About

Earl J Morris, Pharm.D., M.P.H., Ph.D., is a Research Assistant Professor in the Department of Pharmaceutical Outcomes and Policy at the University of Florida College of Pharmacy. He received his Pharm.D. and M.P.H. degrees from the University of Arkansas for Medical Sciences in 2019 and his Ph.D. in Pharmaceutical Sciences from the University of Florida College of Pharmacy in 2023. During his Ph.D. training, he was awarded an American Heart Association predoctoral fellowship. Dr. Morris is a pharmacoepidemiologist and pharmacist with a primary focus on leveraging rigorous pharmacoepidemiologic methods to address clinical questions related to geriatric pharmacotherapy and cardiorheumatology. His research aims to improve the identification and mitigation of adverse drug events in older adults and to better understand cardiovascular risk profiles among individuals with rheumatologic conditions. His work has been published in various reputable journals, including Pharmacoepidemiology and Drug Safety, the American Journal of Hypertension, and the Journal of the American Geriatrics Society.

Research topics

• Medicine
• Pharmacology
• Psychiatry
• Internal medicine
• Psychology
• Family medicine
• Pathology
• Cardiology

Selected publications

• A National Survey of Pharmacy Skills Laboratory Faculty Perceptions of Evaluation, Promotion, and Workload Policies

  American Journal of Pharmaceutical Education · 2026-05-01

  articleOpen access

  OBJECTIVE: The study assessed perceptions of workload and evaluation policies among pharmacy skills laboratory faculty. METHODS: A survey was developed and disseminated to AACP Skills Laboratory Special Interest Group faculty members. The survey contained questions on faculty and institution demographics, satisfaction with current workload, and perceptions of fairness, transparency, workload policy and calculator parity, and promotion climate. Quantitative data were reported using descriptive statistics; exploratory factor analysis assessed item structure and regression models were used to examine predictors of workload satisfaction. Qualitative data were analyzed using an inductive thematic approach. RESULTS: A total of 75 faculty from 66 of 130 institutions (RR=50.7%) responded. The majority were white (90.7%), female (76.0%), and held the rank of associate professor (48.0%), with an average teaching effort of 62.4%. Most reported having a template for faculty evaluation (77.3%); however, transparency in calculating teaching workload remained a challenge (44.0%). While most indicated that workload and evaluation policies did not differ from non-laboratory faculty, a significant number indicated expectations were not fair (41.3%) and that promotion took longer for skills laboratory faculty (22.7%). Perceptions of fairness were the strongest predictor of overall satisfaction. Free responses highlighted invisible workload requirements including concerns related to time, equity, and understanding. CONCLUSION: This study is among the first to examine skills laboratory faculty perceptions of workload policies, evaluation processes, and promotion climate across a national sample. These findings underscore the importance of developing workload policies and evaluation processes that reflect the unique contributions of skills laboratory faculty to pharmacy education.

  PublisherDOI

• Association Between Different Analgesic Use and Hypertension Among Medicare Beneficiaries With Osteoarthritis

  Journal of the American Geriatrics Society · 2026-03-15

  article

  BACKGROUND: In older adults with osteoarthritis (OA) and hypertension (HTN), analgesic use may elevate blood pressure and cardiovascular risk. Whether comorbid HTN influences initial analgesic choice remains unclear; we examined initial analgesic use in Medicare beneficiaries with incident OA, comparing those with and without HTN. METHODS: We conducted a retrospective cohort study using 2011-2022 nationally representative Medicare beneficiaries (≥ 65 years) with incident OA who initiated an analgesic within 30 days of diagnosis and had continuous enrollment for ≥ 365 days prior through ≥ 30 days post-index. Patients with baseline HTN were classified as OA + HTN; others as OA-only. We assessed overall analgesic trends using the Cochran-Armitage test and evaluated differences by HTN status using logistic regression with year as an interaction term. For stratified analyses by joint type, we applied weighted logistic regression. RESULTS: Among 179,033 beneficiaries (mean age 75 ± 7.3 years; 62.7% women; 80.7% White), 57.1% had baseline HTN. Overall, the most commonly initiated analgesic classes were intra-articular injections (30.3%), and oral NSAIDs only (28.2%). Notable changes from 2012 to 2022 were increase in topical NSAIDs use (3.1%-5.7%) and decrease in opioid combination use (25.4%-13.9%), with no significant trend differences by HTN status. In joint-specific analyses, OA + HTN versus OA-only showed no differences in odds of initiating oral opioids (OR: 0.97, 95% CI: 0.92-1.03), intra-articular injections (OR: 1.01, 95% CI: 0.96-1.07) or topical NSAIDs (OR: 0.88, 95% CI: 0.78-1.01) versus oral NSAIDs. CONCLUSION: Baseline HTN did not influence the choice of initial analgesic in incident OA patients. Safer, evidence-based alternatives are needed for older adults with comorbid HTN.

  PublisherDOI

• Neonatal Outcome Ascertainment in Mother‐Infant Paired Claims

  Pharmacoepidemiology and Drug Safety · 2026-01-18

  articleOpen access

  PURPOSE: Claims data are a valuable source to study neonatal outcomes across a wide range of clinical questions. Infants' delayed enrollment in infant insurance poses challenges in capture of neonatal outcomes, which may be charged to the maternal health plan, posing misclassification risks. We evaluated outcome ascertainment across three infant enrollment scenarios. METHODS: We used Merative MarketScan databases (2012-2018) in the United States to construct a mother-infant linked cohort and assess the outcome ascertaiment precision with varying infant enrollment requirement. RESULT: We found that allowing delayed infant enrollment in their own insurance within the first 4 weeks of life retained sample size, nearly doubled case numbers and yielded outcome prevalences similar to those of cohorts with full enrollment since birth. Use of maternal claims in addition to infant claims in this cohort made minor contributions to case capture for neonatal-specific outcomes, while significantly decreasing specificity of more general outcomes. Longer delays in enrollment yielded lower outcome prevalences with higher contributions of maternal claims even for neonatal-specific outcomes. For small for gestational age (SGA), both maternal and infant claims contributed similar proportions of cases. CONCLUSION: These findings inform strategies for outcome ascertainment in claims-based perinatal research and emphasize outcome-specific case ascertainment strategies to balance sensitivity and specificity.

  PublisherOA PDFDOI

• COVID-19 pandemic impact on clinical condition capture in real-world data: an assessment framework

  American Journal of Epidemiology · 2025-07-11

  article

  The COVID-19 pandemic has impacted healthcare utilization and, consequently, real-world data. In this study, we used analytical and data visualization approaches to untangle effects on condition measurement and true shifts in the patient population seeking healthcare. We used Merative MarketScan 2018-2020 commercial claims data to develop 24 monthly cohorts of patients aged ≥18 years with 12 months baseline enrollment and an encounter for diabetes, cancer, hypertension, depression, myocardial infarction, atrial fibrillation, or urinary tract infections as the index condition in a given month. We compared monthly prevalence of each condition in 2020 versus 2019. We then imposed 3-, 6-, and 12-month look-back periods (LBP) to capture comorbidities grouped by Clinical Classifications Software Refined (CCSR) or summarized in the Charleson Comorbidity Index (CCI) and conducted similar 2020 versus 2019 prevalence comparisons. Changes in condition prevalence varied across conditions with strongest declines for cancer in April 2020 (-57.4%) and strongest increases for depression in December 2020 (+11.8%). The mean CCI was higher for most conditions during the spring of 2020, and this difference was accentuated by applying a longer LBP. Similar trends were found regarding the number of CCSR categories. Pandemic-related changes in condition capture were complex, involving both increases and decreases in encounters for specific conditions and in comorbidities, along with variations in comorbidity capture dependent on LBP. We provided a practical approach to untangle these phenomena along with open-source algorithms and visualization tools to assess these changes and inform study design and analysis.

  PublisherDOI

• High‐Throughput Screening for Prescribing Cascades Among Real‐World Angiotensin‐Converting Enzyme Inhibitor Initiators

  Pharmacoepidemiology and Drug Safety · 2025-03-01 · 3 citations

  articleOpen access

  ABSTRACT Purpose Angiotensin‐converting enzyme inhibitors (ACEIs) are commonly prescribed, but their adverse effects may prompt new drug prescription(s), known as prescribing cascades (PCs). We aimed to identify potential ACEI‐induced PCs using high‐throughput sequence symmetry analysis. Methods Using claims data from a national sample of Medicare beneficiaries (2011–2020), we identified new ACEI users aged ≥ 66 years with continuous enrollment ≥ 360 days before and ≥ 180 days after ACEI initiation. We screened for initiation of 446 other (non‐antihypertensive) “marker” drug classes within ±90 days of ACEI initiation, generating sequence ratios (SRs) reflecting proportions of ACEI users starting the marker class after versus before ACEI initiation. Adjusted SRs (aSRs) accounted for prescribing trends over time. For significant aSRs, we calculated the naturalistic number needed to harm (NNTH), and significant signals underwent clinical review for plausibility. Results We identified 308 579 ACEI initiators (mean age 76.1 ± 7.5 years; 59.6% female; 88.6% with hypertension). Of 446 marker classes evaluated, 81 signals were significant, and 42 (52%) classified as potential PCs after clinical review. The strongest signals ranked by lowest NNTH included corticosteroids (NNTH 313; 95% CI, 262–392) and serotonin type 3 (5‐HT 3 ) antagonists (NNTH 496; 95% CI, 392–689); the strongest signals ranked by highest aSR included sympathomimetics (aSR, 1.97; 95% CI, 1.10–3.53) and other antianemic preparations (aSR, 1.87; 95% CI, 1.31–2.67). Conclusion Identified prescribing cascade signals were indicative of known and possibly underrecognized ACEI adverse events in this Medicare cohort. The findings are hypothesis‐generating and require further investigation to determine the extent and impact of the identified PCs on health outcomes.

  PublisherOA PDFDOI

• Abstract 4370259: Medical Cannabis and Acute Myocardial Infarction Risk: A Case-Time-Control Analysis

  Circulation · 2025-11-03

  article1st authorCorresponding

  Introduction/Background: Medical cannabis (MC) appears to have multiple effects on the cardiovascular system via sympathomimetic effects and parasympathetic effects, and there is concern that MC may potentiate major adverse cardiovascular events, such as acute myocardial infarction (AMI). However, few epidemiologic studies have evaluated cardiovascular risk associated with real-world MC use. Research Questions/Hypothesis: Does transient MC exposure increase short-term risk for AMI? Goals/Aims: We aimed to evaluate the association between MC and AMI risk, using a self-controlled case-time-control study design. Methods/Approach: This case-time-control study used Medical Marijuana clinical Outcomes RepositorY (MEMORY) data, which contains OMMU Medical Marijuana Use Registry (MMUR) data linked to Medicaid claims. We included Medicaid beneficiaries with a hospitalization for AMI measured by ICD-10-CM diagnosis codes as cases. These individuals were matched 1:1 with a control (no AMI) on exact age, sex, and calendar time, where each control has at least as much follow-up time as their matched case and did not become a case themselves subsequently. Patients with medical cannabis exposure up to 30 days before AMI (or matched calendar date) were considered exposed during the hazard period, and those with exposure 90–60 days before AMI (or matched calendar date) were considered exposed during the referent period. For cases and controls, odds ratios (ORs) were calculated using multivariable conditional logistic regression by comparing MC exposure ratios between hazard period and referent period within individuals. The overall OR of the case-time-control study was estimated by dividing the OR among cases by the OR among controls. Results: We identified 18,287 patients with an AMI (47.9% female; mean age (SD): 51.8 years old (10.3)); and 333 (0.9%) were receiving MC treatment at the time of AMI. Among cases and controls, we did not find an increase in odds of MC exposure within 30 days before AMI (case OR, 95% CI: 1.34, 0.93-1.93; control OR, 95% CI: 1.29, 0.93-1.79). Moreover, the case-time-control analysis revealed no increased in odds of MC exposure within 30 days before AMI (OR, 95% CI: 1.04, 0.64–1.71), after adjusting for background exposure trends. Conclusion(s): Our findings suggest that medical cannabis use was not associated with an increase in AMI risk within 30 days of use. However, more research is needed to more fully characterize risk among relevant subgroups.

  PublisherDOI

• Clinical characteristics and medication use patterns of middle-aged and older adults with sleep apnea with and without comorbid insomnia

  Sleep And Breathing · 2025-04-23 · 3 citations

  articleOpen access
  PublisherOA PDFDOI

• High‐Throughput Screening for Prescribing Cascades Among Real‐World Angiotensin‐ <scp>II</scp> Receptor Blockers ( <scp>ARBs</scp> ) Initiators

  Pharmacotherapy The Journal of Human Pharmacology and Drug Therapy · 2025-10-21 · 1 citations

  article

  OBJECTIVE: Angiotensin-II Receptor Blockers (ARBs) are commonly prescribed; however, their adverse events may prompt new drug prescriptions, known as prescribing cascade (PC). We aimed to identify potential ARB-induced PCs using high-throughput sequence symmetry analysis. METHODS: Using claims data from a national sample of Medicare beneficiaries (2011-2020), we identified new ARB users aged ≥ 66 years with continuous enrollment ≥ 360 days before and ≥ 180 days after ARB initiation. We screened for initiation of 446 other (non-antihypertensive) "marker" drug classes within ±90 days of ARB initiation. Sequence ratios (SRs) with 95% confidence intervals (CIs) were calculated as the ratio of the number of ARB users initiating the marker class after versus before ARB initiation. Adjusted SRs (aSRs) accounted for prescribing trends over time, and for significant aSRs, we calculated the naturalistic number needed to harm (NNTH); significant signals were reviewed by clinical experts for plausibility. RESULTS: We identified 320,663 ARB initiators, age (mean ± standard deviation) 76.0 ± 7.2 years; 62.5% female; and 91.5% with hypertension. Of the 446 marker classes evaluated, 17 signals were significant, and three (18%) were classified as potential PCs after clinical review. The strongest signals ranked by the lowest NNTH included benzodiazepine derivatives (NNTH 2130, 95% CI 1437-4525), adrenergics in combination with anticholinergics, including triple combinations with corticosteroids (NNTH 2656, 95% CI 1585-10,074), and other antianemic preparations (NNTH 9416, 95% CI 6606-23,784). The strongest signals ranked by highest aSR included other antianemic preparations (aSR 1.7, 95% CI 1.19-2.41), benzodiazepine derivatives (aSR 1.18, 95% CI 1.08-1.3), and adrenergics in combination with anticholinergics, including triple combinations with corticosteroids (aSR 1.12, 95% CI 1.03-1.22). CONCLUSION: The identified PC signals reflected known and possibly under-recognized ARB adverse events in this Medicare cohort. These hypothesis-generating findings require further investigation to determine the extent and impact of these PCs on patient outcomes.

  PublisherDOI

• Impact of prescribing vancomycin capsules vs liquid at discharge on readmissions for <i>C. difficile</i> infection

  American Journal of Health-System Pharmacy · 2025-01-04 · 1 citations

  article

  PURPOSE: Clostridioides difficile infection (CDI) is a hospital-acquired infection commonly treated with oral vancomycin. An institutional policy aimed at reducing costs by substituting compounded liquid vancomycin for capsules may have the unintended consequence of having the liquid formulation prescribed at discharge, potentially delaying patients' access due to a lack of availability in pharmacies or lack of insurance coverage. This study aimed to evaluate hospital readmission rates of patients prescribed either vancomycin capsules or liquid upon discharge. METHODS: This was a retrospective cohort study conducted at an academic hospital using electronic health records data over a 6-year timeframe. The primary outcomes were all-cause and CDI-specific readmission rates within 30 days of discharge, and secondary outcomes included readmission rates within 60 and 90 days. Baseline characteristics were compared using chi-square or Mann-Whitney U tests. The hazard ratio (HR) for readmission was calculated using a Cox proportional hazards model, and readmission rates were analyzed using a Poisson regression model. All readmissions were confirmed by chart review. RESULTS: A total of 440 patients (61.3% female; median age, 58 years) were included; of these, 68% (n = 298) were prescribed vancomycin liquid and 32% (n = 142) a capsule form. Baseline characteristics were similar in the 2 groups, with the exception of the presence of inflammatory bowel disease (19.0% vs 6.4%, P < 0.0001) and median length of stay (6 days vs 8 days, P = 0.010). Patients prescribed vancomycin liquid were not more likely to be readmitted within 30 days relative to those prescribed capsule, with an adjusted HR for all-cause readmission of 1.58 (95% CI, 0.92-2.73) and an adjusted HR for CDI-specific readmission of 2.21 (95% CI, 0.72-6.76). However, patients prescribed liquid were more likely to be readmitted within 60 days, with an adjusted HR for all-cause readmission of 1.87 (95% CI, 1.19-2.94) and an adjusted HR for CDI-specific readmission of 2.84 (95% CI, 1.14-7.06). CONCLUSION: A hospital pharmacy practice implemented to reduce medication costs may impact vancomycin prescribing at discharge and, in turn, may negatively impact readmission rates for patients with CDI treated with oral vancomycin.

  PublisherDOI

• Assessing the Quality of Electronic Health Record Data and the Claims Linked Data for Target Trial Emulation Studies

  medRxiv · 2025-12-29

  articleOpen access

  Objectives: To evaluate whether a EHR cohort, alone and linked to Medicare claims, has sufficient data quality to support design elements required for target trial emulation, using type 2 diabetes (T2D) as a case example. Materials and Methods: We constructed annual University of Florida Health EHR—Medicare linked cohorts of patients ≥ 65 years with T2D from 2013 to 2020. Using Medicare claims as the reference, we assessed EHR data quality for target trial emulation-relevant elements across completeness, accuracy, plausibility, and concordance, spanning target trial components (eligibility, exposure/new-user ascertainment, baseline covariates, outcomes, and follow-up). Data quality was compared across EHR-only, claims-only, and EHR—claims linked data. Results: The mean annual EHR—Medicare linked cohort included 12,895 patients (mean age 74.9 years; 58.0% female). Demographics were complete and highly accurate. In the EHR-only cohort, completeness ranged 34.1-78.4% for conditions and 53.7-63.4% for glucose lowering drugs (GLDs). Accuracy was high for prevalent conditions and GLD use but low for incident measures. Plausible values were common (&gt;98.5%), and HbA1c - T2D concordance was strong (98.6%). Linking EHR and claims substantially improved completeness and accuracy, especially for encounters, mortality, incident diagnoses, and medications. Discussion: The linked dataset addressed major limitations of EHR-only data and provided enhanced granularity compared to claims alone, offering a comprehensive resource for real-world target trial emulation research. Conclusion: EHRs offer valuable clinical details but face data quality challenges. Robust quality assurance strategies and linkage with external data are essential to strengthen real-world evidence and support target trial emulation.

  PublisherOA PDFDOI

Frequent coauthors

• Scott Martin Vouri

  Center for Drug Evaluation and Research

  65 shared

• Steven M. Smith

  University of Florida

  27 shared

• Almut G. Winterstein

  Center for Drug Evaluation and Research

  26 shared

• Shailina Keshwani

  University of Florida

  22 shared

• Amie Goodin

  20 shared

• Grace Hsin‐Min Wang

  University of Florida

  18 shared

• Sebastian Jugl

  Center for Drug Evaluation and Research

  16 shared

• Carl J. Pepine

  University of Florida

  16 shared

Education

• Ph.D., Pharmaceutical Outcomes & Policy

  University of Florida

  2000

• M.S., Pharmaceutical Outcomes & Policy

  University of Florida

  1996

• B.S., Pharmacy

  University of Florida

  1994

Awards & honors

• American Heart Association predoctoral fellowship