Hospitals that adopt more advanced computerized monitoring systems to identify healthcare-associated infections (HAIs) are more likely to have implemented best practices to prevent such infections, according to a study presented at an annual meeting of the Association for Professionals in Infection Control and Epidemiology (APIC).
Only one-third of hospitals use computers to identify infections in a timely and accurate way, according to a survey of quality directors at 241 general acute care hospitals in California.
Those hospitals that use automated surveillance systems to identify HAIs were more likely than those who still rely on manual methods to have fully implemented research-based best practices to reduce MRSA infections (85 percent vs. 66 percent), ventilator-associated pneumonia (96 percent vs. 88 percent), and surgical care infection practices (91 percent vs. 82 percent). The survey was conducted between Oct. 2008 and Jan. 2009.
Automated surveillance technologies or data mining systems are computerized systems that collect infection data, helping infection preventionists identify and investigate potential clusters of HAIs in real time. Not only does electronic surveillance streamline the review and collection of infection data, it gives you a larger amount of information than manual methods, giving infection prevention staff more time to protect patients.
"Manual identification of infections is costly, time-consuming and diverts staff time from prevention activities," said Helen Halpin, lead author of the study and professor of health policy at the University of California, Berkeley.
To learn more:
- read a related APIC position paper
- read the APIC press release
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