Drug Information Journal - March 2009 - (Page 137) Reusing Clinical Protocol Content to Improve Productivity MEDICAL INFORMATION 137 Document metadata are simply bits of information describing the document, typically accessed in a properties dialog; such metadata include key words, author names, title, and so on. Working within a document-metadata environment, information users find related concepts contained in separate documents by searching on the combination of a concept and a text string. The work flow is much simpler in a semantic knowledge repository environment, such as that enabled by use of extensible protocols, because metadata richly populate every document automatically as it is created. That is, the study metadata—the numerical and textual data describing the collected study data—themselves become the original source material. Research documents are simply manifestations (archived instances) of study metadata. Study metadata collected from extensible documents may be archived, analyzed, and combined conceptually, independent from—although still referencing—the documents from which they were originally generated, offering novel knowledge propagation and project metrics capabilities. Finally, structured information reuse is facilitated by automated population of dependent documents and information systems with authoritative source content. Here dependence may be viewed as a time sequence of document or system finalization. Thus, document Y is said to be dependent on document X because document Y cannot be completed before document X is completed. Although some human intervention is needed to perform these tasks, they should be far less susceptible to data corruption or loss than conventional copy/paste and file transfer methods used routinely today, with the use of appropriate controls (ie, automated checks and warnings) and operating procedures. CONCLUSION The protocol contains most of the information needed to describe and conduct a clinical research study. When a protocol is sufficiently represented as computer-analyzable—sometimes termed machine-readable—data, its con- tent may be construed as the definitive source of study metadata. As such metadata are used and referenced continually throughout a trial and are necessary to identify and interpret outcomes from a trial, the protocol and its contributors may be viewed as centrally located in a clinical research knowledge network that influences both the scientific output of a study and its operational efficiency. The influence of the protocol on study operational efficiency has been recognized for some time (13,14). But it has not been as widely appreciated that the effect of protocols on study operational efficiency depends in part (perhaps in large part) on knowledge transfer efficiencies among the clinical research knowledge network. Specifically, knowledge must be transferred between protocol contributors and authors of protocol-dependent documents and to the data managers and end users of protocol-dependent information systems efficiently in order for a study to operate efficiently. Such knowledge transfer, in turn, depends upon the fidelity of formal and informal modes of information transmission and reuse, because error-prone communications necessarily lead to the nonvalue-adding activities of locating definitive source information and correcting information errors after they have been incorporated or implemented (eg, protocol amendments, EDC rebuilds). Representing protocol information as structured, computer-analyzable data—study metadata—that can be exported and shared directly with dependent information systems creates opportunities for markedly improving the fidelity of information transmission and reuse and thus for increasing the efficiency of knowledge transfer throughout the knowledge network. Specifically, reuse efficiency gains are possible at each of the five steps of a typical information reuse cycle. Efficiency gains will be most easily recognizable and measurable at the information interpretation step, which can be disruptively impacted by streaming content from system to system with minimal human intervention, thus avoiding the opportunity for error introductions and rework delays caused by ambiguous Drug Information Journal
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