gender of study participants. Some use 1 and 0 for male and female, others 1 and 2, others M and F, and others an arbitrary designation. Health Level 7 (HL7) has about 15 options for the gender field, she said, depending on how people define themselves. With so many systems and no standards for data collection and reporting, data often have to be examined by hand just to determine something as simple as how many males or females are in a study. Using data standards, such as those being developed by CDISC and other standards development organizations (SDOs), can save significant time and cost, especially when implemented in the early stages of the study, said Kush. She reemphasized the value of developing standards a priori around a core dataset that is required across all trials. Information is lost when data are gathered in different ways and later mapped to common standards. Standardization also provides opportunities for additional impact on clinical research through increased data quality, better data integration and reusability, facilitation of data exchange and communication with partners, interoperability of software tools, and facilitation of regulatory reviews and audits.

Laura Lyman Rodriguez, director of the Office of Policy, Communications, and Education at the National Human Genome Research Institute, observed that the Institute has been thinking about issues of standardization as it has constructed large data repositories that combine genomic information with phenotype information. For example, the PhenX project, through a consensus process, has been working to create standard measures of phenotypes and environmental exposures for use in population-based genomic studies to facilitate cross-study comparisons and analysis. Standardized taxonomies to describe phenotypes ensure that different studies share a common vocabulary. Agreeing with several earlier speakers, Rodriguez emphasized that standards do not ensure quality and that the value of standardization is best realized when it is done upfront. However, aligning interests in the development of data standards and the sharing of data is not easy, she said. The search for common interests requires identifying common values and integrating them into the research enterprise. Communication and transparency can help identify and spread these common values while also building public trust.

Sharing and accessing clinical information is a global issue, said Neil de Crescenzo, senior vice president and general manager at Oracle Health Sciences. For a number of projects in which Oracle has been involved, there has been heavy emphasis on data standardization. Innovation and progress in clinical research and care will depend on immense

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