PubMed · 15559840
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AHIMA computer-assisted coding e-HIM work group. Delving into computer-assisted coding.. https://pubmed.ncbi.nlm.nih.gov/15559840/
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BACKGROUND: The long list of ophthalmologic findings and symptoms at a baseline examination of a patient with uveitis can have an impact on further laboratory workup and differential diagnosis. METHODS: Based on publications and previous work, a decision tree was transformed into the expert system shell D3. A web-based Java Servlet was then programmed and published on our website (http://www.uveitiscenter.de at DiagnoseFinder). Ophthalmologic findings and symptoms of the patient can be checked with this online questionnaire, and recommendations for further laboratory tests and further care of the patient received. RESULTS: Retrospective analysis of 62 patients with characteristic features of secondary uveitis showed a good correlation between the actual diagnosis of the patient and the diagnosis found by the program. In 74% of cases, the correct diagnosis was found among other options. In 37%, only the correct diagnosis was found, while in 37% the correct diagnosis was found among other probable diagnoses. Not all forms of secondary uveitis were found easily by the software. CONCLUSION: This program is meant to be an easily accessible and simply employable help for the care of patients with a secondary form of uveitis. It is intended to be a support not only for residents in particular, but also for ophthalmologists in private practice who rarely treat patients with uveitis.
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BACKGROUND: It is increasingly difficult for clinicians to keep up-to-date with the rapidly growing biomedical literature. Online evidence retrieval methods are now seen as a core tool to support evidence-based health practice. However, standard search engine technology is not designed to manage the many different types of evidence sources that are available or to handle the very different information needs of various clinical groups, who often work in widely different settings. OBJECTIVES: The objectives of this paper are (1) to describe the design considerations and system architecture of a wrapper-mediator approach to federate search system design, including the use of knowledge-based, meta-search filters, and (2) to analyze the implications of system design choices on performance measurements. METHODS: A trial was performed to evaluate the technical performance of a federated evidence retrieval system, which provided access to eight distinct online resources, including e-journals, PubMed, and electronic guidelines. The Quick Clinical system architecture utilized a universal query language to reformulate queries internally and utilized meta-search filters to optimize search strategies across resources. We recruited 227 family physicians from across Australia who used the system to retrieve evidence in a routine clinical setting over a 4-week period. The total search time for a query was recorded, along with the duration of individual queries sent to different online resources. RESULTS: Clinicians performed 1662 searches over the trial. The average search duration was 4.9 +/- 3.2 s (N = 1662 searches). Mean search duration to the individual sources was between 0.05 s and 4.55 s. Average system time (ie, system overhead) was 0.12 s. CONCLUSIONS: The relatively small system overhead compared to the average time it takes to perform a search for an individual source shows that the system achieves a good trade-off between performance and reliability. Furthermore, despite the additional effort required to incorporate the capabilities of each individual source (to improve the quality of search results), system maintenance requires only a small additional overhead.