how demographic (e.g., gender) and clinical information is recorded or defined.
The value of shared clinical data is undermined when those data cannot be used to answer new questions through secondary analysis. Standards can help facilitate pooling of data from disparate sources, either to increase sample sizes or for comparison purposes. By harmonizing vocabularies standards can also help to ensure that researchers are “speaking the same language.”
Meredith Nahm, associate director for clinical research informatics at the Duke Translational Medicine Institute, emphasized that a major function of data sharing is reuse of data for purposes other than those intended by the people who collected the data. If the data are not defined well enough that others can use them, then the original researchers have not done their jobs well, she said. Data reuse requires both standards and a level of rigor and semantic specificity sufficient not just for human, but also for computational analysis. For example, she briefly described an effort by the Clinical Trials Network at the National Institute on Drug Abuse to de-identify data, align the data to Clinical Data Interchange Standards Consortium (CDISC) standards, and make the data available on the Web. Because data elements and tools were defined and implemented uniformly across the network, the mapping of the data onto the CDISC Study Data Tabulation Model (SDTM) standard was relatively straightforward, facilitating pooled analysis and cross-product comparisons.
As an example of the difficulties in synthesizing a common set of data element standards retrospectively from case reports, rather than having them defined upfront, she mentioned the different ways in which sponsors operationalized critical variables in clinical trials on treatment of schizophrenia. As a result, each trial examined yielded fewer and fewer instances of new semantic content. Authoritative clinical definitions are essential, she said, to reduce the burden on clinical investigational sites and to support the compilation and reuse of data for health care, research, and regulatory decision making. “It all depends on the data element as the atomic level of information exchange.”
To demonstrate the need for standards to ensure that shared data can be pooled and compared, Rebecca Kush, CDISC president and chief executive officer, described the many different systems for reporting the