- Vaccines, Blood & Biologics
- Devices and Radiologic Health
The U.S. Food and Drug Administration leverages real-world electronic healthcare data (e.g., electronic health records, insurance claims) to support regulatory decision-making. Potential uses of real-world data (RWD) include quantifying the risk of outcomes too rare to fully assess in preapproval clinical trials or among excluded or underrepresented subpopulations, and continuous monitoring of important clinical outcomes. Prospective sequential surveillance involves multiple statistical evaluations on RWD that accumulate over time (i.e., adding new data for the same patient or adding new patients).
This presentation was delivered to the Reagan-Udall Foundation by representatives from the FDA, TriNetX, and Sentinel Operations Center.
The Sentinel Operations Center is partnering with TriNetX to monitor COVID-19 drug use for FDA.
View the TriNetX press release here.
The objective of this manuscript was to assess the relative frequency with which oxymorphone and oxycodone (a CYP3A-metabolized opioid analgesic) were each prescribed to patients concomitantly receiving CYP3A-modifying drugs (i.e., inducers and inhibitors) to characterize opioid-prescribing patterns in patients at risk for CYP3A-related drug interactions.
Sentinel routine querying tools are SAS programs designed to run against the Sentinel Common Data Model (SCDM). They allow rapid implementation of standard queries across the Sentinel Distributed Database (SDD). The programs can be customized using various input parameters that define medical product exposures, outcomes, covariates, diagnoses, date ranges, age ranges, and other implementation details. Tools can perform simple cohort characterization and descriptive analyses, but may also be used to perform more complex adjustment for confounding and support prospective surveillance activities.
The Cohort Identification and Descriptive Analysis (CIDA) module is the foundation of the routine querying system. CIDA is responsible for identifying, extracting, and characterizing cohorts of interest from the SDD based on the specification of a number of requester-defined options (e.g., continuous enrollment requirements, incidence criteria, inclusion/exclusion criteria).
FDA’s Sentinel System is engaged in numerous activities to protect and promote public health during the COVID-19 pandemic, ranging from monitoring the use of drugs, describing the course of illness among hospitalized patients, and evaluating the treatment impact of therapies actively being used under real-world conditions. Descriptions of efforts led by the Center for Drug Evaluation and Research are detailed in the link below.
This study aims to sequentially monitor priority drugs for the care of patients hospitalized with COVID-19, including sedatives and drugs used to assist with mechanical ventilation, therapies for respiratory diseases, thrombolytics, anticoagulants, anti-infectives, opioid analgesics and other drugs used to treat COVID-19. Drug utilization in the outpatient care setting will also be examined. The purpose of this activity is to assess changing patterns of use to support regional assessments of drug use and to assess for drug shortages.
The purpose of this project is to develop and implement a horizon scan and series of interviews to: (1) identify electronic health record (EHR) sources and registries; and (2) conduct initial feasibility assessment of these potential partners for enhancing the Sentinel System.
This specific project will involve three phases: (1) literature review and environmental scan; (2) interviews with representatives of the most promising data sources identified; and (3) presentations by selected EHR representatives to workgroup members.
The horizon scan will ensure a thorough search of U.S. EHR resources with a particular focus on identifying and evaluating potential sources of data on pediatric, cancer, and pregnancy/birth outcomes, as well as cause of death data. Furthermore, the horizon scan will consider EHR data sources that will be useful to address questions related to future COVID-like outbreaks.
The US Food and Drug Administration (FDA) Sentinel System uses a distributed data network, a common data model, curated real-world data, and distributed analytic tools to generate evidence for FDA decision-making. Sentinel system needs include analytic flexibility, transparency, and reproducibility while protecting patient privacy. Based on over a decade of experience, a critical system limitation is the inability to identify enough medical conditions of interest in observational data to a satisfactory level of accuracy. Improving the system’s ability to use computable phenotypes will require an “all of the above” approach that improves use of electronic health data while incorporating the growing array of complementary electronic health record data sources. FDA recently funded a Sentinel System Innovation Center and a Community Building and Outreach Center that will provide a platform for collaboration across disciplines to promote better use of real-world data for decision-making.
The Sentinel Data Quality Review and Characterization Programs are used by the Sentinel Operations Center (SOC) for data quality review and characterization of the Sentinel Distributed Database (SDD). To create the SDD, each Data Partner transformed local source data into the Sentinel Common Data Model (SCDM) format. The SOC created a set of data quality review and characterization programs to ensure that the SDD meets reasonable standards for data transformation consistency and quality and that the SDD data meets expectations needed for a distributed health data network.
The documentation, appendices, and SAS programs associated with version 6.2.0 of the Sentinel Data Quality Review and Characterization Programs can be found externally in Sentinel's Git Repository.
The project team, comprised of members from Kaiser Permanente Washington Health Research Institute (KPWHRI), Kaiser Permanente Northern California, Division of Research (KPNC), Kaiser Permanente Southern California (KPSC), Henry Ford Health System (HFHS), and Harvard Pilgrim Health Care Institute (HPHC), proposes a comprehensive program of infrastructure development, methods development, and innovative research to generate real-world evidence of suicide and suicidal ideation in the United States. The goal of this project is to enable a robust future program of research to evaluate the effects of medical products on suicidal ideation and behavior. Specific aims include:
The Sentinel Query Builder is a web application which allows users to visualize, draft, and create medical product utilization queries with a user-friendly interface from a set of pre-defined parameters and convert them into Sentinel query request packages. The Sentinel Query Builder application can now be downloaded onto users' computers.
The Sentinel Operations Center (SOC) has transformed the Medicare Claims Synthetic Public Use Files (SynPUFs) into the Sentinel Common Data Model (SCDM) format as part of an ongoing effort to make Sentinel resources available to external investigators, with the goal of creating a community of investigators who can understand, utilize, and contribute to the Sentinel enterprise.
The Sentinel Operations Center and IBM Watson Health have partnered to make SAS® code available for transforming the IBM MarketScan® Commercial and Medicare Supplemental Databases into the Sentinel Common Data Model.
The Sentinel Operations Center (SOC) coordinates the network of Sentinel Data Partners and leads development of the Sentinel Common Data Model (SCDM), a standard data structure that allows Data Partners to quickly execute distributed programs against local data.
Changes in this release from v6.0.2 to v7.0.0 include a new Mother-Infant Linkage table and are listed in the “History of Modifications” tab of the SCDM v7.0.0 document.