Joel Fredrickson, Michael Mannino, Omar Alqahtani, Farnoush Banaei-Kashani
Decision Support Systems,Vol. 116, Pages: 35-47.
We extend a similarity measure for medical event sequences (MESs) and evaluate its classification performance for retrospective mortality prediction of trauma patient outcomes. Retrospective mortality prediction is a benchmarking task used by trauma care governance bodies to assist with policy decisions. We extend the similarity measure, the Optimal Temporal Common Subsequence for MESs (OTCS-MES), by generalizing the event-matching component with a plug-in weighting element. The extended OTCS-MES uses an event prevalence weight developed in our previous study and an event severity weight developed for this study. In the empirical evaluation of classification performance, we provide a more complete evaluation than previous studies. We compare the predictive performance of the Trauma Mortality Prediction Model (TMPM), an accepted regression approach for mortality prediction in trauma data

Lawrence.Cunningham@ucdenver. edu, Francisco.Conejo@ucdenver. edu
Journal of International Marketing Strategy,Vol. 5, Issue 1,

Michael Mannino, Joel Fredrickson, Farnoush Banaei-Kashani, Iris Linck, Raghda Alqurashi Raghda
ACM Transactions on Management Information Systems (TMIS),Vol. 8, Issue 2-3, Pages: 8.
We develop a similarity measure for medical event sequences (MESs) and empirically evaluate it using US Medicare claims data. Existing similarity measures do not use unique characteristics of MESs and have never been evaluated on real MESs. Our similarity measure, the Optimal Temporal Common Subsequence for Medical Event Sequences (OTCS-MES), provides a matching component that integrates event prevalence, event duplication, and hierarchical coding, important elements of MESs. The OTCS-MES also uses normalization to mitigate the impact of heavy positive skew of matching events and compact distribution of event prevalence. We empirically evaluate the OTCS-MES measure against two other measures specifically designed for MESs, the original OTCS and Artemis, a measure incorporating event alignment. Our evaluation uses two substantial data sets of Medicare claims data containing