About

Andrew R. Zullo is an Associate Professor of Epidemiology and Health Services, Policy and Practice at Brown University. His research focuses on improving medication and vaccine use for older adults, with particular attention to optimizing outcomes such as physical and cognitive function. He conducts research in geriatric pharmacoepidemiology and health services research, specializing in studying the functional outcomes of medication use in institutional post-acute care and long-term care settings. Dr. Zullo applies pharmacoepidemiologic, comparative effectiveness and safety, and causal inference methodologies to large datasets, including administrative claims and electronic health records, to inform medication safety and effectiveness in older populations. His work also includes medication-related evidence synthesis projects, aiming to enhance understanding of medication utilization, safety, and outcomes among older adults, especially in nursing home and post-acute care contexts.

Research topics

• Medicine
• Immunology
• Political Science
• Computer Science
• Internal medicine
• Pediatrics
• Artificial Intelligence
• Environmental health
• Intensive care medicine
• Management science
• Engineering
• Virology

Selected publications

• Target-Dose Versus Below-Target-Dose ACE Inhibitors and Lower Risk of Kidney Failure in U.S. Veterans with HFrEF

  European Journal of Heart Failure · 2026-03-06 · 1 citations

  article

  AIMS: In patients with heart failure with reduced ejection fraction (HFrEF), target-dose (vs. below-target-dose) angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) improve clinical outcomes but worsen kidney function. Less is known about their effect on kidney failure (KF), especially in those with advanced chronic kidney disease (CKD), the examination of which was the objective of our study. METHODS AND RESULTS: Of the 154,945 Veterans with HFrEF (EF≤40%) and no baseline KF, 134,046 were initiated on ACEIs (target-dose, n=37,667) and 20,899 were initiated on ARBs (target-dose, n=4017) during 2000-2018. While remaining blinded to study outcomes, we assembled two propensity score-matched cohorts: ACEI (N=70,860; target-dose, n=35,430) and ARB (N=7900; target-dose, n=3950), balanced on 76 baseline characteristics. Hazard ratios (95% CIs) associated with target doses were estimated for 5-year KF and all-cause mortality, up to December 31, 2023. In the ACEI cohort, target-dose was associated with a 18% lower risk of KF (HR, 0.82; 95% CI, 0.75-0.89) and a 6% lower risk of death (HR, 0.94; 95% CI, 0.92-0.97). Subgroup and spline analyses showed that while the KF association was significant for those with baseline eGFR <35 ml/min/1.73m2, the mortality association was significant for those with eGFR ≥35 ml/min/1.73m2. In the ARB cohort, target-dose had no association with outcomes. CONCLUSIONS: In patients with HFrEF, target-dose (vs. below-target-dose) ACEIs, but not ARBs, were associated with lower risk of KF, which was significant in those with advanced CKD. The survival benefit was modest and limited to those without advanced CKD.

  PublisherDOI

• Additional file 1 of Linkage of Medicare insurance claims to police-reported motor vehicle crashes: advancing traffic safety research in older adult populations

  Figshare · 2026-02-06

  articleOpen access

  Supplementary Material 1.

  PublisherDOI

• Additional file 1 of Linkage of Medicare insurance claims to police-reported motor vehicle crashes: advancing traffic safety research in older adult populations

  Figshare · 2026-02-06

  articleOpen access

  Supplementary Material 1.

  PublisherDOI

• Linkage of Medicare insurance claims to police-reported motor vehicle crashes: advancing traffic safety research in older adult populations

  Figshare · 2026-02-06

  otherOpen access

  Abstract Background Motor vehicle crashes (MVCs) are a leading cause of injury among adults aged 65 years and older (“older adults”). As the number of older drivers grows, it is increasingly important to understand clinical factors associated with an increased risk of MVC. A major barrier, however, is the lack of data. To address this, we linked two large-scale administrative databases, the New Jersey Safety and Health Outcomes (NJ-SHO) Data Warehouse, which contains information on all police-reported crashes in New Jersey from 2004 to 2019, and Medicare Fee-for-Service (FFS) insurance claims, which contains health care encounters and prescription drug dispensings among older adults in the United States over the same period. This paper explains the linkage process, describes selected work leveraging these data to study MVCs in older drivers, and highlights features and strengths of this linkage for future research. Methods The NJ-SHO–Medicare linkage was performed using categories of name (first and last), sex, age (birth and death date), and residence (state and ZIP code). Matches were ranked by quality and overall confidence. Results After comparing different match strategies, we accepted a match when (1) the name match quality was High or Medium and the age match was High or (2) the name, sex, and residence match categories were all High. Of the 2,722,773 individuals successfully linked, we accepted 2,661,782 matches (97.76% of individuals linked and 91.59% of those submitted for linkage). All accepted matches were Strong or Fair. Among accepted matches who enrolled in Medicare FFS in 2019, 342,422 (28.57%) were 65–69 years old, 619,437 (51.69%) were female, and 955,309 (79.72%) were non-Hispanic White. Only 29,561 (2.47%) experienced an MVC and 25,478 (2.13%) received a citation. The most prevalent clinical conditions ever diagnosed were cataracts (669,044; 55.83%); chronic pain, fatigue, and fibromyalgia (367,165; 30.64%); and glaucoma (287,420; 23.98%). Conclusions With extensive temporal and population coverage, the NJ-SHO–Medicare linkage supports studying the relationships between clinical exposures (e.g., medications ), driving events (e.g., crashes, citations) and medical care trajectories, which can help advance the driving safety of older adults and inform future efforts to integrate administrative data.

  PublisherDOI

• 26-A-19782-ACC SACUBITRIL/VALSARTAN UNDERUTILIZATION IN SKILLED NURSING FACILITIES AFTER A HEART FAILURE HOSPITALIZATION

  Journal of the American College of Cardiology · 2026-03-27

  articleSenior author
  PublisherDOI

• Concordance Between the Minimum Data Set Kidney Impairment I1500 Item and eGFR Records in Nursing Homes

  Journal of the American Medical Directors Association · 2026-04-02

  articleOpen accessSenior author

  OBJECTIVES: To evaluate the concordance between the Minimum Data Set (MDS) version 3.0 I1500 item and estimated glomerular filtration rate (eGFR) laboratory values for identifying kidney impairment among nursing home (NH) residents. DESIGN: A retrospective cohort study was conducted using data from 8 multistate, multifacility NH chains from January 1, 2018, to July 1, 2022. MDS 3.0 assessments with a complete I1500 item were linked to eGFR values measured on the assessment reference date or within 7 days prior. SETTING AND PARTICIPANTS: The study included NH residents with at least 1 MDS 3.0 assessment linked to a matching eGFR within a 7-day look-back window. METHODS: for the primary analysis and <45 for the secondary analysis. RESULTS: The study included 454,436 MDS assessments from 225,557 NH residents. Using an eGFR threshold of <60, agreement with the MDS I1500 item was 60.3% (kappa = 0.19), with 25.8% sensitivity and 92.3% specificity. At the <45 threshold, agreement rose to 71.8% (kappa = 0.22), with 29.9% sensitivity and 89.2% specificity. CONCLUSIONS AND IMPLICATIONS: The MDS 3.0 I1500 measure demonstrated fair agreement, low sensitivity, and high specificity for identifying kidney impairment compared with eGFR values. Cross-referencing federally mandated MDS data with eGFR data could improve kidney impairment identification and care planning in NHs.

  PublisherDOI

• Prompt and Intensive Antiviral Chemoprophylaxis in Nursing Home Influenza Outbreaks

  JAMA Internal Medicine · 2026-03-30

  articleOpen accessSenior authorCorresponding

  Importance: Influenza outbreaks in nursing homes (NHs) can cause high morbidity and mortality. Antiviral chemoprophylaxis with oseltamivir is recommended, yet optimal implementation strategies remain unclear. Objective: To examine whether initiating antiviral chemoprophylaxis for 70% or more of eligible NH residents within 2 days of influenza outbreak detection is associated with lower all-cause mortality and hospitalization at 14 and 30 days. Design, Setting, and Participants: Retrospective cohort study using a sequential cluster-randomized target trial emulation and randomize-censor-weight approach for influenza outbreaks (September 1, 2018-May 31, 2022) in 12 US NH corporations. Eligibility criteria were age 18 years or older, present on the outbreak-detection day, no antiviral use in the preceding 7 days, no influenza in the past 14 days, and complete baseline data. Residents were followed up until hospitalization or death, an NH discharge to a nonacute-care location, or the end of follow-up. Data were analyzed from February 2023 to January 2026. Exposures: Intensive antiviral chemoprophylaxis with oseltamivir (≥70% of eligible residents within 2 days of outbreak detection) or nonintensive antiviral chemoprophylaxis (0% to <70% of eligible residents). Main Outcomes and Measures: Outcomes were all-cause death and hospitalizations within 14 and 30 days of outbreak detection. Discrete-time hazard models with pooled logistic regression were applied to estimate weighted risks, risk differences (RDs), and risk ratios (RRs). Results: Among 404 outbreaks in 318 NHs, 35 086 resident-trial observations (29 683 residents; median age 78 [IQR, 68- 86] years; 60% women; 81% White; 76% vaccinated) met eligibility criteria. Intensive oseltamivir prophylaxis was randomized to 17 155 observations; 17 931 were randomized to nonintensive care. At 14 days, intensive prophylaxis vs nonintensive yielded an RD of -0.06% (95% CI, -0.73% to 0.93%) and an RR of 0.96 (95% CI, 0.56-1.57) for death, and an RD of -0.96% (95% CI, -1.78% to -0.19%) and an RR of 0.79 (95% CI, 0.64-0.96) for hospitalization. At 30 days, the hospitalization differences persisted but were less precise and there continued to be no difference in death. Conclusions and Relevance: Study results suggest that clinicians should initiate antiviral chemoprophylaxis for at least 70% of eligible NH residents within 2 days of outbreak detection to lower risk of hospitalization.

  PublisherDOI

• Linkage of Medicare insurance claims to police-reported motor vehicle crashes: advancing traffic safety research in older adult populations

  Figshare · 2026-02-06

  otherOpen access

  Abstract Background Motor vehicle crashes (MVCs) are a leading cause of injury among adults aged 65 years and older (“older adults”). As the number of older drivers grows, it is increasingly important to understand clinical factors associated with an increased risk of MVC. A major barrier, however, is the lack of data. To address this, we linked two large-scale administrative databases, the New Jersey Safety and Health Outcomes (NJ-SHO) Data Warehouse, which contains information on all police-reported crashes in New Jersey from 2004 to 2019, and Medicare Fee-for-Service (FFS) insurance claims, which contains health care encounters and prescription drug dispensings among older adults in the United States over the same period. This paper explains the linkage process, describes selected work leveraging these data to study MVCs in older drivers, and highlights features and strengths of this linkage for future research. Methods The NJ-SHO–Medicare linkage was performed using categories of name (first and last), sex, age (birth and death date), and residence (state and ZIP code). Matches were ranked by quality and overall confidence. Results After comparing different match strategies, we accepted a match when (1) the name match quality was High or Medium and the age match was High or (2) the name, sex, and residence match categories were all High. Of the 2,722,773 individuals successfully linked, we accepted 2,661,782 matches (97.76% of individuals linked and 91.59% of those submitted for linkage). All accepted matches were Strong or Fair. Among accepted matches who enrolled in Medicare FFS in 2019, 342,422 (28.57%) were 65–69 years old, 619,437 (51.69%) were female, and 955,309 (79.72%) were non-Hispanic White. Only 29,561 (2.47%) experienced an MVC and 25,478 (2.13%) received a citation. The most prevalent clinical conditions ever diagnosed were cataracts (669,044; 55.83%); chronic pain, fatigue, and fibromyalgia (367,165; 30.64%); and glaucoma (287,420; 23.98%). Conclusions With extensive temporal and population coverage, the NJ-SHO–Medicare linkage supports studying the relationships between clinical exposures (e.g., medications ), driving events (e.g., crashes, citations) and medical care trajectories, which can help advance the driving safety of older adults and inform future efforts to integrate administrative data.

  PublisherDOI

• Post‐Hospital Access to Preferred and High‐Quality Skilled Nursing Facilities for Patients With Opioid Use Disorder

  Health Services Research · 2026-03-31

  articleOpen access

  OBJECTIVE: To examine whether Medicare beneficiaries with opioid use disorder (OUD) encounter limited access to hospitals' highest-volume (i.e., "preferred") or high-quality skilled nursing facilities (SNFs) compared to beneficiaries without OUD. STUDY SETTING AND DESIGN: We estimated within-hospital disparities in access to preferred and high-quality SNFs by OUD status using linear probability models and discrete choice models (McFadden-style conditional logistic regression). We defined preferred status using shared hospital-SNF discharge volume and quality using CMS star ratings. In choice models, we matched patients with and without OUD 1:1 on discharging hospital and date, and applied inverse probability weighting and propensity score subclassification to address confounding. DATA SOURCES AND ANALYTIC SAMPLE: We used 2017-2021 Medicare inpatient claims to identify Medicare beneficiaries ages 18+ discharged to a SNF following hospitalization. PRINCIPAL FINDINGS: In the full sample (N = 6,490,593), patients with OUD were 2.5 and 3.6 percentage points (pp) less likely to enter preferred and high-quality SNFs, respectively. Among those discharged to preferred SNFs, patients with OUD were 2.0 pp less likely to enter high-quality preferred SNFs. In the matched subsample (n = 156,610), the marginal effect of preferred status on a person being discharged to their closest SNF was 1.1 pp lower for patients with OUD than those without OUD (p < 0.05), but with no significant disparity after inverse probability weighting. When the closest SNF's quality rating increased by 1 star, the probability of entry increased by 0.7 pp for people without OUD but decreased by 0.2 pp for people with OUD (difference = 0.9 pp, p < 0.001), a difference that persisted after weighting. CONCLUSIONS AND RELEVANCE: Publicly-reported star ratings had weaker associations with the SNF placements of Medicare beneficiaries with OUD compared to those without OUD, and preferred referral networks alone did not eliminate these gaps. Regulatory and reimbursement reforms that support SNFs in developing OUD-related care capacity and that promote equitable admissions deserve attention.

  PublisherDOI

• PReventing Injury in Skilled nursing facilities through optimizing Medications (PRISM), a protocol for a cluster randomized trial to reduce injurious falls in post-acute care

  UNC Libraries · 2025-10-09

  articleOpen access
  PublisherDOI

Recent grants

• Clinically Significant Drug Interactions among Nursing Home Residents with ADRD

  NIH · $2.8M · 2022–2027

• Opioid use in post-acute hip fracture care: prescribing patterns, effectiveness, and safety

  NIH · $462k · 2019–2023

• Medications and the Risk of Motor Vehicle Crashes in Older Adults

  NIH · $2.1M · 2020–2025

Frequent coauthors

• Sarah D. Berry

  Hebrew SeniorLife

  289 shared

• Stefan Gravenstein

  Brown University

  245 shared

• Melissa R. Riester

  John Brown University

  238 shared

• Robertus van Aalst

  Brown University

  213 shared

• Vincent Mor

  Providence College

  186 shared

• Kevin W. McConeghy

  Brown University

  183 shared

• Lori A. Daiello

  Brown University

  177 shared

• Douglas P. Kiel

  Hebrew SeniorLife

  170 shared

Education

• Other, Pharmacy

  Brown University

• Ph.D.

  Brown University