Publications

OBJECTIVES: The 2023 Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) equations for 10-year cardiovascular disease (CVD) were developed by the American Heart Association to improve upon the 2013 Pooled Cohort Equations (PCEs). This study sought to compare risk reclassification using the PREVENT equations with and without the use of optional predictors of hemoglobin A1c (HbA1c) and urine albumin-creatinine ratio (UACR).

RESEARCH DESIGN AND METHODS: This was a cross-sectional study of adults aged 30 to 79 years participating in the National Health and Nutrition Examination Survey 2015-2020. Ten-year CVD estimates stratified by diabetes status using the base PREVENT equations and the enhanced PREVENT equations including HbA1c and UACR were examined.

RESULTS: The study included 8,293 participants (weighted mean age 51 years; 52% female; 13% with diabetes) representing 147.9 million US adults. Estimated 10-year CVD risks using the base and enhanced PREVENT equations were within 5 percentage points for 99% of adults without diabetes and 82% of adults with diabetes. Individuals with HbA1c ≥9.0% had a higher enhanced equations' mean risk of 17.8% (95% CI, 15.9%-19.7%) compared to the base equations' mean risk of 11.8% (95% CI, 10.7%-12.9%). This was mirrored with UACR, as individuals UACR ≥300 mg/g had a higher enhanced equations' mean risk at 36.1% (95% CI, 33.2%-39.1%) compared to the based equations' mean risk of 23.4% (95% CI, 20.0%-26.9%).

CONCLUSIONS: Inclusion of HbA1c and UACR in the PREVENT equations provides opportunity for greater individualization of CVD risk estimation in adults with diabetes but little benefit in populations without diabetes.

BACKGROUND: Physical restraints and antipsychotics should only be used as a last resort in hospitalized individuals at risk of harm to themselves or others. Since verbal reorientation and de-escalation are first-line management in these scenarios, patients with limited English proficiency (LEP) may be at higher risk of physical restraint and antipsychotic use. We aimed to examine the relationship between English proficiency, physical restraints, and antipsychotic use in hospitalized adults.

METHODS: Retrospective cohort study of adults discharged from an academic medical center between 1/2019 and 6/2023. LEP was defined by non-English primary language listed in the electronic medical record. The primary outcome was use of either physical restraints or antipsychotics during the hospitalization, defined by orders and pharmacy charges, respectively. Multivariable generalized estimating equations were used to examine the relationship between primary language and outcomes, controlling for demographic, hospitalization, and clinical characteristics.

RESULTS: The cohort consisted of 132,767 hospitalizations (mean age 62.9 years, 48.3% female, 10.8% with LEP). Either physical restraints or antipsychotics were used in 14,802 (11.2%) hospitalizations. Unadjusted outcome rates in LEP and non-LEP groups were similar (10.1% vs. 11.3% for either physical restraints or antipsychotics, 7.9% vs. 8.9% for physical restraints, and 4.9% vs. 4.9% for antipsychotics). However, LEP patients had higher adjusted odds of either physical restraint or antipsychotic use (aOR 1.18; 95% CI, 1.08-1.28), physical restraint use (aOR 1.30; 95% CI 1.17-1.43), and antipsychotic use (aOR 1.12; 95% CI 1.01-1.25). Subgroup analysis among patients with diagnosed delirium revealed an even stronger association between LEP and the primary outcome (aOR 1.42; 95% CI 1.22-1.65).

CONCLUSION: This single center study found language-based disparities in orders for physical restraints and antipsychotics among hospitalized patients. Given the potential risks associated with both physical restraints and antipsychotics, causes and mitigators of this disparity should be investigated.

IMPORTANCE: State Medicaid prescription cap policies (ie, limiting the monthly number of covered prescriptions) may impede access to medications for opioid use disorder (OUD) and other chronic conditions. Yet, these policies remain understudied among those who become subject to caps at age 21 years.

OBJECTIVE: To evaluate the association of prescription cap policies with medication and acute care use among young adults with OUD.

DESIGN, SETTING, AND PARTICIPANTS: This study identified a cohort of young adults diagnosed with OUD using T-MSIS Analytic Files from January 1, 2016, to December 31, 2021. Data analysis was conducted from July 2025 to December 2025. The study compared outcomes between prescription cap and noncap states using a difference-in-differences analysis where a 2-month policy phase-in window was applied before and after age 21 years and effects estimated across the full follow-up period and the early (months 3-6), mid (months 7-9), and late (months 10-12) periods since the 21st birthday.

EXPOSURES: Becoming exposed to prescription caps at age 21 years.

MAIN OUTCOMES AND MEASURES: Monthly use (any and count) of buprenorphine, overall prescriptions, inpatient hospitalizations, and emergency department (ED) visits 12 months before vs after participant reached the age of 21.

RESULTS: This study analyzed 15 526 individuals from 26 non-prescription cap states and 1769 from 8 states with prescription cap policies. Most individuals were female (noncap states, 8156 [52.5%]; cap states, 1033 [58.4%]) and White (noncap states, 9512 [61.3%]; cap states, 705 [39.9%]). The baseline monthly prevalence for noncap and cap states was 39.3% vs 40.2% for any prescription receipt, 7.5% vs 3.1% for buprenorphine receipt, 3.2% vs 4.8% for hospitalizations, and 14.1% vs 18.7% for ED visits. After adjustment, cap policies were associated with a 4.7% (95% confidence limit [CL], -9.9% to -0.2%) lower prevalence of any prescription receipt and 12.7% (95% CL, -18.7%, -6.7%) fewer total monthly prescriptions 10 to 12 months after participants reached the age of 21. Cap states had more hospitalizations during postperiod months 10 to 12 (6.0%; 95% CL, 0.3%-10.0%) and more ED visits in postperiod months 3 to 6 (4.7%; 95% CL, 1.0%-10.0%) and months 7 to 9 (8.3%; 95% CL, 3.3%-13.3%). Buprenorphine use did not significantly change after cap implementation.

CONCLUSIONS AND RELEVANCE: In this cohort study, Medicaid prescription caps were associated with lower overall use of prescription medications and greater frequency of acute care use among young adults with OUD.

BACKGROUND: Hypertension is common during and after pregnancy. Patterns of antihypertensive medication discontinuation (AMD) in the postpartum period are not well characterized. This study examined factors associated with AMD among postpartum women.

METHODS: A retrospective claims analysis was conducted using the Komodo Health Healthcare Map. The study included 63,312 postpartum women aged 18-64 years who delivered between January 1, 2019, and December 31, 2022, and initiated an antihypertensive medication within 30 days after live delivery. AMD was defined as the absence of any anti-hypertensive medication from index medication (days' supply + 30-day). Multivariable Poisson regression models with a log link and robust variance estimators were used.

RESULTS: Discontinuation occurred in 57.8% (36,576) of women. In adjusted analyses, older age was associated with lower risk of AMD compared with women aged 18-24 years (RR 0.93, 95% CI 0.93, 0.94 for ages 25-34; RR 0.89, 95% CI 0.88, 0.90 for ages 35-44; RR 0.85, 95% CI 0.82, 0.88 for ages ≥45). Hispanic (RR 1.03, 95% CI 1.02, 1.04) and Asian (RR 1.02, 95% CI 1.01, 1.04) women had higher risk of discontinuation compared with White women. Women with eclampsia (RR 0.97, 95% CI 0.97, 0.98), baseline hypertension (RR 0.95, 95% CI 0.95, 0.96), and postpartum depression (RR 0.95, 95% CI 0.94, 0.96) had lower risk of discontinuation.

CONCLUSIONS: Postpartum AMD was common in this national claims-based cohort. Differences across demographic and clinical subgroups highlight patient populations that may benefit from directed postpartum blood pressure follow-up and medication management.

INTRODUCTION: Although drug shortages for outpatient chronic conditions commonly occur, population-level data on how they impact patients' ability to refill prescriptions is scarce. We sought to identify distinct patterns of refill adherence following drug shortages and patient- and prescription-level factors associated with adherence trajectories reflecting potential shortage-related treatment disruption.

METHODS: We retrospectively analyzed panel data assembled from 2017 to 2020 Veterans Health Administration (VHA) electronic health record data. Patients were included if they were baseline users of medications subject to a shortage within VHA. Group-based trajectory modeling was applied to users' monthly proportion of days covered (PDC) values from 6-months before to 6-months after the reported drug supply chain disruption. Patient demographics and medication characteristics were compared between identified trajectory groups using multivariable logistic regression.

RESULTS: Among 1.5 million episodes of medication use (representing 1.3 million unique Veterans) for 29 medications in shortage in VHA, 6.3% were for female patients and the mean age was 66.4 ± 12.8 years. A 4-group trajectory model had the best fit: High Adherence (69.2% of observations), Moderate Adherence (14.1%), Potential Shortage-Related Disruption (8.5%), and Pre-Shortage Disruption (8.3%). Drug characteristics (drug class, number of manufacturers) were more strongly associated than patient characteristics with having Potential Shortage-Related Treatment Disruption vs. High Adherence.

CONCLUSIONS: We identified 4 trajectories of refill adherence for medications subject to VHA drug shortages, with 8.5% of users of affected drugs exhibiting a trajectory consistent with shortage-related treatment disruption. Drug characteristics may modify whether drug shortages lead to treatment disruption in VHA.

BACKGROUND: Alert fatigue is defined as alert dismissals due to excessive or irrelevant alerts and is frequently cited as a barrier to clinical decision support system use and impact. However, the criteria for determining the presence or absence of alert fatigue are poorly defined. The objective of this systematic review of systematic reviews was to identify operationalized definitions and measures of alert fatigue or alert-related metrics.

METHODS: Systematic reviews reporting at least one alert-related metric or measure/operationalization of alert fatigue for physician-directed electronic alerts were included. The Cochrane Library, Embase, and PubMed were searched from database start to 2024. The Revised Assessment of Multiple Systematic Reviews was used to assess study quality and risk of bias. Data were synthesized narratively and with descriptive statistics.

RESULTS: A total of 22 studies were included in the review. Studies reported between 1 and 11 alert metrics. Studies were most often of medium quality. Reporting of primary study characteristics was frequently judged to be insufficient. Only one article reported an operational definition of alert fatigue. The most common alert metrics were quantity, override rate, and acceptance rate.

DISCUSSION: Alert fatigue measurement methods are not clearly or consistently defined in systematic reviews related to alert fatigue in clinical decision support. Reporting of other primary study characteristics is often limited. We recommend that future efforts use a significant, sustained decrease in appropriate alert response rates from an established baseline as a measure of alert fatigue.