摘要：Objective To describe how the state syndromic surveillance system (NC DETECT) was used to initiate near real time surveillance for endocarditis, sepsis and skin infection among drug users. Introduction Recreational drug use is a major problem in the United States and around the world. Specifically, drug abuse results in heavy use of emergency department (ED) services, and is a high financial burden to society and to the hospitals due to chronic ill health and multiple injection drug use complications. Intravenous drug users are at high risk of developing sepsis and endocarditis due to the use of a dirty or infected needle that is either shared with someone else or re-used. It can also occur when a drug user repeatedly injects into an inflamed and infected site or due to the poor overall health of an injection drug user. The average cost of hospitalization for aortic valve replacement in USA is about $165,000, and in order for the valve replacement to be successful, patients must abstain from using drugs. Methods We examined temporal trends of drug-related visits to hospital EDs, as well as drug-related related ED admissions complicated with endocarditis, bacteremia and sepsis. Results The trends in Endocarditis/Sepsis and drug-related related admissions appear to echo overdose related ED admissions increase. Patients ED return visits and hospitalizations for the same problem are also growing compare to the previous years. We will discuss the NC DETECT case definition used to monitor drug overdose/dependence and infection, case definition transition from ICD-9 to ICD-10 codes, and will share surveillance analysis results. Conclusions NC DETECT’s system flexibility has been important in rapidly establishing surveillance of infections among drug users. Near real time analysis on hospital, county and state levels can be performed using NC DETECT system reports to provide state officials, hospitals and LHDs with situational awareness. Limitations: Syndromic surveillance ED data contains less accurate information about the diagnosis codes, procedures, length of stay, and severity comparing to the hospital discharge data.
