ing the data elements (including sequencing and error handling) (Hammond, 2002). Interchange standards can also include document architectures for structuring data elements as they are exchanged and information models that define the relationships among data elements in a message.

  • Terminologies—the medical terms and concepts used to describe, classify, and code the data elements and data expression languages and syntax that describe the relationships among the terms/concepts.

  • Knowledge Representation—standard methods for electronically representing medical literature, clinical guidelines, and the like for decision support.

At the most basic level, data standards are about the standardization of data elements: (1) defining what to collect, (2) deciding how to represent what is collected (by designating data types or terminologies), and (3) determining how to encode the data for transmission. The first two points apply to both paper-based and computer-based systems; for example, a laboratory test report will have the same data elements whether paper or electronic. A data element is considered the basic unit of information, having a unique meaning and subcategories of distinct units or values (van Bemmel and Musen, 1997). In computer terms, data elements are objects that can be collected, used, and/or stored in clinical information systems and application programs, such as patient name, gender, and ethnicity; diagnosis; primary care provider; laboratory results; date of each encounter; and each medication. Data elements of specific clinical information, such as blood glucose level or cholesterol level, can be grouped together to form datasets for measuring outcomes, evaluating quality of care, and reporting on patient safety events.

Associated with data elements are data types that define their form. Simple data types include date, time, numeric, currency, or coded elements that rely on terminologies (Hammond, 2002). Examples of complex data types are names (a structure for names) and addresses. For comparability and interchange, data types must be universal and must be carried through all uses of the data. The designation of common scientific units is also necessary. Units (e.g., kilograms, pounds) must be specified as another measure to prevent adverse events such as those related to dosing errors. Until recently, each institution or organization defined independently the data it wished to collect and the units employed, did not use data types, and created local vocabularies, resulting in fragmentation that prevented reuse.

For data elements that rely on terminologies and their codes for definition, merely referencing a terminology alone does not provide enough speci-

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