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Gilan M Saadawi

Publications and source records attributed to Gilan M Saadawi.

2 recordsLinked to original sources

Definition of an XML markup language for clinical laboratory procedures and comparison with generic XML markup.

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.

Clinical Laboratory Information Systems↗

A method for automated detection of usability problems from client user interface events.

Think-aloud usability analysis provides extremely useful data but is very time-consuming and expensive to perform because of the extensive manual video analysis that is required. We describe a simple method for automated detection of usability problems from client user interface events for a developing medical intelligent tutoring system. The method incorporates (1) an agent-based method for communication that funnels all interface events and system responses to a centralized database, (2) a simple schema for representing interface events and higher order subgoals, and (3) an algorithm that reproduces the criteria used for manual coding of usability problems. A correction factor was empirically determining to account for the slower task performance of users when thinking aloud. We tested the validity of the method by simultaneously identifying usability problems using TAU and manually computing them from stored interface event data using the proposed algorithm. All usability problems that did not rely on verbal utterances were detectable with the proposed method.

Algorithms↗