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Definition of an XML Markup Language for Clinical Laboratory Procedures and Comparison with Generic XML Markup

Centers for¹ Biomedical Informatics and ² Pathology Informatics and Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh PA.
Current addresses:³ Division of Informatics and Department of Health and Community Systems, School of Nursing, University of Pittsburgh, Pittsburgh PA; and ⁴ Division of Clinical Informatics and Departments of Public Health Sciences and Pathology, University of Virginia School of Medicine, Charlottesville VA.

^aAddress correspondence to this author at: Department of Public Health Sciences, P.O. Box 800717, Charlottesville VA 22908. Fax 434-924-8437; e-mail james.harrison{at}virginia.edu.

Background: Clinical laboratory procedure manuals are typically maintained as word processor files and are inefficient to store and search, require substantial effort for review and updating, and integrate poorly with other laboratory information. Electronic document management systems could improve procedure management and utility. As a first step toward building such systems, we have developed a prototype electronic format for laboratory procedures using Extensible Markup Language (XML).

Methods: Representative laboratory procedures were analyzed to identify document structure and data elements. This information was used to create a markup vocabulary, CLP-ML, expressed as an XML Document Type Definition (DTD). To determine whether this markup provided advantages over generic markup, we compared procedures structured with CLP-ML or with the vocabulary of the Health Level Seven, Inc. (HL7) Clinical Document Architecture (CDA) narrative block.

Results: CLP-ML includes 124 XML tags and supports a variety of procedure types across different laboratory sections. When compared with a general-purpose markup vocabulary (CDA narrative block), CLP-ML documents were easier to edit and read, less complex structurally, and simpler to traverse for searching and retrieval.

Conclusion: In combination with appropriate software, CLP-ML is designed to support electronic authoring, reviewing, distributing, and searching of clinical laboratory procedures from a central repository, decreasing procedure maintenance effort and increasing the utility of procedure information. A standard electronic procedure format could also allow laboratories and vendors to share procedures and procedure layouts, minimizing duplicative word processor editing. Our results suggest that laboratory-specific markup such as CLP-ML will provide greater benefit for such systems than generic markup.