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Purpose: A new model expressing Arden Syntax with the eXtensible Markup Language (XML) was developed to increase its portability., Methods: Every example was manually parsed and reviewed until the schema and the style sheet were considered to be optimized. When the first schema was finished, several MLMs in Arden Syntax Markup Language (ArdenML) were validated against the schema. They were then transformed to HTML formats with the style sheet, during which they were compared to the original text version of their own MLM. When faults were found in the transformed MLM, the schema and/or style sheet was fixed. This cycle continued until all the examples were encoded into XML documents. The original MLMs were encoded in XML according to the proposed XML schema and reverse-parsed MLMs in ArdenML were checked using a public domain Arden Syntax checker., Results: Two hundred seventy seven examples of MLMs were successfully transformed into XML documents using the model, and the reverse-parse yielded the original text version of MLMs. Two hundred sixty five of the 277 MLMs showed the same error patterns before and after transformation, and all 11 errors related to statement structure were resolved in XML version. The model uses two syntax checking mechanisms, first an XML validation process, and second, a syntax check using an XSL style sheet., Conclusion: Now that we have a schema for ArdenML, we can also begin the development of style sheets for transformation ArdenML into other languages.

Purpose: To improve the completeness and timeliness of an electronic problem list, we have developed a system using Natural Language Processing (NLP) to automatically extract potential medical problems from clinical, free-text documents; these problems are then proposed for inclusion in an electronic problem list management application., Methods: A prospective randomized controlled evaluation of the Automatic Problem List (APL) system in an intensive care unit and in a cardiovascular surgery unit is reported here. A total of 247 patients were enrolled: 76 in an initial control phase and 171 in the randomized controlled trial that followed. During this latter phase, patients were randomly assigned to a control or an intervention group. All patients had their documents analyzed by the system, but the medical problems discovered were only proposed in the problem list for intervention patients. We measured the sensitivity, specificity, positive and negative predictive values, likelihood ratios and the timeliness of the problem lists., Results: Our system significantly increased the sensitivity of the problem lists in the intensive care unit, from about 9% to 41%, and even 77% if problems automatically proposed but not acknowledged by users were also considered. Timeliness of addition of problems to the list was greatly improved, with a time between a problem's first mention in a clinical document and its addition to the problem list reduced from about 6 days to less than 2 days. No significant effect was observed in the cardiovascular surgery unit.

Purpose: This report describes an ongoing transition from the HELP Hospital Information System to HELP II, a replacement Health Information System built to manage clinical information captured in a variety of medical settings. The focus of the article is on the medical decision support provided by this system and studied by researchers at the University of Utah and Intermountain Health Care (IHC), a large health care organization in Utah, for many years., Methods: Select success features of the original HELP system's decision support environment are identified and lessons learned are related. Plans for transferring these features to HELP II are discussed., Results: The article focuses on four features: (1) the importance of easy access to patient data essential for decision support, (2) the commitment to continued measurement and revision of both the logic and the interventional strategy in a decision support application, (3) experience with data mining as a tool for developing decision support tools, and (4) the role of clinical reports in supporting the decision making process.