BACKGROUND: Clostridium difficile infection (CDI) has become the most common cause of health-care associated infections in the United States. The CDC estimates that C. difficile causes nearly 500,000 infections each year in the United States, attributing to about 29,000 deaths. In 2015, the South Carolina Department of Health and Environmental Control (DHEC) made CDI a laboratory reportable condition. The objective of this evaluation was to assess the CDI surveillance system attributes.
METHODS: Data analyzed in this evaluation was CDI lab reports submitted into the Carolinas Healthcare Electronic Surveillance System (CHESS) from January 1st 2015 through June 30th2015. The methods of this evaluation were based on the Updated Guidelines for Evaluating Public Health Surveillance Systems published by the CDC. The CHESS attributes assessed were simplicity, flexibility, stability, acceptability, data quality, timeliness, and representativeness.
RESULTS: There was a total of 2887 CDI lab reports submitted to CHESS from January-June. CDI reporting is complex because facilities can submit a report via: (i) Electronic Laboratory Reporting (ELR), (ii) manual data entry by external user, and (iii) disease report cards mailed and entered by Division of Acute Disease Epidemiology staff. CHESS easily adapts to changing information and can accommodate the addition of new conditions with minimum time and resources. The stability of CHESS is marked by its infrequent unplanned outages. The percent completeness of the six demographic variables ranged from 79.7-99.9% compared to a range of 60-100% completeness for the six lab-related variables. For all lab reports, 74.8% were reported to public health within the requested time frame of three days following a positive C.difficile lab test result. Nearly 60% of lab reports submitted to DHEC by disease report cards were received 3 or more days after the lab test result date. The incidence rate of C. difficilewas higher in females compared to males and was highest in those aged 65 and older. These data patterns are representative of CDI rates found by the Emerging Infections Program.
CONCLUSIONS: Overall, CHESS was found to be a very flexible and stable system with high acceptability. The system’s complexity needs improvement as this complexity also influences the attributes of data quality and timeliness. Improving the simplicity of the system would have a positive effect on the other attributes and result in an overall improvement of surveillance system attributes.