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1.  Using GEM-encoded guidelines to generate medical logic modules. 
Among the most effective strategies for changing the process and outcomes of clinical care are those that make use of computer-mediated decision support. A variety of representation models that facilitate computer-based implementation of medical knowledge have been published, including the Guideline Elements Model (GEM) and the Arden Syntax for Medical Logic Modules (MLMs). We describe an XML-based application that facilitates automated generation of partially populated MLMs from GEM-encoded guidelines. These MLMs can be further edited and shared among Arden-compliant information systems to provide decision support. Our work required three steps: (a) Knowledge extraction from published guideline documents using GEM, (b) Mapping GEM elements to the MLM slots, and (c) XSL transformation of the GEM-encoded guideline. Processing of a sample guideline generated 15 MLMs, each corresponding to a conditional or imperative element in the GEM structure. Mechanisms for linking various MLMs are necessary to represent the complexity of logic typical of a guideline.
PMCID: PMC2243667  PMID: 11825147
2.  An implementation framework for GEM encoded guidelines. 
Access to timely decision support information is critical for delivery of high-quality medical care. Transformation of clinical knowledge that is originally expressed in the form of a guideline to a computable format is one of the main obstacles to the integration of knowledge sharing functionality into computerized clinical systems. The Guideline Element Model (GEM) provides a methodology for such a transformation. Although the model has been used to store heterogeneous guideline knowledge, it is important to demonstrate that GEM markup facilitates guideline implementation. This report demonstrates the feasibility of implementation of GEM-encoded guideline recommendations using Apache Group s Cocoon Web Publishing Framework. We further demonstrate how XML-based programming allows for maintaining the separation of guideline content from processing logic and from presentation format. Finally, we analyze whether the guideline authors original intent has been sufficiently captured and conveyed to the end user.
PMCID: PMC2243348  PMID: 11825181
3.  A preliminary evaluation of guideline content mark-up using GEM--an XML guideline elements model. 
OBJECTIVE: To describe application of GEM to analysis and categorization of guideline content. METHOD: We examined the application of GEM constructs to the AAP guideline on neurodiagnostic evaluation of febrile seizures. Subjects at 4 sites marked-up the guideline content using a hierarchical template that includes branches for identity, developer, purpose, intended audience, method of development, knowledge components, testing, and review. The types of elements used were tabulated. Subjects were surveyed regarding the usability of the model. RESULTS: Eight subjects analyzed the guideline, using between 46 and 149 elements to model its content. There was considerable variation in the application of elements. The number of elements used correlated with time to complete the task. Subjects found application of GEM to be straightforward in 6 of 8 categories and sufficiently comprehensive to model the guideline's information content. CONCLUSIONS: Subjects found GEM constructs were able to model the content of the guideline. Improved editing tools will facilitate translation.
PMCID: PMC2243751  PMID: 11079916
4.  User satisfaction and frustration with a handheld, pen-based guideline implementation system for asthma. 
OBJECTIVE: To evaluate clinicians' satisfaction and frustrations with the use of a handheld computer system that implements a guideline for management of childhood asthma exacerbations. SETTING: Nine primary-care pediatric practices. DESIGN: Survey component of a randomized, prospective before-after trial. INTERVENTION: Newton MessagePad outfitted with custom software (called "AsthMonitor") that assists in documentation of clinical findings and provides guideline-based recommendations. RESULTS: Overall, 3 users gave strongly positive global ratings while 6 users were neutral. The majority used the documentation functions concurrently with care. Except for recommendations to administer oxygen (which were unsupported by evidence), users found the recommendations appropriate and appreciated the reminders. Seven of 9 participants believed it took more time to document with AsthMonitor. CONCLUSIONS: Handheld computers are acceptable to some office-based practitioners to provide guideline-based advice within the context of the clinical encounter.
PMCID: PMC2232865  PMID: 10566499
5.  Operationalization of clinical practice guidelines using fuzzy logic. 
There are a number of obstacles to successful operationalization of clinical practice guidelines, including the difficulty in accurately representing a statement's decidability or an action's executability. Both require reasoning with incomplete and imprecise information, and we present one means of processing such information. We begin with a brief overview of fuzzy set theory, in which elements can have partial memberships in multiple sets. With fuzzy inferencing, these sets can be combined to create multiple conclusions, each with varying degrees of truth. We demonstrate a fuzzy model developed from a published clinical practice guideline on the management of first simple febrile seizures. Although the creation of fuzzy sets can be an arbitrary process, we believe that fuzzy inferencing is an effective tool for the expression of guideline recommendations, and that it can be useful for the management of imprecision and uncertainty.
PMCID: PMC2233344  PMID: 9357633
6.  A findings model for an ambulatory pediatric record: essential data, relational modeling, and vocabulary considerations. 
Effective, computer-based representation of clinical observations requires balancing the advantages of structured, coded descriptions against those of free text narrative. An essential data set of relevant signs and symptoms was defined by a multidisciplinary group based on management goals published in a national guideline to meet the needs of clinicians in the Spina Bifida Clinic at Yale-New Haven Hospital. These core data elements are stored in a structured format. Additional material is stored as free text. A relational schema was devised that permits storage of both coded findings and narrative. Symptoms and signs are represented as subtypes of a supertype patient finding entity; they inherit common attributes and specialize others. The IVORY vocabulary was supplemented and modified to provide terms that describe relevant clinical observations. For this application, fields were added that enable predictive data entry of findings based on patient age and gender.
PMCID: PMC2579125  PMID: 8563313
7.  Towards effective implementation of a pediatric asthma guideline: integration of decision support and clinical workflow support. 
Successful local implementation of national guideline recommendations requires attention to factors that promote clinician compliance. Design of a computerized system is described that will implement recommendations from a recently published guideline for outpatient management of childhood asthma exacerbations. Logical analysis of the guideline shows that it is incomplete and contains several ambiguities that must be addressed before the guideline can be operationalized. Once the user-audience is defined guideline decision points are examined and a structured data entry system is devised. Support of clinicians' workflow is provided by an integrated capability for encounter documentation, dosage calculation, and prescription-writing. A pen-based, graphical interface represents an appropriate platform for implementation of the system because of its ease of use and portability.
PMCID: PMC2247945  PMID: 7950034
8.  Translation of appropriateness criteria into practice guidelines: application of decision table techniques to the RAND criteria for coronary artery bypass graft. 
The process of creating clinical practice guidelines from collected evidence has not been well defined. We have developed a technique for translation of a comprehensive set of appropriateness criteria into a usable set of practice guidelines. The criteria are derived from a formal consensus process conducted by RAND and relate to indications for coronary artery bypass graft in acute myocardial infarction. The clinical indications defined by the expert panel are entered as conditions in a decision table. For each combination of relevant clinical findings, the recommended action is defined from the median ranking of the Rand panel. The fully constructed table is next compacted by conventional decision table techniques and sorted to facilitate parsing the knowledge. Ultimately, 8 narrative statements are derived from 51 rules. Augmented decision tables permit display of detailed data in the summary table and its access on an as-needed basis.
PMCID: PMC2248512  PMID: 8130471
9.  Rule set reduction using augmented decision table and semantic subsumption techniques: application to cholesterol guidelines. 
Clinical practice guidelines must comprehensively address all logically possible situations, but this completeness may result in sizable and cumbersome rule sets. We applied rule set reduction techniques to a 576-rule set regarding recommendations for medication treatment of hypercholesterolemia. Using decision tables augmented with information regarding test costs and rule application frequencies, we sorted the rule sets prior to identifying irrelevant tests and eliminating unnecessary rules. Alternatively, we examined the semantic relationships among risk factors in hypercholesterolemia and applied a subsumption technique to reduce the rule set. Both methodologies resulted in substantial rule set compression (mean, 48-70%). Subsumption techniques proved superior for compacting a large rule set based on risk factors.
PMCID: PMC2248051  PMID: 1482893
10.  Use of augmented decision tables to convert probabilistic data into clinical algorithms for the diagnosis of appendicitis. 
Decision table techniques have been shown to be useful for ensuring logical completeness, eliminating ambiguity, and optimizing the translation of logic into flowcharts or computer programs. Nevertheless, they have not been widely applied in medicine. We have used decision table techniques to demonstrate the derivation of two sets of rules for determining whether to operate on patients with suspected appendicitis based on patterns of observed signs and symptoms. One rule set is based on a diagnostic threshold whereby morbidity is minimized; the other rule set minimizes mortality. For this purpose, we have developed an augmented decision table format that allows the incorporation of probability and utility data.
PMCID: PMC2247618  PMID: 1807691
11.  Composing user models through logic analysis. 
The evaluation of tutorial strategies, interface designs, and courseware content is an area of active research in the medical education community. Many of the evaluation techniques that have been developed (e.g., program instrumentation), commonly produce data that are difficult to decipher or to interpret effectively. We have explored the use of decision tables to automatically simplify and categorize data for the composition of user models--descriptions of student's learning styles and preferences. An approach to user modeling that is based on decision tables has numerous advantages compared with traditional manual techniques or methods that rely on rule-based expert systems or neural networks. Decision tables provide a mechanism whereby overwhelming quantities of data can be condensed into an easily interpreted and manipulated form. Compared with conventional rule-based expert systems, decision tables are more amenable to modification. Unlike classification systems based on neural networks, the entries in decision tables are readily available for inspection and manipulation. Decision tables, descriptions of observations of behavior, also provide automatic checks for ambiguity in the tracking data.
PMCID: PMC2247617  PMID: 1807690

Results 1-11 (11)