A5065153070- Statistical Methods in Clinical Trials
- Health Systems, Economic Evaluations, Quality of Life
- Advanced Causal Inference Techniques
- Pharmacovigilance and Adverse Drug Reactions
- Machine Learning in Healthcare
- Biomedical Text Mining and Ontologies
- COVID-19 Clinical Research Studies
- Meta-analysis and systematic reviews
- Diabetes Treatment and Management
- Chronic Disease Management Strategies
- Vaccine Coverage and Hesitancy
- Electronic Health Records Systems
- Influenza Virus Research Studies
- Long-Term Effects of COVID-19
- SARS-CoV-2 and COVID-19 Research
- Artificial Intelligence in Healthcare
- Statistical Methods and Bayesian Inference
- Blood Pressure and Hypertension Studies
- Pharmaceutical Practices and Patient Outcomes
- Medical Coding and Health Information
- Ethics in Clinical Research
- Rheumatoid Arthritis Research and Therapies
- Diabetes Management and Research
- COVID-19 and healthcare impacts
- Pharmaceutical Economics and Policy
Janssen (United States)
2016-2025
Columbia University Irving Medical Center
2015-2025
Columbia University
2016-2025
Johnson & Johnson (United States)
2010-2025
The Coordinating Center
2024
University of Cincinnati Medical Center
2024
Janssen (Belgium)
2012-2024
Johnson & Johnson (Israel)
2012-2024
National Institutes of Health
2024
University of Oxford
2023
The vision of creating accessible, reliable clinical evidence by accessing the clincial experience hundreds millions patients across globe is a reality. Observational Health Data Sciences and Informatics (OHDSI) has built on learnings from Medical Outcomes Partnership to turn methods research insights into suite applications exploration tools that move field closer ultimate goal generating about all aspects healthcare serve needs patients, clinicians other decision-makers around world.
Systematic analysis of observational medical databases for active safety surveillance is hindered by the variation in data models and coding systems. Data analysts often find robust clinical difficult to understand ill suited support their analytic approaches. Further, some do not facilitate computations required systematic across many interventions outcomes large datasets. Translating from these idiosyncratic a common model (CDM) could both analysts' understanding suitability large-scale...
Harmonized data quality (DQ) assessment terms, methods, and reporting practices can establish a common understanding of the strengths limitations electronic health record (EHR) for operational analytics, improvement, research. Existing published DQ terms were harmonized to comprehensive unified terminology with definitions examples organized into conceptual framework support approach defining whether EHR is 'fit' specific uses.DQ publications, informatics analytics experts, managers...
The U.S. Food and Drug Administration (FDA) Amendments Act of 2007 mandated that the FDA develop a system for using automated health care data to identify risks marketed drugs other medical products. Observational Medical Outcomes Partnership is public–private partnership among FDA, academia, owners, pharmaceutical industry responding need advance science active product safety surveillance by existing observational databases. Partnership's transparent, open innovation approach designed...
Abstract Introduction Critical illness is a well-recognized cause of neuromuscular weakness and impaired physical functioning. Physical therapy (PT) has been demonstrated to be safe effective for critically ill patients. The impact such an intervention on patients receiving extracorporeal membrane oxygenation (ECMO) not well characterized. We describe the feasibility active PT ECMO Methods performed retrospective cohort study 100 consecutive in medical intensive care unit university...
Signal-detection algorithms (SDAs) are recognized as vital tools in pharmacovigilance. However, their performance characteristics generally unknown. By leveraging a unique gold standard recently made public by the Observational Medical Outcomes Partnership (OMOP) and conducting systematic evaluation, we provide new insights into diagnostic potential of SDAs that routinely applied to US Food Drug Administration (FDA) Adverse Event Reporting System (AERS). We find can attain reasonable...
Abstract Objectives To evaluate the utility of applying Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) across multiple observational databases within an organization and to apply standardized analytics tools for conducting research. Materials methods Six deidentified patient-level datasets were transformed OMOP CDM. We evaluated extent information loss that occurred through standardization process. developed a analytic tool replicate cohort construction process...
Abstract Identification of adverse drug reactions (ADRs) during the post-marketing phase is one most important goals safety surveillance. Spontaneous reporting systems (SRS) data, which are mainstay traditional surveillance, used for hypothesis generation and to validate newer approaches. The publicly available US Food Drug Administration (FDA) Adverse Event Reporting System (FAERS) data requires substantial curation before they can be appropriately, applying different strategies cleaning...
<h3>Importance</h3> Although randomized clinical trials are considered to be the criterion standard for generating evidence, use of real-world evidence evaluate efficacy and safety medical interventions is gaining interest. Whether observational data can used address same questions being answered by traditional still unclear. <h3>Objective</h3> To identify number published in high-impact journals 2017 that could feasibly replicated using from insurance claims and/or electronic health records...
Abstract Objective To quantify the background incidence rates of 15 prespecified adverse events special interest (AESIs) associated with covid-19 vaccines. Design Multinational network cohort study. Setting Electronic health records and claims data from eight countries: Australia, France, Germany, Japan, Netherlands, Spain, United Kingdom, States, mapped to a common model. Participants 126 661 070 people observed for at least 365 days before 1 January 2017, 2018, or 2019 13 databases. Main...
Abstract Objective To develop a conceptual prediction model framework containing standardized steps and describe the corresponding open-source software developed to consistently implement across computational environments observational healthcare databases enable sharing reproducibility. Methods Based on existing best practices we propose 5 step for: (1) transparently defining problem; (2) selecting suitable datasets; (3) constructing variables from data; (4) learning predictive model; (5)...
Abstract Objective We sought to assess the quality of race and ethnicity information in observational health databases, including electronic records (EHRs), propose patient self-recording as an improvement strategy. Materials Methods assessed completeness large databases United States (Healthcare Cost Utilization Project Optum Labs), at a single healthcare system New York City serving racially ethnically diverse population. compared data collected via administrative processes with recorded...
<h3>Importance</h3> Current guidelines recommend ticagrelor as the preferred P2Y12 platelet inhibitor for patients with acute coronary syndrome (ACS), primarily based on a single large randomized clinical trial. The benefits and risks associated vs clopidogrel in routine practice merits attention. <h3>Objective</h3> To determine association of ischemic hemorrhagic events undergoing percutaneous intervention (PCI) ACS practice. <h3>Design, Setting, Participants</h3> A retrospective cohort...
Hydroxychloroquine, a drug commonly used in the treatment of rheumatoid arthritis, has received much negative publicity for adverse events associated with its authorisation emergency use to treat patients COVID-19 pneumonia. We studied safety hydroxychloroquine, alone and combination azithromycin, determine risk routine care arthritis.
ACE (angiotensin-converting enzyme) inhibitors and angiotensin receptor blockers (ARBs) are equally guideline-recommended first-line treatments for hypertension, yet few head-to-head studies exist. We compared the real-world effectiveness safety of versus ARBs in treatment hypertension. implemented a retrospective, new-user comparative cohort design to estimate hazard ratios using techniques minimize residual confounding bias, specifically large-scale propensity score adjustment, empirical...
Abstract Importance The Observational Health Data Sciences and Informatics (OHDSI) is the largest distributed data network in world encompassing more than 331 sources with 2.1 billion patient records across 34 countries. It enables large-scale observational research through standardizing into a common model (CDM) (Observational Medical Outcomes Partnership [OMOP] CDM) requires comprehensive, efficient, reliable ontology system to support harmonization. Materials methods We created OHDSI...
Abstract Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, methods exist construct them automatically. However, tackling biomedical problems flexibility way knowledge is modeled. Moreover, existing KG construction provide robust tooling cost...
Importance Semaglutide, a glucagonlike peptide-1 receptor agonist (GLP-1RA), has recently been implicated in cases of nonarteritic anterior ischemic optic neuropathy (NAION), raising safety concerns the treatment type 2 diabetes (T2D). Objective To investigate potential association between semaglutide and NAION Observational Health Data Sciences Informatics (OHDSI) network. Design, Setting, Participants This was retrospective study across 14 databases (6 administrative claims 8 electronic...
Often the literature makes assertions of medical product effects on basis ‘ p < 0.05’. The underlying premise is that at this threshold, there only a 5% probability observed effect would be seen by chance when in reality no effect. In observational studies, much more than randomized trials, bias and confounding may undermine premise. To test premise, we selected three exemplar drug safety studies from literature, representing case–control, cohort, self‐controlled case series design. We...
Background: Expanded availability of observational healthcare data (both administrative claims and electronic health records) has prompted the development statistical methods for identifying adverse events associated with medical products, but operating characteristics these when applied to real‐world are unknown. Methods: We studied performance eight analytic estimating strength association‐relative risk (RR) standard error 53 drug–adverse event outcome pairs, both positive negative...