Introduction 1 2 3 4 5 6 7 8 syntactic reformulation Semantic reformulation 9 search filters 10 11 meta-search filters 4 Methods The Quick Clinical System User Interface Figure 1 Figure 1 Figure 2 Quick Clinical System Architecture Overview 13 12 Figure 3 Figure 3 Unified Query Language UQL is used to represent queries obtained from users in a consistent internal way, and UQL statements identify query elements such as the external information sources to be searched and a set of search attributes used to delimit the search. For example, UQL expressions can store date range delimiters for a search. UQL also contains statements that indicate whether or not QC needs to process the query further. For example, we may wish to remove duplicate items obtained from different sources. In our current implementation, UQL is implemented using XML. To define the structure of the data within the XML document we use a data type definition (DTD), which allows various internal components of QC to validate the XML data received in the UQL query. The following example illustrates how a UQL query might look in XML. Unified Response Language Similarly to the UQL, the unified response language (UReL) is used internally to guide display of information to users, also represented using XML. Each separate result, or “article,” from a source can be broken up into smaller chunks and given meta-data labels to represent the different sections of the data (eg, abstracts from journal articles). Since the majority of sources accessed by QC are journals, the data that are retrieved typically contain document elements such as Title, Author(s), Journal Name, Date of Publication, and the URL where the electronic version of the paper is accessed. Other sources, such as drug descriptions from pharmaceutical compendia, have sections such as Drug Name and Manufacturer. These different document elements, based upon the typical sources QC expects to find, are defined as specific fields in the UReL definition. The following example illustrates how a set of documents retrieved by QC might be represented in UReL.
http://www.ncbi.nlm.nih.gov:80 /entrez/query.fcgi?cmd=Retrieve&db=PubMed &list_uids=12198020&dopt=Abstract Abstract Heath AL, Skeaff CM, Gibson RS. Dietary treatment of iron deficiency 2002 9 PubMed
http://mims.hcn.net.au /ifmx-nsapi/mims-data/?MIval=2MIMS_abbr_pi &product_code=288 &product_name=Ferrum+H+Injection More Information Sigma Pharmaceuticals Pty Ltd. Ferrum H Injection MIMS
Wrappers Figure 4 Mediator 6 7 Connection speed and latency of response time from sources are, for practical purposes, nondeterministic in an Internet environment, and a meta-search engine can therefore experience large fluctuations in responses from the same source under different circumstances. Latency is subject to network traffic conditions, making it impossible to guarantee that all resources that are queried at a particular time will respond predictably and equally. To counter this, the mediator has a time-out feature. If a response is not received within the time-out specified by a profile, the mediator will cancel a subsearch and forward all the results currently available from other sources to the user interface. This effectively guarantees a defined response time irrespective of the state of the individual data sources and provides some control over the speed/accuracy trade-off. Capability Manager 13 In QC, a capability manager (CM) is responsible for mimicking a range of search capabilities and is located between the mediator and wrapper. The CM may modify a query and/or the result depending on the capabilities of the sources about to be queried. Capabilities of the CM within the QC system included the following: Date-CM: search within a date range Duplicate-CM: remove document duplicates Sort-CM: sort results by title, author, document rank, or date 14 QC uses a stacking mechanism to insert individual CMs into the processing of queries for wrappers and the processing of results from a source. A component called the search planner, containing simple rules, is responsible for stacking the CMs. This means that the sequence of CMs can be ordered to ensure the correct outcome of query or result translations. Theoretically, this corresponds to a composition of operations. A lexical variant CM, for example, has to replace the search terms in the query before the wrapper executes the search. The Date-CM, on the other hand, can only perform its job after the successful execution of the wrapper. Search Filters 10 11 10 sensitivity and specificity [MESH] OR sensitivity [WORD] OR diagnosis [SH] OR diagnostic use [SH] OR specificity [WORD] These terms have been shown to significantly enhance the quality of Medline results, but they are unlikely to be known to a typical clinical user. Table 1 4 Table 1 System Platform The system was constructed using Java, the Struts Web application framework, and a MySQL database and is deployed on a RedHat Linux platform. The user interface (JSP, servlet, and HTML pages) is deployed through an Apache Web server connected to a Tomcat servlet engine. The Apache-Tomcat platform incorporates load balancing and fail-over and is suitable for scalability and large-scale deployment. Technical Evaluation 4 15 16 BMJ Medical Journal of Australia (MJA) The Merck Manual Figure 5 In the following section we report on the technical performance of the architecture and then reflect on its suitability for supporting evidence retrieval in clinical practice. Results In the pre-trial questionnaire, 40% of the clinicians reported having a broadband (ADSL, cable, satellite) connection, while 43% used a 56k or 64k modem connection. The remaining 17% either did not know the type of connection used or had a slower connection. A total of 1662 searches were performed over the trial. Search Speed Under local network conditions (LAN, 100MBit), the user time (from starting the search on a client computer to displaying the results) was approximately 1.5 s. However, since most users accessed the system through the Internet, latency was significantly longer and slowed down the overall search speed. Figure 6 System Time Figure 5 Figure 7 System Time Versus Number of Individual Sources Involved Table 2 Speed and Reliability of Individual Data Sources Table 3 The Merck Manual MJA BMJ Figure 8 Discussion System Time Table 3 Search Times Figure 6 Figure 8 Future Work 17 18 19 20