All drugs are approved by regulatory agencies after proof that they are safe and efficacious. In the US, the FDA approves each drug for marketing in the country. The DRUG_APPROVAL table contains the approval date for each ingredient in the Standard Vocabulary:
|APPROVAL_DATE||Contains the approval date (see below)|
Contains the CONCEPT_ID of the ingredient, e.g. 778268 for "Imipramine".|
|APPROVED_BY||Contains the name of the regulatory agency. Currently, all records contain "FDA" as only FDA approvals are included.|
The approval date was determined as follows:
Records from the regulatory action database the FDA publishes at http://www.fda.gov/Drugs/InformationOnDrugs/ucm079750.htm were selected where the regulatory action was "Approval". These records were parsed for their product (active ingredient), and the earliest date an active ingredient ever received approval, in a standalone or combination drug, was selected as approval date. These active ingredients were mapped to the RxNorm ingredient records (vocabulary_id=8, concept_level=2).
Note: The date is the first approval date of an active ingredient. It does not contain approval dates for individual products, whether innovator or generic.
|Concept ID||Concept Name||Approval Date|
In order to interpret the results of any analysis on a data source, the characteristics of the data source be clearly understood. The Observational Source Characteristics Analysis Report (OSCAR) provides a systematic approach for summarizing all observational healthcare data within the OMOP common data model. The procedure creates structured output of descriptive statistics for all relevant tables within the model to facilitate rapid summary and interpretation of the potential merits of a particular data source for addressing active surveillance needs.
Observational Source Characteristics Analysis Report (OSCAR) and Source Code:
If you have implemented CDM v4.0, use OSCAR for CDM v4.0 otherwise, use OSCAR for CDM v2.0.
OSCAR code and specifications for CDM v4.0
OSCAR code and specifications for CDM v2.0
OSCAR has many uses, including:
OSCAR provides descriptive statistics that summarizes the entire database as a means to benchmark all studies. The diagram below outlines how we envision OSCAR fitting into the workflow for validating the transformation from raw data to the OMOP common data model.
The only prerequisite for OSCAR is that the program must be applied to a data source that conforms to the OMOP common data model, including all necessary tables and fields, and SAS 9.1 has to be available. OSCAR creates a summary result dataset in a structured format. This dataset contains descriptive statistics for all the various data elements with the common data model, but do not contain any person-level data. Organizations within the OMOP Data Community are encouraged to share these aggregate summary results by loading them into the OMOP Research Lab, where comparative analyses across the different sources can be conducted.
This page provides a simple power estimator for drug-outcome research. For each drug ingredient and each Health Outcome of Interest, an estimated minimal detectable relative risk (MDRR) can be computed. This MDRR can be detected given the population size of the database and the frequency of drug and outcome in 10 age and 2 gender strata:
The MDRR decreases over time with more and more drug exposure. It is important for newly introduced drugs to know when sufficient sample size has accumulated to power a MDRR of as low as necessary to detect typical drug outcome risks. This following provides the MDRR over time for detection the 35 HOIs for all drugs introduced to the market between 2003 and 2009 .