A healthcare-associated surgical site infection surveillance and decision support system

Surgical site infection (SSI) is a long-term issue in the hospital and contributes to patient deaths and disability. Also healthcare-associated SSI (HASSI) increases healthcare costs and extend hospitalization stay, so prevention of HASSI is one of the most important points in infection control. However, the current manual surveillance method is error prone and time-consuming. To increase the efficiency of healthcare-associated SSI surveillance and evaluate different detection rule using different data sources (antibiotic prescription, microbiology laboratory, discharge diagnosis codes, surgical report, and symptoms & physical examination), the HASSI surveillance system was developed. According to the preliminary results, the rule-based SSI systems of antibiotic prescription and microbiology laboratory acquires 89% and 85% sensitivity, respectively. Electronic medical records from September 2013 through December 2013 of 7849 inpatients were detected by different defined rules of HASSI. The performance analysis of this surveillance system was calculated by comparing the manual reviewed HASSIs. Hence, The HASSI system decreases the number of patients need to evaluate by infection control personnel (ICP) and significantly improves the efficiency of HASSI detection.