine hundred sixty PsA patients were enrolled in an observational, longitudinal registry. Demographics, medical history, medication use, and psoriatic disease phenotype were collected. Multi-b/tsDMARD failure was defined as requiring ≥ 4 b/tsDMARDs. RESULTS:Seven hundred twenty-five patients (75%) used ≥ 1 b/tsDMARD during their disease course. The initial b/tsDMARDs prescribed were predominately anti-TNF agents. 166 (17%) patients had multi-b/tsDMARD failure. Compared to those requiring 1 b/tsDMARD, female sex (OR 2.3; 95%CI 1.4-3.8), axial disease (OR 2.1; 95% CI 1.2-3.6), depression (OR 2.0; 95%CI 1.1-3.7), and obesity (OR 1.7; 95%CI 1.0-2.8) were risk factors for multi-b/tsDMARD failure disease after adjustment for age, disease duration, sex, depression, smoking, obesity, and skin severity. Patients with multi-b/tsDMARD failure PsA also had increased disease activity at their clinical visit (i.e., swollen joint count, p = 0.005). CONCLUSION/CONCLUSIONS:In this cohort, 17% patients with PsA experienced multi-b/tsDMARD failure. These patients were more likely to be female, obese, and have higher rates of axial involvement and depression, along with higher active disease activity. This highlights the inflammatory and non-inflammatory drivers of multiple therapeutic failures, underscoring the need for precision medicine strategies and potential non-pharmacologic adjuvant therapies for patients with PsA to improve outcomes and quality of life.

Mandatory prescription drug monitoring programs and cannabis legalization have been hypothesized to reduce overdose deaths. We examined associations between prescription monitoring programs with access mandates ("must-query PDMPs"), legalization of medical and recreational cannabis supply, and opioid overdose deaths in United States counties in 2013-2020. Using data on overdose deaths from the National Vital Statistics System, we fit Bayesian spatiotemporal models to estimate risk differences and 95% credible intervals (CrI) in county-level opioid overdose deaths associated with enactment of these state policies. Must-query PDMPs were independently associated with on average 0.8 (95% CrI: 0.5, 1.0) additional opioid-involved overdose deaths per 100,000 person-years. Legal cannabis supply was not independently associated with opioid overdose deaths in this time period. Must-query PDMPs enacted in the presence of legal (medical or recreational) cannabis supply were associated with 0.7 (95% CrI: 0.4, 0.9) more opioid-involved deaths, relative to must-query PDMPs without any legal cannabis supply. In a time when overdoses are driven mostly by non-prescribed opioids, stricter opioid prescribing policies and more expansive cannabis legalization were not associated with reduced overdose death rates.

BACKGROUND:Medication non-adherence, which is common in chronic diseases such as heart failure, is often estimated using proportion of days covered (PDC). PDC is typically calculated using medication fill information from pharmacy or insurance claims data, which lack information on when medications are prescribed. Many electronic health records (EHRs) have prescription and pharmacy fill data available, enabling enhanced PDC assessment that can be utilized in routine clinical care. OBJECTIVE:To describe our approach to calculating PDC using linked EHR-pharmacy data and to compare to PDC calculated using pharmacy-only data for patients with heart failure. METHODS:We performed a retrospective cohort study of adult patients with heart failure who were prescribed guideline-directed medical therapy (GDMT) and seen in a large health system. Using linked EHR-pharmacy data, we estimated medication adherence by PDC as the percent of days in which a patient possessed GDMT based on medication pharmacy fills over the number of days the prescription order was active. We also calculated PDC using pharmacy-only data, calculated as medications possessed over days with continued medication fills. We compared these two approaches for days observed and PDC using a paired t-test. RESULTS:Among 33,212 patients with heart failure who were prescribed GDMT, 2226 (6.7%) never filled their medications, making them unavailable in the assessment of PDC using pharmacy-only data (n = 30,995). Linked EHR-pharmacy data had slightly longer days observed for PDC assessment (164.7 vs. 163.4 days; p < 0.001) and lower PDC (78.5 vs. 90.6, p < 0.001) as compared to assessment using pharmacy-only data. CONCLUSIONS:Linked EHR-pharmacy data can be used to identify patients who never fill their prescriptions. Estimating adherence using linked EHR-pharmacy data resulted in a lower mean PDC as compared to estimates using pharmacy-only data.

BACKGROUND:Cardiometabolic comorbidities such as obesity, diabetes, and hypertension are highly prevalent in heart failure (HF). We aimed to examine the association between severity of cardiometabolic comorbidities and hospitalization in patients with HF. METHODS: RESULTS: CONCLUSIONS:Greater cardiometabolic comorbidity burden was associated with increased risk of all-cause hospitalization in HF. This reinforces the role for targeting severely uncontrolled cardiometabolic comorbidities to reduce morbidity in HF.

OBJECTIVE:Individuals of racially and ethnically diverse backgrounds are underrepresented in psoriatic arthritis (PsA) research/clinical trials, despite evidence that their disease presentation, severity and course may be distinct. Here we aim to describe how race, ethnicity and other socioeconomic factors inform disease characteristics in PsA. METHODS:817 consecutive patients with PsA from a large, diverse metropolitan area, were enrolled in an observational, longitudinal registry. Demographics, medical history, medication use, and psoriatic disease phenotype and activity were all recorded and analyzed. RESULTS:The population was 77.4% non-Hispanic White, 2.2% Black, 7.1% Asian, and 9.9% identified as other races or multiracial, and 11.8% identified as Hispanic. Hispanic and non-White individuals had higher tender joint counts (p= 0.033) with similar swollen joint counts (p= 0.308) and medication use (p= 0.171). They also had high rates of radiographic axial disease. Hispanic individuals were significantly more likely to have higher tender joint counts (p= 0.029), higher RAPID3 scores (p= 0.004), and moderate-severe psoriasis (p= 0.010) compared with non-Hispanic White individuals. CONCLUSION/CONCLUSIONS:In this diverse cohort, 22.6% of patients identified as underrepresented racial and/or ethnic groups, mostly Asian or Hispanic. Despite similar swollen joint counts and medication use, non-white individuals have higher tender joint counts compared with white individuals. Phenotypically, they also were more likely to have radiographic axial involvement. These findings may reflect differences in PsA presentation, experience and outcomes in individuals of various racial and ethnic groups, which need to be taken into consideration in clinical care and research design.

IMPORTANCE/UNASSIGNED:Among older adults with ischemic heart disease, participation in traditional ambulatory cardiac rehabilitation (CR) remains low. While mobile health CR (mHealth-CR) provides a novel opportunity to deliver care, age-specific impairments to technology use may limit uptake, and efficacy data are currently lacking. OBJECTIVE/UNASSIGNED:To test whether mHealth-CR improves functional capacity in older adults. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:The RESILIENT phase 2, multicenter, randomized clinical trial recruited patients aged 65 years or older with ischemic heart disease (defined as a hospital visit for myocardial infarction or coronary revascularization) from 5 academic hospitals in New York, Connecticut, and Massachusetts between January 9, 2020, and April 22, 2024. INTERVENTION/UNASSIGNED:Participants were randomized 3:1 to mHealth-CR or usual care. mHealth-CR consisted of commercially available software delivered on a tablet computer, coupled with remote monitoring and weekly exercise therapist telephone calls, delivered over a 3-month duration. As RESILIENT was a trial conducted in a routine care setting to inform decision-making, participants in both arms were also allowed to receive traditional CR at their cardiologist's discretion. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The primary outcome was change from baseline to 3 months in functional capacity, measured by 6-minute walk distance (6MWD). Secondary outcomes were health status (12-Item Short Form Health Survey [SF-12]), residual angina, and impairment in activities of daily living. RESULTS/UNASSIGNED:A total of 400 participants (median age, 71.0 years [range, 65.0-91.0 years]; 291 [72.8%] male) were randomized to mHealth-CR (n = 298) or usual care (n = 102) and included in the intention-to-treat analysis. Of those, 356 participants (89.0%) returned in person for 6MWD assessment at 3 months. For the primary outcome, there was no adjusted difference in 6MWD between participants receiving mHealth-CR vs usual care (15.6 m; 95% CI, -0.3 to 31.5 m; P = .06). Among subgroups, there was an improvement in 6MWD among women (36.6 m; 95% CI, 8.7-64.4 m). There were no differences in any secondary outcomes between groups (eg, adjusted difference in SF-12 physical component scores at 3 months: -1.9 points; 95% CI, -3.9 to 0.2 points). Based on inverse propensity score weighting, there was no effect of mHealth-CR on 6MWD among those who did not attend traditional CR (25.7 m; 95% CI, -8.7 to 60.2 m). CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this randomized clinical trial of mHealth-CR vs usual care, mHealth-CR did not significantly increase 6MWD or result in improvements in secondary outcomes. The findings suggest the older adult population may require more age-tailored mHealth strategies to effectively improve outcomes. TRIAL REGISTRATION/UNASSIGNED:ClinicalTrials.gov Identifier: NCT03978130.

PURPOSE/OBJECTIVE:Hypertension (HTN) is common and represents a major modifiable risk factor for ischemic heart disease in older adults. While home blood pressure monitoring (HBPM) is important in HTN management, patterns of HBPM engagement in older adults undergoing mobile health cardiac rehabilitation (mHealth-CR) are unknown. We aimed to identify patterns of adherence to HBPM in a cohort of older adults undergoing mHealth-CR to optimize HBPM use in the future. METHODS:We used interim data from the ongoing Rehabilitation using Mobile Health for Older Adults with Ischemic Heart Disease in the Home Setting (RESILIENT) randomized trial, in which intervention arm participants (adults ≥ 65 years with ischemic heart disease) were instructed to monitor blood pressure (BP) at least weekly. Engagement groups were determined by latent class analysis and compared using ANOVA or Chi-Square tests. Longitudinal mixed effect modeling determined the associations between weekly HBPM and baseline covariates including uncontrolled HTN, obesity, diabetes, depression, alcohol, and tobacco use. RESULTS:Of the 111 participants, the mean age was 71.9 ± 5.6 years, and 83% had HTN. Over the 12-week study, mean HBPM engagement was 2.3 ± 2.3 d/wk. We observed 3 distinct patterns of engagement: high engagement (22%), gradual decline (10%), and sustained baseline engagement (68%). HBPM adherence decreased in two of the engagement groups over time. Of the covariates tested, only depression was associated with weekly HBPM after adjusting for relevant covariates (OR 9.09, P  = .03). CONCLUSIONS:In this older adult cohort undergoing mHealth-CR, we found three main engagement groups with declining engagement over time in two of the three groups. These patterns can inform future mHealth-CR interventions.

INTRODUCTION/BACKGROUND:The United States is facing an opioid use disorder (OUD) epidemic, marked by unprecedented overdose death rates. In New York State, synthetic opioids significantly contribute to the increasing overdose deaths, disproportionately impacting Black and Latinx communities. There is an urgent need to address issues related to equitable access to and the quality of care provided by substance use disorder (SUD) treatment programs. In light of this, the Quality Measurement and Management Research Center (QM2-RC) brought together an academic-government partnership to develop a person-centered quality measurement system and to assess its impact on a statewide treatment system that serves approximately 180,000 individuals per year. METHODS AND ANALYSIS/METHODS:The QM2-RC encompasses three interconnected projects (Project 1, 2, and 3) aimed at developing a quality management strategy and evaluating its impact on system performance across New York State. This report specifically focuses on Project 3, which involves a stepped-wedge trial with 35 clinics receiving a quality management intervention that includes performance coaching. This intervention will be compared to a treatment-as-usual (TAU) condition for clinics not participating in the trial. Administrative data will be utilized to monitor outcomes over four years. The coaching intervention, guided by the Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) model, emphasizes interpreting quality measures and applying insights to enhance care. Coaches will provide support on data utilization, patient-centered care, harm reduction strategies, and the use of patient monitoring tools. The trial aims to evaluate clinic staff and leadership attitudes, experiences, and behaviors through surveys, semi-structured interviews, and external facilitator notes. Primary clinic outcomes will be assessed through adverse events, decreased clinic rates of substance use related emergency department visits and hospitalizations as well as mortality among patients within the first 12 months after admission to treatment after adjusting for individual and community level characteristics. This study is being developed over a multi-year period and will be informed by a mixed-methods approach incorporating multiple data sources, qualitative interviews, patient and clinic surveys. The study is being conducted in partnership with New York State Office of Addiction Services and Supports (OASAS) and will be informed by input from patient, providers, health insurers, family members and local governing units. DISCUSSION/CONCLUSIONS:Project 3 of the QM2 study specifically targets key barriers in measuring the quality of SUD treatment, including technological limitations, unvalidated measures, workforce data literacy, and concerns about fairness in assessing clinical complexity. Through the implementation of a stepped-wedge trial involving 35 clinics, the project aims to develop new quality measures, offer performance feedback, and engage clinic leadership and staff in efforts to improve practices. The ultimate goal of Project 3 is to overcome these barriers, promote person-centered care, and improve SUD treatment practices across New York State.

Prior studies suggest that diabetes is associated with severe outcomes following COVID-19. However, most research has focused on early phases of the COVID-19 pandemic, and less is known about changing diabetes-associated risks over time. We constructed a retrospective cohort of U.S. Veterans with documented COVID-19 between March 2020 and August 2023 (N = 426,170). We used Poisson regression models to estimate relative risks of 60-day mortality following COVID-19 among Veterans with and without diabetes, incorporating demographic and clinical covariates, as well as weights to address unequal probabilities of selection into the sample. We then incorporated interaction terms representing six-month time windows and plotted predicted mortality risks over time. To contextualize risk estimates, we repeated the analysis among a cohort of Veterans without documented COVID-19. Diabetes was associated with overall higher risk of 60-day mortality following COVID-19 (RR = 1.21, 95% CI = 1.17-1.26). Mortality risks attenuated over time and converged with risks observed among Veterans without COVID-19 by March-August 2022. Results suggest that post-COVID-19 mortality risks associated with diabetes may have attenuated over time. Mechanisms underlying the attenuation of mortality risks were beyond the scope of the paper, however, future studies can potentially shed light on the contributions of population immunity (driven by previous infection or vaccination status), changing treatment patterns, and other factors to time-varying mortality risks following COVID-19 among individuals with diabetes.