- Vaccines, Blood & Biologics
- Devices and Radiologic Health
As the prevalence of diabetes mellitus increases in the population, the exposure to antidiabetic drugs (ADDs) during pregnancies is expected to grow, as has been seen over the last decade. The objective of this study was to estimate the prevalence of ADD use during pregnancy among women in the Mini-Sentinel Distributed Database (MSDD) who delivered a liveborn infant. We identified qualifying livebirth pregnancies among women aged 10 to 54 years in the MSDD from 2001 to 2013. ADD use was estimated using outpatient pharmacy dispensing claims and days-supplied among three cohorts: all livebirth pregnancies, pregnancies among women with pre-existing diabetes, and pregnancies among women without prior ADD use.
The purpose of these reports was to compare the frequency of diagnoses for several selected health outcomes using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) versus International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes. These health outcomes include adult-onset Still's disease, alveolar proteinosis, interstitial lung disease, macrophage activation syndrome, non-Hodgkin's lymphoma, pulmonary arterial hypertension, and systemic juvenile idiopathic arthritis.
The purpose of this request was to estimate the number of pediatric patients with respiratory syncytial virus (RSV) and RSV-related events and related preventative services in the Sentinel Distributed Database (SDD).
Epidemiological study reporting is improving but is not transparent enough for easy evaluation or replication. One barrier is insufficient details about design elements in published studies. Using a previously conducted drug safety evaluation in claims as a test case, we investigated the impact of small changes in five key design elements on risk estimation. These elements are index day of incident exposure's determination of look-back or follow-up periods, exposure duration algorithms, heparin exposure exclusion, propensity score model variables, and Cox proportional hazard model stratification. We covaried these elements using a fractional factorial design, resulting in 24 risk estimates for one outcome. We repeated eight of these combinations for two additional outcomes. We measured design effects on cohort sizes, follow-up time, and risk estimates.
In these reports, we present incident and prevalent use of sodium-glucose cotransporter-2 (SGLT-2) inhibitors and obesity drugs dispensed in the Sentinel Distributed Database (SDD).
Healthcare databases are very useful sources of post-marketing real-world information, generating evidence on drug use, safety and effectiveness, particularly in populations where such information may be lacking in pre-clinical studies, such as paediatric and geriatric populations. However, healthcare databases can also provide pre-marketing information by measuring the burden of disease, identifying unmet clinical needs and estimating the number of patients potentially eligible for innovative and costly treatment. Whether in a pre- or post-marketing setting, these data sources can provide regulatory agencies with evidence that can inform the development/implementation of regulatory interventions and answer questions of high, and often urgent, public health interest. In April 2019, the Italian Drug Agency (Agenzia Italiana del Farmaco) organised a workshop on the role of healthcare databases in supporting drug regulatory agencies in their pre- and post-marketing regulatory activities. The experiences of the USA, Canada, Spain and Italy in this context were presented.
Our objective was to estimate use of hydroxyprogesterone caproate and progesterone during the second or third trimesters among pregnancies that ended with a live-birth delivery in the Sentinel Distributed Database (SDD). We identified live-birth deliveries occurring between January 1, 2008 to April 30, 2019. We distributed this request on August 5, 2019 to 15 Data Partners contributing to the SDD.
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 6.0.0 of the Sentinel Data Quality Review and Characterization Programs can be found externally in Sentinel's Git Repository.
This study was designed to estimate real-world off-label use of sodium–glucose cotransporter 2 (SGLT2) inhibitors in patients with type 1 diabetes, estimate rates of diabetic ketoacidosis (DKA), and compare them with DKA rates observed in sotagliflozin clinical trials. This study identified initiators of SGLT2 inhibitors in the Sentinel system from March 2013 to June 2018, determined the prevalence of type 1 diabetes using a narrow and a broad definition, and measured rates of DKA using administrative claims data. Standardized incidence ratios (SIRs) were calculated using age- and sex-specific follow-up time in Sentinel and age- and sex-specific DKA rates from sotagliflozin trials 309, 310, and 312.
Sentinel has created the Sentinel CMS DataMart, containing 100% Medicare FFS administrative claims data housed in the Center for Medicare and Medicaid Services' CMS Virtual Research Data Center (VRDC). Duke University Department of Population Health Sciences (DPHS) serves as the Sentinel Data Partner in accessing the source data in the VRDC, transforming it into a Sentinel Common Data Model (SCDM) compliant database, executing queries, and returning results to the Sentinel Operations Center (SOC). There are three components made available to the public: (1) Program Specifications; (2) Code pack; and (3) User Guide.
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) program 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).
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.