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FDA Adverse Events Reporting System
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Source U.S. Food and Drug Administration
Size 6.0 GB (entire collection); by year: 250-400 MB in 6-7 tables
Dates Covered 1998-Dec. 2007 (Plus archived records for old Spontaneous Reporting System 1969-1998)
Record Count over 3.3 million total records (1969-2006)
How Available Entire United States, all years
Cost: (1997-2006 AERS data)
  • 50-200 market or circulation below 50,000: $75
  • 26-50 market or circulation 50,000-100,000: $135
  • Top 25 market or circulation over 100,000: $210

  • Cost: (1969-1998 Archived SRS data)
  • 50-200 market or circulation below 50,000: $30
  • 26-50 market or circulation 50,000-100,000: $55
  • Top 25 market or circulation over 100,000: $75




  • About the Data:
    The FDA relies on the Adverse Event Reporting system to flag safety issues and identify pharmaceuticals or therapeutic biological products (such as blood products), for further epidemiological study. It may ultimately prompt regulatory responses such as drug labeling changes, letters to health care professionals, or market withdrawals.
    The agency requires product manufacturers and distributors to report adverse events regularly in accordance with 21 CFR 310.305 and 314.80. Mandatory reports for drugs in clinical trials and newly marketed drugs are submitted in various forms: 15-day alerts, quarterly or annual updates. The MedWatch program also collects voluntary reports from health care professionals and consumers. Adverse drug experiences include any serious and unexpected consequences of human drug use in a medical practice - such as failure of "expected pharmacological action," as well as accidental or intentional overdoses or abuse.

    AERS replaced the Spontaneous Reporting System in October 1997. The FDA estimates that 118 reports for 1997-98 are included in the old SRS data. The AERS collection begins with the fourth quarter of 1997 and is complete through December 2006. Emphasis on reporting and efficiency of collecting reports have fluctuated, as seen by the relatively small number of records for the earlier years in this dataset and the incomplete entries throughout.

    The AERS format attempts to improve and standardize the same basic information fields collected in SRS. The most notable difference between the two sets is a Comments table containing detailed memo fields; it only exists for SRS data 1993-1998.


    Related Resources

    Medical Device Reports (MAUDE):A database listing medical devices that have failed, how they failed and the manufacturer information.


    Mortality, multiple causes of death:The Mortality Multiple Cause-of-Death database contains detailed information found in standard death certificate records from the United States and its territories.


    Table Layouts and Sample Data:

  • Demo: Main table with patient's age and sex, name of manufacturer sending report, date of the event, date of the mfr's initial report, and date FDA received the file. FDA fields list an image-id that can be used as a reference in further inquiries and notes report type (expedited, periodid, direct) and whether it was an initial or follow-up report. A unique ISR# identifies each report and serves as a primary key for linking tables. See record layout
  • demo100.DBF
    demo100.xls
  • Drug: Information on the drug(s) or biologic product(s) in each report, including: drug name, role (primary suspect, concomitant, interacting, etc.), dose, route of administration, and rechallenge/dechallenge codes for result the outcome when drug therapy stopped or restarted. Other codes indicate whether the drug name was validated or taken verbatim off the report in a non-standard form. See record layout
  • drugs100.DBF
    drugs100.xls
  • Reaction: Describes the patient's reaction using standardized terms from the Medical Dictionary for Regulatory Activities (MedDRA).
  • rxn100.DBF
    rxn100.xls
    Instructions on opening DBF files in Access


    What you can do: Journalists who have used this data recommend using it to guide reporting on consumer medical issues, the FDA or the pharmaceutical industry.

    Note that AERS reports are not a stand-alone source or proof that certain drugs are the most dangerous. Only sound epidemiological research can provide conclusive evidence for comparing the safety of one drug to another. Complicated medical conditions, multiple drug interactions and other variables may contribute to outcomes in these reports. In the AERS data, drugs are classified as "primary suspect" or "concomitant" to address such issues.

    The AERs data does not contain any identifiable patient information or names of persons/facilities reporting the events and only the country the event occured in. The only identified reporters are manufacturers.


    STORIES AND TIPSHEETS FROM THE IRE RESOURCE CENTER:
    To order copies one or more of following stories call the IRE RESOURCE CENTER at 573-882-3364 and give them the FILE NUMBER or TIP SHEET NUMBER. The cost is 15 cents per page for IRE members.

    Story Number: 17401
    A CBS News investigation into the FDA reveals that the organization has approved a number of drugs despite objections from its own scientists. Among the questionably approved drugs was Rezulin, a diabetes drug, and Relenza, a flu drug. "The series exposed a serious rift between FDA rank-and-file scientists who felt their concerns were being ignored, and FDA executives who repeatedly sided with pharmaceutical companies over issues of safety regarding controversial drugs."

    Tipsheet Number: 1284
    Tips on how to find websites dealing with pharmaceuticals.

    Tipsheet Number: 1455
    Provides a listing of websites for information about drug trials; lists sites to help track money, survivors and doctors; Includes reference points to use in accountability; Lists other databases available on the FDA website that are helpful

    Tipsheet Number: 2161
    Adams lists sources of pharmaceutical data that include the National Ambulatory Medical Care Survey as well as data from the FDA. The background, data description and pitfalls are described for each dataset.