Publications

BACKGROUND: The aim of this study was to determine whether dental providers wrote fewer prescriptions for opioid-containing medications and more prescriptions for non-opioid analgesics after taking a continuing education course that targeted both knowledge about an American Dental Association-endorsed guideline on the management of acute dental pain and challenges in shared decision-making.

METHODS: The implementation strategy comprised a prerecorded 1-h video continuing education course and supplementary materials that were previously shown to increase knowledge about shared decision-making. Using propensity score matching, we matched 420 dentists and dental specialists who took the continuing education course to 4,200 providers who had not. We used regression analyses to compare learners with their propensity score-matched controls on their change in opioid prescribing and change in non-opioid analgesic prescribing from the 6 mo before to the 6 mo after course completion.

RESULTS: Providers who took the continuing education course decreased the number of opioid prescriptions they wrote by 0.60 prescriptions more than providers who did not take the continuing education course (B = -0.60; 95% confidence interval [CI] -1.07, -0.13; t = -2.50; P < 0.01). Among providers who decreased their prescribing by 3 or more prescriptions, a greater percentage took the continuing education course. There was no difference in non-opioid analgesic prescribing between providers who took the continuing education course and providers who did not (B = -0.10; 95% CI -0.87 0.68; t = -0.25, ns).

CONCLUSION: Equipping dental providers with skills in shared decision-making to use in conversations with patients about approaches to acute pain management may enable them to decrease the number of opioid prescriptions they write more than providers who are not exposed to these skills.Knowledge Transfer Statement:The results of this study can be used by groups and organizations seeking to improve dental providers' adherence to the guideline on managing acute dental pain following simple and surgical tooth extraction or toothache.

BACKGROUND/OBJECTIVES: Preclinical evidence suggests beta blockers may reduce cartilage degradation and delay knee osteoarthritis (OA) progression. While beta blockers are widely used in patients with hypertension, their potential role in preventing total knee arthroplasty (TKA) is unclear. Therefore, we assessed the association between beta blocker use and TKA in knee OA patients with hypertension.

METHODS: We conducted a nested case-control study using a nationally representative sample of Medicare beneficiaries with newly diagnosed knee OA and prevalent hypertension from 2011 to 2020. Beneficiaries who underwent TKA were defined as cases, while those without TKA were defined as controls. Cases and controls were matched at a 1:4 ratio based on pre-specified criteria using incident density sampling. We measured binary (exposed/unexposed) and cumulative exposure of beta blockers during 6 months before TKA using total standardized daily doses (TSDD) for each patient, categorized as unexposed (0), < 1-200, 201-400, 401-600, 601-900, > 900. Confounding was addressed using propensity score adjustment and stratification for the binary exposure and direct covariate adjustment for cumulative exposure in conditional logistic regression models.

RESULTS: We included 30 338 beneficiaries with TKA and 106 145 matched controls. The mean age (SD) was 74.4 (5.5) years, and 67.1% were women in both groups. There was no significant association between beta blocker use and odds of TKA (adjusted OR [aOR] 1.01; 95% CI, 0.97-1.02) compared with unexposed individuals. Smilarly, no cumulative exposure category was associated with TKA risk (TSDD: < 1-200 [aOR, 1.01; 95% CI,0.97-1.04]; TSDD: 201-400 [aOR 1.00; 95% CI, 0.96-1.05]; TSDD: 401-600 [aOR, 1.02; 95% CI, 0.96-1.08]; TSDD: 601-900 [aOR 0.94; 95% CI, 0.87-1.00]; and, TSDD: > 900 [aOR 0.99; 95% CI, 0.91-1.08]), compared with the unexposed group.

CONCLUSION: We found no evidence to support that beta blocker exposure reduces the likelihood of TKA.

OBJECTIVES: This study aimed to describe changes in psychotropic medication use over time in commercially insured children with autism spectrum disorder (ASD) across age groups and characterize the comorbidity burden in patients with more complex treatment regimens.

METHODS: Using deidentified administrative claims from the Workpartners Research Reference Database, we conducted a retrospective cohort study of employee dependents aged 0-17 years with ASD followed for 3 years. Psychotropic medication use was analyzed across three age groups (0-4, 5-9, and 10-17 years). In a subgroup with high treatment complexity, defined as polypharmacy (≥3 drug classes) and/or antipsychotic use, the prevalence of various co-occurring conditions associated with ASD was also described.

RESULTS: Among 2747 children with ASD, psychotropic medication use and polypharmacy were more common in older age groups. At Year 1, 32.8% of children aged 10-17 used ≥2 drug classes concurrently, compared with 0.9% and 15.3% in the 0-4 and 5-9 age groups, respectively. From Year 1 to Year 3, medication use increased in younger children but declined in the 10-17 age group. High treatment complexity was observed in 20.5% of children (n = 562) over the entire 3-year study period, most frequently in the 10-17 age group. A higher prevalence of comorbidities, including attention-deficit hyperactivity disorder, mental health conditions, conduct disorders, and irritability and agitation, was observed in those with high treatment complexity compared with those without.

CONCLUSIONS: Pharmacologic treatment patterns varied by age in children with ASD, and higher treatment complexity was associated with more frequent diagnoses of co-occurring psychiatric and behavioral conditions. Further understanding of longitudinal treatment trajectories should be explored in future research, such as by contextualizing treatment changes with symptom assessment and evaluating the social impact of treatment complexity.

BACKGROUND: Hospitalization for alcohol use disorder (AUD) offers an opportunity to initiate evidence-based medications for alcohol use disorder (MAUDs).

OBJECTIVE: To describe patterns and factors associated with hospital initiation of MAUD.

DESIGN: Retrospective cohort study.

SETTING: Veterans Health Administration (VHA).

PARTICIPANTS: Veterans hospitalized with a primary diagnosis of AUD in 2022 or 2023.

MEASUREMENTS: Patients had MAUD initiated as an inpatient or within 7 days of discharge. Logistic regression models estimated the predicted probabilities of MAUD initiation based on hospital fixed effects and demographic and clinical characteristics.

RESULTS: Among 29 041 hospitalizations for AUD of veterans without MAUD at baseline in 142 hospitals (median age, 55 years; 94% male), in 8932 hospitalizations (30.8%), MAUD was initiated as an inpatient or within 7 days; MAUDs were naltrexone (57.9%), acamprosate (16.5%), and injectable naltrexone (13.9%). Of MAUD initiations, 6221 (69.6%) were during an inpatient stay and the rest were within 7 days. Of the 6221 inpatient initiations, 97.7% had a prescription for MAUD within 30 days after discharge. In adjusted analyses, MAUD initiation was more likely for hospitalizations with a specialty addiction consultation and those receiving psychiatry versus medicine service. Initiation of MAUD was less likely for persons aged 65 years or older, men, American Indian or Alaska Native versus White veterans, frail veterans, veterans diagnosed with opioid use disorder, and those in the intensive care unit. The median hospital-level rate of MAUD initiation was 29.9% (IQR, 22.6% to 36.3%).

LIMITATION: Generalizability to other health care systems.

CONCLUSION: Within the VHA, 30% of hospitalizations for AUD resulted in MAUD initiation as an inpatient or within 7 days of discharge, with substantial variation across hospitals and patient demographic and clinical factors. These data indicate a need to identify and disseminate successful hospital-based strategies to increase prescribing of MAUD.

PRIMARY FUNDING SOURCE: U.S. Department of Veterans Affairs and National Institute on Aging.

BACKGROUND: Opioid overdose remains a leading cause of preventable death in the United States. Existing approaches to identify individuals at elevated risk rely on imprecise rule-based criteria that misclassify patients' risk of this serious health outcome. Machine learning (ML) algorithms can help improve prediction performance and can be combined with electronic health record (EHR) interventions to reduce overdose risk.

OBJECTIVE: The Machine Learning Prediction and Reducing Overdoses With EHR Nudges (mPROVEN) clinical trial integrates a validated ML overdose risk model with behavioral economics-informed EHR nudges to test whether the combination improves evidence-based prescribing behaviors associated with lower overdose risk and, ultimately, reduces overdose among elevated-risk patients.

METHODS: mPROVEN is a pragmatic cluster randomized controlled trial conducted in primary care practices within a large multistate integrated health system. Eligible patients are adults (≥18 years) identified by the ML algorithm as having elevated overdose risk and seen at a primary care visit during the study period. Primary care practices serve as the unit of randomization and will be randomized into three arms: (1) usual care; (2) elevated risk flag only, where clinicians see a noninterruptive EHR flag indicating elevated overdose risk; and (3) elevated risk flag + nudges, in which active choice and accountable justification alerts are embedded within the EHR in addition to the elevated risk flag. The trial will enroll a target cohort of 800 patients for the primary analysis. The intervention period is 4 months (or until the study ends, whichever occurs later). The primary outcome is a 3‑point composite measure of safer opioid prescribing at 4 months, awarding 1 point each for active naloxone prescription, average opioid dosage of 50 morphine milligram equivalents per day or less, and absence of opioid-benzodiazepine overlap. Secondary outcomes include the composite outcome at 6 months, individual score components, and all-cause and overdose-specific emergency department or inpatient visits. Outcomes will be compared across study arms using an intention‑to‑treat approach with linear mixed‑effects models accounting for clinic-level clustering.

RESULTS: Funded by the National Institutes of Health, in June 2022, enrollment began on March 10, 2025. Enrollment for the primary analysis cohort (n=798) was completed in May 2025 with additional participants enrolled for secondary analyses through December 2025 (n=1662). Primary cohort analyses began in January 2026, and results are expected by mid-2027.

CONCLUSIONS: The mPROVEN study is among the first pragmatic randomized controlled trials to integrate ML‑based opioid overdose risk prediction with behavioral nudges within a large health system EHR. By combining advances in data science and behavioral economics, the study aims to reduce opioid overdose risk in primary care using a scalable and low-touch intervention to address a high-priority public health issue.

TRIAL REGISTRATION: ClinicalTrials.gov NCT06806163; https://clinicaltrials.gov/study/NCT06806163.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/94007.

INTRODUCTION: Higher buprenorphine maintenance doses (>24 mg daily) may be more effective in improving opioid use disorder (OUD) treatment outcomes in the era of fentanyl predominance. Evidence on maintenance dose trends remains limited, especially among vulnerable populations, who are disproportionately affected by opioid overdose deaths. The objective of this study was to describe trends in maintenance dose of buprenorphine for OUD and the association of social vulnerability with maintenance dose.

METHODS: We identified buprenorphine treatment episodes initiated between January 2019 and June 2021 using the IQVIA Longitudinal Prescription database. Episodes were assigned to a maintenance dose category of <16, 16-24, or >24 mg, to reflect dosages lower than, consistent with, or higher than the guideline-recommended target dose range, respectively. County-level social vulnerability was measured with the Minority Health Index (MHI). We used multinomial logistic regression with generalized estimating equations to test the association between MHI (stratified into quartiles) and maintenance doses <16 mg and >24 mg (with 16-24 mg as the reference group), adjusting for patient, geographic, and time characteristics.

RESULTS: Of 1,044,460 treatment episodes among 543,326 individuals (mean [SD] age 41.9 [12.6] years, 43% female), the most common buprenorphine maintenance dose category was 16-24 mg (62.7%), followed by <16 mg (34.5%), then >24 mg (2.8%). The median (IQR) episode duration was 64 (109) days. The proportion of episodes in the <16 mg category increased from 34.1% in 2019 to 39.2% in 2021, whereas prevalence of the remaining categories decreased. A greater proportion of episodes in the >24 mg category were in rural versus urban counties; the magnitude of this difference increased over time. Relative to 16-24 mg, maintenance dose >24 mg was more likely among individuals in the most vulnerable MHI quartile compared to the least vulnerable quartile (aOR 1.28, 95% CI 1.19-1.38).

CONCLUSION: During a period of growing evidence supporting higher buprenorphine maintenance doses, the prevalence of treatment episodes with maintenance dose <16 mg increased. Individuals in the highest social vulnerability quartile tended to receive higher doses, suggesting that some higher-risk groups may receive more intensive treatment, even as important gaps remain. These results can inform efforts targeting equitable, high-quality buprenorphine prescribing.

PURPOSE: We sought to describe how often and circumstances in which supply chain disruptions were associated with outpatient drug shortages within the Veterans Health Administration (VHA).

METHODS: We conducted a descriptive analysis of VHA purchasing data for drugs used to treat chronic conditions for outpatients with a supply chain report from 2017 to 2020. In primary analyses, a VHA drug shortage was defined as a ≥ 10% absolute decrease in percentage of doses ordered that were filled by the wholesaler and/or a ≥ 10% relative decrease in total number of doses filled, comparing the 3 months after the reporting date with the 6 months before. We also examined longitudinal ordering and filling data over 12 months before and after the reporting date by whether the medication resulted in a shortage to VHA.

RESULTS: Of 64 medications with supply chain disruptions, 67% (n = 43) resulted in a shortage to VHA. Bivariable analyses did not identify covariates significantly associated with VHA experiencing a shortage. For medications with a shortage, dosage units ordered sharply increased over the 4 months before the reporting date, peaked at the reporting date (336.0%), and then generally decreased over the remaining 11 months. The monthly dosage units filled slowly declined leading up to the reporting date, dropped more quickly to 60% at two months post-reporting date, and then increased.

CONCLUSIONS: Among ambulatory-focused medications for chronic conditions, a high proportion of those with supply chain disruptions were associated with shortages to VHA. Sharp increases in medication ordering may serve as an early signal of shortages.

BACKGROUND: Guidelines on primary prevention of atherosclerotic cardiovascular disease (ASCVD) recommend considering risk enhancing factors (REFs) to inform decisions on use of lipid-lowering therapies for the 44 million Americans with borderline or intermediate estimated ASCVD risk.

OBJECTIVE: To quantify REF burden and estimate whether REFs are associated with higher likelihood of statin use.

DESIGN: Cross-sectional using National Health and Nutrition Examination Survey pooled 2015 to March 2020.

PARTICIPANTS: Adults aged 40-75 without known ASCVD.

MAIN MEASURES: Nine REFs were measurable in NHANES including family history of premature ASCVD, rheumatoid arthritis, metabolic syndrome, premature menopause, chronic kidney disease and biomarkers of hypercholesteremia, hypertriglyceridemia, elevated low-density lipoprotein cholesterol and elevated C-reactive protein. Prevalence of REFs and association with statin use were calculated overall and across ASCVD treatment categories based on diabetes and 10-year ASCVD risk.  KEY RESULTS: In the sample of 3,111 participants (mean age 56 years; 52.6% female) weighted to represent 115.7 million US adults, 77% had at least one REF and 28% had at least three. The most common REFs were elevated high sensitivity C-reactive protein (49.6%) metabolic syndrome (48.3%), and hypertriglyceridemia (18.9%). The presence of any REF was associated with a 2.17 (95% CI, 1.42-3.33) greater odds of statin use. Metabolic syndrome, family history of premature ASCVD, hypertriglyceridemia and hypercholesteremia were associated with greater odds of statin use (aORs ranging from 1.5 to 2.3). The presence of any REF was associated with higher likelihood of statin use in participants with low (< 5%), intermediate (7.5-19%), and high ASCVD risk (≥ 20%), but not borderline ASCVD risk (5-7.4%) or diabetes categories.

CONCLUSIONS: REFs are highly prevalent and inconsistently associated with statin use. Achieving the potential benefit of individualizing ASCVD risk estimates will require clearer guidance on when and how to incorporate REFs into primary prevention prescribing decisions.