A Framework for Dynamic Evidence Based Medicine using Data Mining
CBMS '02 Proceedings of the 15th IEEE Symposium on Computer-Based Medical Systems (CBMS'02)
Adaptive information for consumers of healthcare
The adaptive web
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The emergence of genomically targeted cancer treatments has spurred the development of methods that correlate genomic information with treatments and outcomes. Because this information is usually pulled from published literature, such methods are limited to summarizing only the data generated through the slow and narrow publication pipeline. However, many thousands of patients are treated each year whose data does not make it into publications. Each of these is, in effect, a case study whose capture would add to our overall knowledge of cancer treatment, and could speed up the search for treatments and cures. Our work extends one such literature-based system, the Melanoma Targeted Therapy Advisor (TTA), by adding direct patient profiling. This extension of the TTA, or PTTA (Personalized or Patient TTA), both enriches the TTA knowledge base by collecting case reports directly from patients, and gives patients and/or physicians immediate feedback by ranking the best-performing treatments for genomic profiles of interest to them. The PTTA will permit patients to register their test and treatment results and then to obtain rankings for additional potentially useful tests and treatments. It will also provide a report with statistical and literature evidence that justifies the rankings. These functionalities can aid physicians in treating patients in the most effective manner.