Comparison of algorithms that detect drug side effects using electronic healthcare databases

The electronic healthcare databases are starting to become more readily available and are thought to have excellent potential for generating adverse drug reaction signals. The Health Improvement Network (THIN) database is an electronic healthcare database containing medical information on over 11 million patients that has excellent potential for detecting ADRs. In this paper we apply four existing electronic healthcare database signal detecting algorithms (MUTARA, HUNT, Temporal Pattern Discovery and modified ROR) on the THIN database for a selection of drugs from six chosen drug families. This is the first comparison of ADR signalling algorithms that includes MUTARA and HUNT and enabled us to set a benchmark for the adverse drug reaction signalling ability of the THIN database. The drugs were selectively chosen to enable a comparison with previous work and for variety. It was found that no algorithm was generally superior and the algorithms’ natural thresholds act at variable stringencies. Furthermore, none of the algorithms perform well at detecting rare ADRs.     

A decision procedure for detecting atomicity violations for communicating processes with locks

The problem of interest is to verify data consistency of a concurrent Java program. In particular, we present a new decision procedure for verifying that a class of data races caused by inconsistent accesses on multiple fields of an object cannot occur (so-called atomic-set serializability). Atomic-set serializability generalizes the ordinary notion of a data race (i.e., inconsistent coordination of accesses on a single memory location) to a broader class of races that involve accesses on multiple memory locations. Previous work by some of the authors presented a technique to abstract a concurrent Java program into an EML program, a modeling language based on pushdown systems and a finite set of reentrant locks. Our previous work used only a semi-decision procedure, and hence provides a definite answer only some of the time. In this paper, we rectify this shortcoming by developing a decision procedure for verifying data consistency, i.e., atomic-set serializability, of an EML program. When coupled with the previous work, it provides a decision procedure for verifying data consistency of a concurrent Java program. We implemented the decision procedure, and applied it to detect both single-location and multi-location data races in models of concurrent Java programs. Compared with the prior method based on a semi-decision procedure, not only was the decision procedure 34 times faster overall, but the semi-decision procedure timed out on about 50% of the queries, whereas the decision procedure timed out on none of the queries.