Development and evaluation of a similarity measure for medical event sequences

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