Treatment effectiveness plays a fundamental role in patient therapies. In most observational studies, researchers often design an analysis pipeline for a specific treatment based on the study cohort. To evaluate other treatments in the data set, much repeated and multifarious work including cohort construction, statistical analysis need to be done. In addition, as treatments are often with an intrinsic hierarchical relationship, many rational comparable treatment pairs can be derived as new treatment variables besides the original single treatment one from the original cohort data set. In this paper, we propose an automatic treatment effectiveness analysis approach to solve this problem. With our approach, clinicians can assess the effect of treatments not only more conveniently but also more thoroughly and comprehensively. We applied this method to a real world case of estimating the drug effectiveness on Chinese Acute Myocardial Infarction (CAMI) data set and some meaningful results are obtained for potential improvement of patient treatments.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 firstname.lastname@example.org
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 email@example.com