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We analyzed query logs from use of MEDLINEplus to answer the questions: Are consumers' health information needs stable over time? and To what extent do users' queries change over time? To determine log stability, we assessed an Overlap Rate (OR) defined as the number of unique queries common to two adjacent months divided by the total number of unique queries in those months. All exactly matching queries were considered as one unique query. We measured ORs for the top 10 and 100 unique queries of a month and compared these to ORs for the following month. Over ten months, users submitted 12,234,737 queries;only 2,179,571 (17.8%) were unique and these had a mean word count of 2.73 (S.D., 0.24); 121 of 137 (88.3%) unique queries each comprised of exactly matching search term(s) used at least 5000 times were of only one word. We could predict with 95% confidence that the monthly OR for the top 100 unique queries would lie between 67% - 87% when compared with the top 100 from the previous month. The mean month-to-month OR for top 10 queries was 62% (S.D., 20%) indicating significant variability;the lowest OR of 33% between the top 10 in Mar.compared to Apr. was likely due to "new" interest in information about SARS pneumonia in Apr. 2003.Consumers' health information needs are relatively stable and the 100 most common unique queries are about 77% the same from month to month. Website sponsors should provide a broad range of information about a relatively stable number of topics. Analyses of log similarity may identify media-induced, cyclical,or seasonal changes in areas of consumer interest.

We are investigating the use of axiomatic design (AD) as a principled approach to the revision of guidelines. AD models guidelines in a modular and hierarchical manner and captures interactions be-tween modules. To test this approach we applied AD to encode segments of three guidelines and their revised versions. Guideline encodings for the original versions were modified to incorporate changes made in the revised documents. The results indicate that AD is a promising approach for guideline modeling.

GELLO is a purpose-specific, object-oriented (OO) query and expression language [1]. GELLO is the result of a concerted effort of the Decision Systems Group (DSG) working with the HL7 Clinical Decision Support Technical Committee (CDSTC) to provide the HL7 community with a common format for data encoding and manipulation. GELLO will soon be submitted for ballot to the HL7 CDSTC for consideration as a standard.

Representation of multi-step clinical guidelines (CG) and their implementation in computerized decision support (DS) systems are complex and logistically challenging tasks. However, many simple rules based on CGs (e.g., medical logic modules), have been successfully implemented through a few popular DS models (e.g., prevention reminders, order entry systems). To facilitate mapping of CGs to practical DS models, we propose an empirical method for sub-dividing CGs into modules according to the locus in a clinical process flow model where implementation would be most effective (e.g., post-encounter provider order entry). We further propose a classification of triggers and objectives for CG modules that provides a framework for a DS system to implement the module Successful application of the method to ten diverse CGs in the outpatient setting is described.

Clinical problem-solving exercises have long been used as a way of providing simulated experience with clinical medicine. Multimedia capabilities now available extend the potential for realism of these exercises. In addition, with the use of hypermedia methodologies, it is now possible to link components of a clinical case — e.g., the tests, the images (or sounds, or tracings) of the actual results, or the textual descriptions of findings — with other related information. This information can amplify on the tests themselves, the range of possible results that could alternatively have been obtained, the differential diagnosis of any particular finding, or the profiles of diseases in the differential, and can provide discussions and references about the diseases. Thus the case problem-solving exercise may have potential for more than providing practice with making clinical judgments; it may offer an alternative paradigm for accessing much of the same medical content traditionally delivered in didactic lectures and in textbook presentations. We have implemented an authoring environment for case problem-solving exercises that enables access to multimedia presentation of clinical results, and related clinical and pathophysiologic content material. Case simulations designed with this approach are currently being used in teaching first-year medical students in the HST track of the Harvard Medical School.

The Unified Medical Language Systems Project (UMLS) of the National Library of Medicine (NLM) has produced Meta-1, a metathesaurus featuring over 40,000 concepts and their synonyms from several commonly-used medical vocabularies. We have adapted Meta-1 for use in SAPHIRE, an information retrieval system featuring automated indexing and probabilistic retrieval. We have also built DESYGNS, a semantic network system designed to contain Meta-1 concepts along with their semantic relationships. Future plans include improved concept matching, improved indexing capability, and the use of semantic relationships.