Michael E Matheny

• MD, MS, MPH
• Professor at Vanderbilt University

OBJECTIVE To assess the association between glucagon-like peptide 1 receptor agonist (GLP-1RA) use and risk of incident thyroid tumors. RESEARCH DESIGN AND METHODS The retrospective, active-comparator new-user cohort study used international administrative claims and electronic health record databases. Participants included patients with type 2 di...

Background In the IMPROVE AKI (A Cluster‐Randomized Trial of Team‐Based Coaching Interventions to Improve Acute Kidney Injury) trial, a combination of team‐based coaching and data‐driven surveillance dashboards reduced the odds of AKI following cardiac catheterization by 46%. The objective of this study was to determine if improvements in AKI outco...

Background: The widespread adoption of electronic health records (EHRs) has resulted in the generation of large volumes of clinical notes. Learning algorithms and large language models (LLMs) train from these resources but are susceptible to noise irrelevant or non informative data from them. This sensitivity can lead to significant challenges, inc...

Importance More than 10% of US patients undergoing endovascular procedures experience contrast-associated acute kidney injuries (AKIs), resulting in increased costs and health deficits. Prevention protocols reduce AKIs, but uptake and adherence vary greatly, and the cost-effectiveness of these interventions is unknown. Objective To analyze the cos...

Background Contemporary research in peripheral artery disease (PAD) remains limited due to lack of a national registry and low accuracy of diagnosis codes to identify patients with PAD. Methods Leveraging a novel natural language processing system that identifies PAD with high accuracy using ankle‐brachial index and toe‐brachial index values, we c...

Objectives While performance drift of clinical prediction models is well-documented, the potential for algorithmic biases to emerge post-deployment has had limited characterization. A better understanding of how temporal model performance may shift across subpopulations is required to incorporate fairness drift into model maintenance strategies. M...

BACKGROUND The American Academy of Pediatrics recommends up to 7 days of observation for neonatal opioid withdrawal syndrome (NOWS) in infants with chronic opioid exposure. However, many of these infants will not develop NOWS, and infants with seemingly less exposure to opioids may develop severe NOWS that requires in-hospital pharmacotherapy. We a...

Objectives To evaluate the feasibility for use of electronic health record (EHR) data in conducting adverse event surveillance among women who received mid-urethral slings (MUS) to treat stress urinary incontinence (SUI) in five health systems. Design Retrospective observational study using EHR data from 2010 through 2021. Women with a history of...

To explore threats and opportunities and to chart a path for safely navigating the rapid changes that generative artificial intelligence (AI) will bring to clinical research, the Duke Clinical Research Institute convened a multidisciplinary think tank in January 2024. Leading experts from academia, industry, nonprofits, and government agencies high...

Large language models (LLMs) hold promise for transforming healthcare, from streamlining administrative and clinical workflows to enriching patient engagement and advancing clinical decision-making. However, their successful integration requires rigorous development, adaptation, and evaluation strategies tailored to clinical needs. In this Review,...

Background Fluoroquinolones (FQs) are commonly used to treat urinary tract infections (UTIs), but some studies have suggested they may increase the risk of aortic aneurysm or dissection (AA/AD). However, no large-scale international study has thoroughly assessed this risk. Methods A retrospective cohort study was conducted using a large, distribut...

Objective To evaluate the validity of death ascertainment from publicly available internet media sources by benchmarking against state and Federal vital statics data for patients in two large healthcare systems from the US. Methods We extracted names and dates of birth and death from publicly available data including obituaries and memorial website...

The field of artificial intelligence (AI) has entered a new cycle of intense opportunity, fueled by advances in deep learning, including generative AI. Applications of recent advances affect many aspects of everyday life, yet nowhere is it more important to use this technology safely, effectively, and equitably than in health and health care. Here,...

Accurate detection and prevalence estimation of behavioral health conditions, such as opioid use disorder (OUD), are crucial for identifying at-risk individuals, determining treatment needs, monitoring prevention and intervention efforts, and recruiting treatment-naive participants for clinical trials. The availability of extensive health data, com...

Electronic health records (EHRs) have emerged as resources for both the identification of adverse drug events (ADEs) and general population health surveillance, however questions remain around how best to utilize EHR data for drug safety signal identification. While the majority of signal identification research has utilized spontaneous reports and...

Background: Mortality is a critical variable in healthcare research, but inconsistencies in the availability of death date and cause of death (CoD) information limit the ability to monitor medical product safety and effectiveness. Objective: To develop scalable approaches using natural language processing (NLP) and large language models (LLM) for t...

Background: Hospital Score is a well-known and validated tool for predicting readmission risk among diverse patient populations. Integrating social risk factors using natural language processing with the Hospital Score may improve its ability to predict 30-day readmissions following an acute myocardial infarction. Methods: A retrospective cohort in...

Objectives Traditional methods for medical device post-market surveillance often fail to accurately account for operator learning effects, leading to biased assessments of device safety. These methods struggle with non-linearity, complex learning curves, and time-varying covariates, such as physician experience. To address these limitations, we sou...

Purpose The US Food and Drug Administration's Sentinel Innovation Center aimed to establish a query‐ready, quality‐checked distributed data network containing electronic health records (EHRs) linked with insurance claims data for at least 10 million individuals to expand the utility of real‐world data for regulatory decision‐making. Methods In thi...

Rationale and Objective Acute kidney injury (AKI) is a common complication among hospitalized adults, but AKI prediction and prevention among adults has proved challenging. We used machine learning to update the nephrotoxic injury negated by just-in time action (NINJA), a pediatric program that predicts nephrotoxic AKI, to improve accuracy among ad...

Objectives To assess the feasibility of assessing long-term outcomes of peripheral vascular intervention (PVI) by linking data from a clinical registry to electronic health records (EHR) data from a clinical research network. Design Observational cohort study. Setting Vascular Quality Initiative registry linked to INSIGHT Clinical Research Networ...

Background Sodium-glucose cotransporter 2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) reduce the risk of major adverse cardiovascular events (MACE) in patients with type 2 diabetes mellitus (T2DM). However, their effectiveness relative to each other and other second-line antihyperglycemic agents is unknown, withou...

Background Little is known about the association of discontinuation of sodium-glucose co-transporter-2 (SGLT2) inhibitors and glucagon-like peptide-1 receptor agonists (GLP-1 RA) with outcomes in patients with chronic kidney disease (CKD). Methods We identified adults with CKD stages 3-4 from 2005-2022 in the Veterans Affairs healthcare system. In...

Background Contemporary research in peripheral artery disease (PAD) remains limited due to lack of a national registry and low accuracy of diagnosis codes to identify PAD patients in electronic health records. Methods & Results Leveraging a novel natural language processing (NLP) system that identifies PAD with high accuracy using ankle brachial i...

Importance The Sentinel System is a key component of the US Food and Drug Administration (FDA) postmarketing safety surveillance commitment and uses clinical health care data to conduct analyses to inform drug labeling and safety communications, FDA advisory committee meetings, and other regulatory decisions. However, observational data are frequen...

Background Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are associated with self-reported problems with cognition as well as risk for Alzheimer’s disease and related dementias (ADRD). Overlapping symptom profiles observed in cognitive disorders, psychiatric disorders, and environmental exposures (e.g., head injury) can comp...

Background Despite efforts to enhance the quality of medication prescribing in outpatient settings, potentially inappropriate prescribing remains common, particularly in unscheduled settings where patients can present with infectious and pain-related complaints. Two of the most commonly prescribed medication classes in outpatient settings with freq...

Introduction Acute kidney injury (AKI) is associated with increased risk of heart failure (HF). Determining the type of HF experienced by AKI survivors (heart failure with preserved or reduced ejection fraction, HFpEF or HFrEF) could suggest potential mechanisms underlying the association and opportunities for improving post-AKI care. Methods In t...

The Phenome-Wide Association Study (PheWAS) is increasingly used to broadly screen for potential treatment effects, e.g., IL6R variant as a proxy for IL6R antagonists. This approach offers an opportunity to address the limited power in clinical trials to study differential treatment effects across patient subgroups. However, limited methods exist t...

Reducing the prevalence of acute kidney injury (AKI) is an important patient safety objective set forth by the National Quality Forum. Despite international guidelines to prevent AKI, there continues to be an inconsistent uptake of these interventions by cardiac teams across practice settings. The IMPROVE-AKI study was designed to test the effectiv...

Background As the enthusiasm for integrating artificial intelligence (AI) into clinical care grows, so has our understanding of the challenges associated with deploying impactful and sustainable clinical AI models. Complex dataset shifts resulting from evolving clinical environments strain the longevity of AI models as predictive accuracy and assoc...

Background SGLT2 inhibitors (SGLT2is) and GLP-1 receptor agonists (GLP1-RAs) reduce major adverse cardiovascular events (MACE) in patients with type 2 diabetes mellitus (T2DM). However, their effectiveness relative to each other and other second-line antihyperglycemic agents is unknown, without any major ongoing head-to-head trials. Methods Across...

Objective Assigning outcome labels to large observational data sets in a timely and accurate manner, particularly when outcomes are rare or not directly ascertainable, remains a significant challenge within biomedical informatics. We examined whether noisy labels generated from subject matter experts’ heuristics using heterogenous data types within...

Objective: Assigning outcome labels to large observational data sets in a timely and accurate manner, particularly when outcomes are rare or not directly ascertainable, remains a significant challenge within biomedical informatics. We examined whether noisy labels generated from subject matter experts' heuristics using heterogenous data types withi...

Standardized operational definitions are an important tool to improve reproducibility of research using secondary real-world healthcare data. This approach was leveraged for studies evaluating the effectiveness of AZD7442 as COVID-19 pre-exposure prophylaxis across multiple healthcare systems. Value sets were defined, grouped, and mapped. Results o...

Introduction: Angiotensin converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARB) improve outcomes but are underutilized in patients with chronic kidney disease (CKD). Little is known about reasons for discontinuation and lack of reinitiating these medications. We aimed to explore clinicians’ and patients’ experiences and percep...

Post marketing safety surveillance depends in part on the ability to detect concerning clinical events at scale. Spontaneous reporting might be an effective component of safety surveillance, but it requires awareness and understanding among healthcare professionals to achieve its potential. Reliance on readily available structured data such as diag...

Chronic age-related imbalance is a common cause of falls and subsequent death in the elderly and can arise from dysfunction of the vestibular system, an elegant neuroanatomical group of pathways that mediates human perception of acceleration, gravity, and angular head motion. Studies indicate that 27–46% of the risk of age-related chronic imbalance...

Background Measuring the effectiveness of preventing and treating viruses like SARS-CoV-2 poses a challenge in understanding the variants’ susceptibility and resistance to being neutralized. Ideally, each breakthrough case would be sequenced, but in real-world settings, we rely on surveillance samples and estimated date cutoffs to determine effecti...

Objective We examined the influence of 4 different risk information formats on inpatient nurses’ preferences and decisions with an acute clinical deterioration decision-support system. Materials and methods We conducted a comparative usability evaluation in which participants provided responses to multiple user interface options in a simulated set...

Significance Statement African Americans are at increased risk of CKD in part due to high-risk (HR) variants in the apolipoprotein L1 ( APOL1 ) gene, termed G1/G2. A different APOL1 variant, p.N264K , reduced the risk of CKD and ESKD among carriers of APOL1 HR variants to levels comparable with individuals with APOL1 low-risk variants in an analysi...

Objective To assess the uptake of second line antihyperglycaemic drugs among patients with type 2 diabetes mellitus who are receiving metformin. Design Federated pharmacoepidemiological evaluation in LEGEND-T2DM. Setting 10 US and seven non-US electronic health record and administrative claims databases in the Observational Health Data Sciences a...

Introduction: The pitfalls of label leakage, contamination of model input features with outcome information, are well established. Unfortunately, avoiding label leakage in clinical prediction models requires more nuance than the common advice of applying "no time machine rule." Framework: We provide a framework for contemplating whether and when...

Study design: A 5-year longitudinal, retrospective, cohort study. Objectives: Develop a prediction model based on electronic health record (EHR) data to identify veterans with spinal cord injury/diseases (SCI/D) at highest risk for new pressure injuries (PIs). Setting: Structured (coded) and text EHR data, for veterans with SCI/D treated in a...

Background: Rapid progression of chronic kidney disease (CKD) is associated with poor clinical outcomes. Despite extensive study of the genetics of cross-sectional estimated glomerular filtration rate (eGFR), only a few loci associated with eGFR decline over time have been identified. Methods: We performed a meta-analysis of genome-wide associat...

Background: Angiotensin converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARB) are frequently discontinued in patients with chronic kidney disease (CKD). Documented adverse drug reactions (ADRs) in medical records may provide insight into the reasons for treatment discontinuation. Methods: In this retrospective cohort of U.S...

Introduction: Lung cancer screening with low-dose computed tomography (LDCT) is widely underutilized. Organizational factors, such as readiness for change and belief in the value of change (change valence), may contribute to underutilization. The aim of this study was to evaluate the association between healthcare organizations' preparedness and l...

Background: Validating new algorithms, such as methods to disentangle intrinsic treatment risk from risk associated with experiential learning of novel treatments, often requires knowing the ground truth for data characteristics under investigation. Since the ground truth is inaccessible in real world data, simulation studies using synthetic datas...

Purpose: Understanding the real-world safety of paclitaxel (PTX) coated devices for treating lower extremity peripheral artery disease remains a high clinical priority of the Food and Drug Administration. Materials and methods: Data from FAIR Health, the largest commercial claims data warehouse in the US, was used for this study. The study consi...

Rationale & objective: Sodium-glucose co-transporter 2 inhibitors (SGLT2i) are recommended for type 2 diabetes mellitus (T2DM) in patients with chronic kidney disease (CKD) or atherosclerotic cardiovascular disease (ASCVD). We evaluated factors associated with SGLT2i prescription, disparities by race and sex, and facility-level variation in prescr...

Background: Super-utilizers consume the greatest share of resource intensive healthcare (RIHC) and reducing their utilization remains a crucial challenge to healthcare systems in the United States (U.S.). The objective of this study was to predict RIHC among U.S. counties, using routinely collected data from the U.S. government, including informat...

Background: Up to 14% of patients in the United States undergoing cardiac catheterization each year experience AKI. Consistent use of risk minimization preventive strategies may improve outcomes. We hypothesized that team-based coaching in a Virtual Learning Collaborative (Collaborative) would reduce postprocedural AKI compared with Technical Assi...

Background : Characterization studies of COVID-19 patients with chronic obstructive pulmonary disease (COPD) are limited in size and scope. The aim of the study is to provide a large-scale characterization of COVID-19 patients with COPD. Methods : We included thirteen databases contributing data from January-June 2020 from North America (US), Europ...

Objectives To assess the uptake of second-line antihyperglycemic agents among patients with type-2 diabetes mellitus (T2DM) receiving metformin. Design Serial cross-sectional study (2011-2021). Setting Ten US and seven non-US electronic health record and administrative claims databases in the Observational Health Data Sciences and Informatics netwo...

Background Postoperative infections constitute more than half of all postoperative complications. Surveillance of these complications is primarily done through manual chart review, which is time consuming, expensive, and typically only covers 10% to 15% of all operations. Automated surveillance would permit the timely evaluation of and reporting of...

Background: Current methods to identify cardiac implantable electronic devices (CIED) lead failure include post-approval studies, which may be limited in scope, participant numbers, and attrition; studies relying on administrative codes, which lack specificity; and voluntary adverse event reporting, which cannot determine incidence or attribution...

Objectives Generating and using real-world evidence (RWE) is a pragmatic solution for evaluating health technologies. RWE is recognized by regulators, health technology assessors, clinicians, and manufacturers as a valid source of information to support their decision-making. Well-designed registries can provide RWE and become more powerful when li...

Purpose: Alpha-1 blockers, often used to treat benign prostatic hyperplasia (BPH), have been hypothesized to prevent COVID-19 complications by minimising cytokine storm release. The proposed treatment based on this hypothesis currently lacks support from reliable real-world evidence, however. We leverage an international network of large-scale heal...

As the implementation of artificial intelligence (AI)-enabled tools is realized across diverse clinical environments, there is a growing understanding of the need for ongoing monitoring and updating of prediction models. Dataset shift—temporal changes in clinical practice, patient populations, and information systems—is now well-documented as a sou...

Background The total impact of the current COVID-19 pandemic on cancer screenings and diagnostic procedures by race and ethnicity has not yet been fully characterized. Methods In this study, we compared the ethnic and racial differences in cancer screening for breast, colon, and prostate cancer and compared them to population-level SARS-CoV2 infec...

BACKGROUND The utility of quality dashboards to inform decision-making and improve clinical outcomes is tightly linked to the accuracy of the information they provide and, in turn, accuracy of underlying prediction models. Despite recognition of the need to update prediction models to maintain accuracy over time, there is limited guidance on updati...

Background and Aims Gastrointestinal (GI) symptoms are well-recognized manifestations of coronavirus disease 2019 (COVID-19). Our primary objective was to evaluate the association between GI symptoms and COVID-19 severity. Methods In this nationwide cohort of US veterans, we evaluated GI symptoms (nausea/vomiting/diarrhea) reported 30 days prior t...

Importance: Acute kidney injury (AKI) is a heterogeneous syndrome prevalent among hospitalized patients. Personalized risk estimation and risk factor identification may allow effective intervention and improved outcomes. Objective: To develop and validate personalized AKI risk estimation models using electronic health records (EHRs), examine whe...

Objectives To assess the feasibility of using electronic health record (EHR) derived clinical data within an active surveillance setting to evaluate the safety of a novel intervertebral body implant (IVBI) stabilization device. Design Retrospective, longitudinal observational cohort study comparing clinical outcomes for patients seen through 1 yea...

Background P2Y12 inhibitor medications are critical following percutaneous coronary intervention (PCI); however, adherence remains suboptimal. Our objective was to assess the effectiveness of a multifaceted intervention to improve P2Y12 inhibitor adherence following PCI. Methods and Results This was a modified stepped wedge trial of 52 eligible ho...

Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates acr...

Background: Current important regulatory resources and methods to identify cardiac implantable electronic devices (CIED) lead failure include post-approval studies, which may be limited in scope, participant numbers, and by attrition; studies relying on administrative codes, which lack specificity in multi-chamber systems; and voluntary adverse eve...

PurposeStatin-associated side effects (SASEs) can limit statin adherence and present a potential barrier to optimal statin utilization. How standardized reporting of SASEs varies across medical facilities has not been well characterized.Methods We assessed facility-level variation in SASE reporting among patients with atherosclerotic cardiovascular...

Background Veterans Health Administration (VHA) issued policy for lung cancer screening; resources at eight Veterans Affairs medical centers (VAMCs) in a demonstration project (DP) from 2013 to 2015. Research Question Do policies that provide resources increase lung cancer screening rates? Study Design and Methods Data from 8 DP VAMCs (DP group)...

OBJECTIVES/GOALS: Using the covariate-rich Veteran Health Administration data, estimate the association between Proton Pump Inhibitor (PPI) use and severe COVID-19, rigorously adjusting for confounding using propensity score (PS)-weighting. METHODS/STUDY POPULATION: We assembled a national retrospective cohort of United States veterans who tested p...

Background Social risk factors influence rehospitalization rates yet are challenging to incorporate into prediction models. Integration of social risk factors using natural language processing (NLP) and machine learning could improve risk prediction of 30‐day readmission following an acute myocardial infarction. Methods and Results Patients were e...

Background : Characterization studies of COVID-19 patients with chronic obstructive pulmonary disease (COPD) are limited in size and scope. The aim of the study is to provide a large-scale characterization of COVID-19 patients with COPD. Methods : We included thirteen databases contributing data from January-June 2020 from North America (US), Europ...

Purpose Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisati...

Many clinical natural language processing methods rely on non-contextual word embedding (NCWE) or contextual word embedding (CWE) models. Yet, few, if any, intrinsic evaluation benchmarks exist comparing embedding representations against clinician judgment. We developed intrinsic evaluation tasks for embedding models using a corpus of radiology rep...

Background Despite its high prevalence and clinical impact, research on peripheral artery disease (PAD) remains limited due to poor accuracy of billing codes. Ankle-brachial index (ABI) and toe-brachial index can be used to identify PAD patients with high accuracy within electronic health records. Methods We developed a novel natural language proc...