Analysis of information needs of users of MEDLINEplus, 2002 - 2003.

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.

A methodology for modular representation of guidelines.

Computer-based clinical practice guidelines often need to be modified when medical knowledge evolves or when guidelines are implemented in a local setting with specific constraints and preferences. To enable easy modifications to guidelines and maintain their integrity, we have developed a methodology for modular representation of guidelines. Using this approach, we create guidelines in a hierarchical and modular manner. We use the Axiomatic Design methodology to facilitate the development of independent modules. Design matrices capture the interactions among modules. The design matrices can be used during guideline modification to create a change process and to enable identification of other modules that are affected by a change to a module. We implemented this modular knowledge representation approach by incorporating it into the Guideline Interchange Format (GLIF) language. We applied this approach to encode parts of three outdated guidelines released during 2000-2001, and we revised these designs to model updated releases of the guideline. Qualitative and quantitative metrics were developed to assess the types of changes made to the encoded guidelines.

Applying axiomatic design methodology for guideline revision.

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.