About

Sean Hennessy, PharmD, PhD, is a Professor of Epidemiology in Biostatistics and Epidemiology at the Perelman School of Medicine, University of Pennsylvania. He is a Senior Fellow at the Leonard Davis Institute of Health Economics, a Fellow at the Institute on Aging, and a Senior Scholar at the Center for Clinical Epidemiology and Biostatistics. He is also the Founding Director of the Center for Real-World Effectiveness and Safety of Therapeutics (CREST) at the University of Pennsylvania. His research evaluates the real-world effectiveness and safety of prescription drugs using healthcare data, with a focus on serious health consequences of drug-drug interactions involving high-risk drugs such as anticoagulants, diabetes treatments, and medications for opioid use disorder. His work has contributed to understanding the survival benefits of potassium supplements in users of loop diuretics and statins in relation to outdoor temperatures, as well as evaluating drug utilization review programs and their impact on prescribing practices. Additionally, he co-led studies demonstrating the effectiveness of the Japanese encephalitis vaccine, which has led to immunization efforts in several countries, and developed innovative research designs for studying exposures with marked time trends. Dr. Hennessy has served in leadership roles within NIH, FDA, and international organizations, and has been recognized with numerous awards, including election to the National Academy of Medicine.

Research topics

• Emergency medicine
• Medicine
• Internal medicine

Selected publications

• Impact of empiric potassium supplementation on mortality, sudden cardiac arrest and stroke in furosemide initiators

  British Journal of Clinical Pharmacology · 2026-05-03

  articleOpen access

  AIM: A prior non-randomized study suggests that potassium supplementation may improve survival among furosemide initiators, and a randomized trial suggests that salt substitutes containing potassium might lower stroke risk. We conducted a retrospective cohort study using health-care data to confirm or refute these associations among new users of furosemide. METHODS: The exposure of interest was empiric potassium dispensing (yes/no) concurrent with furosemide initiation. Outcomes were all-cause mortality, sudden cardiac arrest/ventricular arrhythmia (SCA/VA), and stroke. Primary as-started and secondary as-treated analyses were performed with Cox proportional hazards regression. We used inverse probability of treatment weighting (IPTW) to control for confounding, with weights calculated from high-dimensional propensity scores. RESULTS: We identified 511 462 and 320 703 initiators of furosemide <40 and ≥40 mg/day with 21.5% and 35.3%, respectively, starting empiric potassium supplementation. In initiators of furosemide <40 mg/day with (vs. without) empiric potassium, as-started IPTW-hazard ratios (HRs) were 1.02 (95%CI 1.01-1.04) for death, 1.00 (0.94-1.04) for SCA/VA, and 1.03 (1.00-1.06) for stroke. Similarly, in initiators of furosemide ≥40 mg/day with (vs. without) empiric potassium, as-started IPTW-HRs were 1.02 (1.00-1.03) for death, 0.98 (0.94-1.03) for SCA/VA, and 1.01 (0.98-1.04) for stroke. CONCLUSION: We did not observe associations suggesting a clinically meaningful effect of empiric potassium supplementation among furosemide users. However, given the high prevalence of furosemide use among highly heterogeneous patient populations, a large pragmatic trial may be warranted to more definitively evaluate the potential benefits and harms of empiric potassium supplementation among furosemide initiators.

  PublisherDOI

• Causal inference for evaluating prescription opioid abuse using trend‐in‐trend design

  UNC Libraries · 2025-07-23

  articleOpen access

  PURPOSE: One response to the opioid crisis in the United States has been the development of opioid analgesics with properties intended to reduce non-oral use. Previous evaluations of abuse in the community have relied on population averaged interrupted time series Poisson models with utilization offsets. However, competing interventions and secular trends complicate interpretation of time-series analyses. An alternative research design, trend-in-trend, accounts for heterogeneity in per capita opioid dispensing and unmeasured time-varying confounding, which provides a causal evaluation, provided that underlying assumptions are met. METHODS: Trend-in-trend can be modeled using a logistic regression framework. In logistic regression, exposure was any product-specific outpatient dispensing by three-digit ZIP code and calendar quarter, for 22 opioids. The outcome was any product-specific abuse case ascertained from poison centers and drug treatment programs, covering 94% of the US population, between July 2009 and December 2016. Product-specific odds ratios compared places without dispensing with places with any dispensing; the causal contrast represents the odds of product-specific abuse in the community given exposure. RESULTS: Dispensing of new and low-volume opioids varied considerably across the country, with no region showing high of all products. Of 22 opioids analyzed, the three with approved labeling as intended to deter abuse ranked near the lowest in both absolute (population-adjusted rates: 1.7, 0.9, and 8.2 per million people per quarter, respectively) and relative measures (trend-in-trend ORs: 1.96, 1.79, 1.69, respectively). CONCLUSIONS: Postmarketing studies of prescription opioid abuse may benefit by evolving from unadjusted surveillance rates to a causal inference approach.

  PublisherDOI

• Characterizing Treatment Effect Heterogeneity Using Real‐World Data

  Clinical Pharmacology & Therapeutics · 2025-03-06 · 15 citations

  reviewOpen accessSenior author

  Characterizing heterogeneity of treatment effects (HTE) is a fundamental goal of pharmacoepidemiology, addressing why medications work differently across patient populations. This paper reviews state-of-the-art methods for studying HTE using real-world data (RWD), which offer larger study sizes and more diverse patient populations compared to randomized clinical trials. The paper first defines HTE and discusses its measurement. It then examines three leading approaches to studying HTE: subgroup analysis, disease risk score (DRS) methods, and effect modeling methods. Subgroup analyses offer simplicity, transparency, and provide insights into drug mechanisms. However, they face difficulties in resolving which subgroup or combination of characteristics should be the basis for clinical decision making when multiple effect modifiers are present. DRS methods address some of these limitations by incorporating multiple patient characteristics into a summary score of outcome risk but may obscure insights into mechanisms. Effect modeling methods directly predict individual treatment effects, offering potential for precise HTE characterization, but are prone to model misspecification and may not provide mechanistic insights. The methods each have tradeoffs. Subgroup analysis is straightforward but can lead to spurious associations and does not account for multiple characteristics at once. DRS methods are relatively simple to implement and clinically useful, but may not completely describe HTE or provide mechanistic insight. Effect modeling approaches have great potential for characterizing HTE but are still being developed. Understanding HTE is essential for personalizing treatment strategies to improve patient outcomes. Researchers must weigh the strengths and limitations of each approach when using RWD to study HTE.

  PublisherOA PDFDOI

• 1163-P: Disparities in Glucagon-Like Peptide 1 Receptor Agonist (GLP-1RA) Utilization in Pediatric Type 2 Diabetes (T2D)

  Diabetes · 2025-06-13 · 1 citations

  article

  Introduction and Objective: Disparities in GLP-1 RA use by race/ethnicity and socioeconomic status are documented in adult T2D. To assess if similar disparities occur in pediatric T2D, the association between GLP-1 RA prescriptions and race/ethnicity amongst Medicaid-insured youths with T2D was examined. Methods: A cross-sectional study of youths aged 10-17 years (y) with T2D (2021-2022) was conducted using the Merative MarketScan Medicaid Database. Multivariable logistic regression was used to assess associations of GLP-1 RA prescription ever prescribed (yes/no) with race/ethnicity and potential confounders (age, sex, obesity, co-morbidities, and use of metformin or insulin). Results: Among 4000 youths (57.7 % female, 33.1% NH White, 47.2% NH Black, 13.0% Hispanic, 6.7% Other, mean age: 14.9 y [SD 1.9]), GLP-1 RAs were prescribed in 23.3% (liraglutide 17.5%, dulaglutide 4.4%, exenatide 2.3%, semaglutide 2.2%) and less frequently than metformin (73.8%) and insulin (64.0%). After covariate adjustment, Hispanic ethnicity, but not Black race, was associated with lower odds of GLP-1 RA prescription compared to NH White (OR 0.57 [95% CI 0.43, 0.76], p &amp;lt; 0.001) (Figure 1). Conclusion: Among Medicaid-insured youths with T2D, Hispanic youths were less likely to be prescribed GLP-1 RAs. Developing strategies to ensure equitable access to novel treatments in pediatric T2D are needed. Disclosure P.Y. Chu: None. A. Kelly: None. M. Vajravelu: None. S. Hennessy: Consultant; Novo Nordisk, AstraZeneca, Urovant Sciences, i2o Therapeutics, Basilea, Eli Lilly and Company, Balance Opthalmics, Inc, Applied Therapeutics, GlaxoSmithKline plc, Lycos Therapeutics. S. Amaral: Consultant; Bristol-Myers Squibb Company. Funding National Institute of Diabetes and Digestive and Kidney Diseases (F32DK138739); National Institute of General Medical Sciences (T32GM075766)

  PublisherDOI

• Effectiveness of Empagliflozin vs Dapagliflozin for Kidney Outcomes in Type 2 Diabetes

  JAMA Internal Medicine · 2025-01-21 · 12 citations

  articleOpen access

  Importance: No large randomized clinical trial has directly compared empagliflozin with dapagliflozin, leaving their comparative effectiveness regarding kidney outcomes unknown. Objective: To compare kidney outcomes between initiation of empagliflozin vs dapagliflozin in adults with type 2 diabetes who were receiving antihyperglycemic treatment. Design, Setting, and Participants: This target trial emulation used nationwide, population-based routinely collected Danish health care data to compare initiation of empagliflozin vs dapagliflozin in adults with type 2 diabetes who received antihyperglycemic treatment between June 1, 2014, and October 31, 2020. Data were analyzed from October 2023 to August 2024. Persons were followed up until an outcome, emigration, death, 6 years, or December 31, 2021, whichever occurred first. Exposure: Initiation of empagliflozin vs dapagliflozin. Main Outcomes and Measures: Outcomes included acute kidney injury, incident chronic kidney disease (stages G3 to G5 or stage A2 or A3), and progression of chronic kidney disease (≥40% decrease in estimated glomerular filtration rate from baseline). Risks of kidney outcomes were estimated in intention-to-treat and per-protocol analyses using an Aalen-Johansen estimator that adjusted for 56 potential confounders and considered death as a competing event. Results: A total of 32 819 individuals who initiated treatment with empagliflozin and 17 464 with dapagliflozin were included (median [IQR] age, 63 [54-71] years; 18 872 female individuals [37.5%]; median [IQR] estimated glomerular filtration rate, 88 [73-104] mL/min/1.73 m2). After weighting, all measured covariates were well balanced between the groups. In intention-to-treat analyses, people who initiated treatment with empagliflozin and dapagliflozin exhibited comparable 6-year risks of acute kidney injury (18.2% vs 18.5%; risk ratio, 0.98; 95% CI, 0.91-1.06), chronic kidney disease stages G3 to G5 (11.8% vs 12.1%; risk ratio, 0.97; 95% CI, 0.89-1.05), chronic kidney disease stage A2 or A3 (14.8% vs 14.3%; risk ratio, 1.04; 95% CI, 0.93-1.15), and progression of chronic kidney disease (5.3% vs 5.7%; risk ratio, 0.94; 95% CI, 0.56-1.58). The primary analyses were supported by corresponding per-protocol analyses. Conclusions and Relevance: The results of this cohort study suggest that people with type 2 diabetes who initiated treatment with empagliflozin and dapagliflozin had comparable long-term kidney outcomes.

  PublisherOA PDFDOI

• Stimulant Overdose Prediction Model for Medicaid-Insured Persons

  JAMA Health Forum · 2025-09-19

  articleOpen accessSenior authorCorresponding

  Importance: Overdoses involving methamphetamines and cocaine have increased in recent years. Identification of individuals at highest risk could facilitate the implementation of evidence-based interventions to reduce overdose risk. Objective: To develop and internally validate a model that predicts hospitalization or emergency department (ED) treatment for stimulant-involved overdose among the Medicaid-insured population. Design, Setting, and Participants: This was a retrospective case-cohort study using Medicaid claims data from 2016 to 2019 (development) and 2020 (validation) for all Medicaid enrollees age 15 years or older with a cocaine- or other stimulant-involved overdose. A subcohort was created using a simple random sample of the full cohort of all cases. Within the full cohort, cases were identified as those having any inpatient or ED encounter for stimulant-involved overdose during the following year. A case-cohort sample was obtained for each calendar year from 2016 to 2020, each with a subcohort size of 100 000. Each individual contributed only 1 case event (for an individual with multiple overdoses, only the first eligible was selected). For each of the 4 overdose outcomes, a predictive weighted Cox model was first developed among enrollees of sampling years 2016 to 2019 (development set), and its performance was evaluated in our test set of 2020. The prediction models were first developed in November 2023, and the model fairness assessment was performed in April to May 2025. Interventions or Exposures: Individual-level candidate predictors were demographic characteristics, enrollment, health care utilization, and other clinical variables. Area-level variables included social, economic, housing, and demographic characteristics data from the American Community Survey, rural-urban classification, Social Deprivation Index, retail opioid dispensing rates, and health resources. Main Outcomes and Measures: Four types of stimulant-involved overdose associated with hospitalization or ED treatment: cocaine-involved overdose, (1) involving an opioid or (2) not involving an opioid; or methamphetamine-, ecstasy-, or other psychostimulant-involved overdose (hereafter, other stimulant), (3) involving an opioid or (4) not involving an opioid. Results: The analysis included 78 795 enrollees with cocaine- and other stimulant-involved overdose (mean [SD] age, 42.2 [13.7] years; 33 304 [42%] female and 45 491 [58%] male individuals). Weighted Cox regression prediction models showed good calibration and high discriminatory performance (Harrell C statistic): cocaine-involved overdose, with (0.923) or without (0.902) an opioid; other stimulant-involved overdose, with (0.909) or without (0.868) an opioid. For cocaine-involved overdose with opioids, previous individual opioid use disorder diagnosis or cocaine use disorder diagnosis played the largest role in overdose risk prediction. For cocaine-involved overdose without opioids, previous cocaine use disorder diagnosis and area-level income inequality and housing variables contributed most to prediction. For other stimulant-involved overdose with opioids, previous opioid use disorder diagnosis and area-level percentage of those living with a disability contributed most to prediction. For other stimulant-involved overdoses without opioids, previous stimulant-related disorder and area-level proportion of individuals receiving Supplemental Nutrition Assistance Program contributed most to prediction. Conclusions and Relevance: This case-cohort study found that readily available data can be used to identify those at high risk of hospitalization or ED visit for cocaine- or stimulant-involved overdose. These individuals would likely benefit most from evidence-based interventions and awareness of risk factors for overdose.

  PublisherOA PDFDOI

• Real‐World Data and Real‐World Evidence in Regulatory Decision Making: Report Summary From the Council for International Organizations of Medical Sciences (<scp>CIOMS</scp>) Working Group <scp>XIII</scp>

  Pharmacoepidemiology and Drug Safety · 2025-03-01 · 12 citations

  reviewOpen access1st authorCorresponding

  Data from sources other than traditional randomized clinical trials are known as real-world data (RWD), and the evidence derived from the review and analysis of RWD is known as real-world evidence (RWE). RWD and RWE are used increasingly throughout the lifecycle of medicinal products to provide evidence about their effectiveness and safety. Recent regulatory guidance about RWE and approvals based on the use of RWE to demonstrate beneficial effects of products have created an urgency to develop generally accepted processes that promote trust in the evidence-generation process. A recent report from a working group of the Council for International Organizations of Medical Science (CIOMS) describes the use of RWE for decision making in the lifecycle of medical products, describes RWD and data sources, discusses key scientific considerations in the generation of RWE, and discusses ethical and governance issues related to the use of RWD. This paper provides a high-level summary of this report. More work remains to be done to globally harmonize practices and guidance for using RWD and RWE for regulatory decision making, thereby maximizing the benefits they can bring to patient care and public health.

  PublisherOA PDFDOI

• Trends in Methadone Use for Pain and Opioid Use Disorder Among Medicaid Enrollees

  JAMA Health Forum · 2025-11-21 · 1 citations

  articleOpen accessSenior author

  This cross-sectional study aims to quantify methadone use for opioid use disorder in the Medicaid program and assesses buprenorphine use as a possible shift between medications for opioid use disorder.

  PublisherOA PDFDOI

• Evaluation of Drug–Drug Interactions in Pharmacoepidemiologic Research

  Pharmacoepidemiology and Drug Safety · 2025-01-01 · 10 citations

  reviewOpen access

  Drug-drug interactions (DDIs) represent a significant concern for clinical care and public health, but the health consequences of many DDIs remain largely underexplored. This knowledge gap underscores the critical need for pharmacoepidemiologic research to evaluate real-world health outcomes of DDIs. In this review, we summarize the definitions commonly used in pharmacoepidemiologic DDI studies, discuss common sources of bias, and illustrate through examples how these biases can be mitigated.

  PublisherOA PDFDOI

• Switching From Aspirin Monotherapy After Noncardioembolic Stroke: A Systematic Review and Network Meta-Analysis

  Stroke · 2025-12-05 · 1 citations

  reviewOpen access

  BACKGROUND: Patients who experience an ischemic stroke while on aspirin therapy present a clinical dilemma about optimal long-term secondary prevention. While switching to an alternative antithrombotic agent is often considered, the effectiveness of switching remains uncertain. METHODS: We conducted a systematic review and network meta-analysis of randomized controlled trials reporting outcomes among patients with ischemic stroke while on aspirin who were either continued on aspirin or switched to an alternative antithrombotic therapy. Alternative antithrombotics included 2 trials of vitamin K antagonists (n=478), 3 trials of dual antiplatelet therapy (n=2229), 3 trials of direct oral anticoagulant (n=2660) monotherapy, and 1 trial of low-dose direct oral anticoagulant added onto aspirin (n=92). We excluded trials of patients with only short-term outcomes of 90 days or fewer, or those with cardioembolic sources of stroke requiring anticoagulation. Our primary outcome was recurrent ischemic stroke; the secondary outcome was a composite of ischemic stroke, myocardial infarction, and vascular death (or all-cause mortality). Outcomes reflect recurrent events measured over a median of ≈19 months (range 11-42 months). In the network portion of this meta-analysis, surface under the cumulative ranking curve rankings and pairwise meta-analyses were used to evaluate and compare the relative efficacy of alternative antithrombotic medications. RESULTS: ²=0). For the composite secondary outcome, 6 studies contributed data, yielding a pooled relative risk of 0.89 (95% CI, 0.72-1.10). In the network meta-analysis, dabigatran, apixaban, and aspirin+low-dose rivaroxaban ranked the highest among antithrombotic alternatives to aspirin, though none were significantly better than continuing aspirin. Rankings were similar when based on posterior estimates from the clinical trials and when using predictive distributions that incorporate between-study variance (ie, expected performance in future settings). CONCLUSIONS: Among patients experiencing ischemic stroke while taking aspirin, switching to an alternative antithrombotic therapy was not conclusively associated with a reduction in recurrent stroke and composite cardiovascular events. Trials are needed to determine whether specific antithrombotic strategies meaningfully improve outcomes in this high-risk population.

  PublisherOA PDFDOI

Recent grants

• NIH Grant K23AG000987

  NIH · $642k · 2006

• NIH Grant R01HL076697

  NIH · $2.8M · 2009

• Enhancing the Utility of the Trend-in-Trend Research Design

  NIH · $2.2M · 2019–2024

• Drug-Drug Interactions Involving Antidiabetic Agents

  NIH · $2.4M · 2014–2018

• NIH Grant F32HS000066

  NIH · $64k

Frequent coauthors

• Warren B. Bilker

  University of Pennsylvania

  218 shared

• Charles E. Leonard

  University of Pennsylvania

  166 shared

• Brian L. Strom

  Rutgers, The State University of New Jersey

  131 shared

• Colleen M. Brensinger

  University of Pennsylvania

  92 shared

• James Flory

  Memorial Sloan Kettering Cancer Center

  88 shared

• Stephen E. Kimmel

  University of Florida

  52 shared

• Craig Newcomb

  43 shared

• Todd A. Miano

  University of Pennsylvania

  41 shared

Awards & honors

• 1998 Stanley A. Edlavitch Award for Best Abstract Submitted…
• 2002 Saul Winegrad Award for Outstanding Dissertation in Epi…
• 2005 Young Alumnus Award, University of the Sciences in Phil…
• 2008 Leon I Goldberg Young Investigator Award, American Soci…
• 2013 Samuel Martin Health Evaluation Sciences Research Award…