report could be voluntarily submitted to the Food and Drug Administration (FDA), either through the FDA MedWatch reporting system or through private-sector organizations such as the United States Pharmacopia (USP), to inform the FDA of potential serious problems with the drug. Adding further to the burden of disparate and multiple methods for representing an ADE are the voluntary reporting requirements of the hospitals’ accrediting organization, the Joint Commission for Accreditation of Healthcare Organizations (JCAHO), whose proposed taxonomy provides yet another dataset for classifying and reporting such events. Already this example involves four different reports with varying data elements for the same ADE.

In the case of the FDA, reports are submitted to support the agency’s regulatory obligations for postmarket surveillance of drugs marketed in the United States, particularly those associated with ADEs. To this end, the organization needs the capability to analyze and compare the ADEs occurring during the clinical trial process with those experienced in clinical practice. However, the FDA uses one terminology, MedDRA, for representation of ADEs experienced by patients during clinical trials and documentation in the manufacturer’s dossier for regulatory approval, and another in its MedWatch reporting system. The agency also accepts data from private-sector organizations using different data standards. Thus, for the FDA alone, the data related to one particular ADE is represented by three different data sources. More importantly, the data from clinical trials and postmarket surveillance cannot be compared without costly mapping of the terms among the different taxonomies.

An additional consideration relates to the ability to share and compare data in integrated systems. For example, a clinician who wanted to conduct an analysis of or research on ADE reports compared with events detected and/or prevented with various decision support systems (e.g., pharmacy systems, computerized physician order entry, bar-code medication administration) could not do so without common methods for representing the most basic ADE data (e.g., drug involved, type of event, route of administration, dosage). The ability to compare the factors contributing to an ADE among systems would add to the knowledge and understanding of events. It would also provide a common reference point for classifying event data derived from other sources (e.g., malpractice claims, complaints, claims attachments) and different health care settings (e.g., primary care, inpatient, nursing home). However, such analysis cannot be undertaken without a common language.

The remedy for the disparate scenario described above is the development of a common reporting format of domain areas, data elements, and



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