A framework for infection control surveillance using association rules

Lili Ma, Fu-Chiang Tsui, William R Hogan, Michael M Wagner, Haobo Ma
2003 AMIA Annual Symposium Proceedings  
Surveillance of antibiotic resistance and nosocomial infections is one of the most important functions of a hospital infection control program. We employed the association rule method for automatically identifying new, unexpected, and potentially interesting patterns in hospital infection control. We hypothesized that mining for low-support, low-confidence rules would detect unexpected outbreaks caused by a small number of cases. To build a framework, we preprocessed the data and added new
more » ... ates to eliminate uninteresting patterns. We applied our method to the culture data collected over 3 months from 10 hospitals in the UPMC Health System. We found that the new process and system are efficient and effective in identifying new, unexpected, and potentially interesting patterns in surveillance data. The clinical relevance and utility of this process await the results of prospective studies.
pmid:14728205 pmcid:PMC1480000 fatcat:ov34y7uebrdsvpsuhpujen4zzi