Healthcare-associated infections (HAIs) are a major patient safety issue. These adverse events add to the burden of resource use, promote resistance to antibiotics, and contribute to patient deaths and disability. A rule-based HAI classification and surveillance system was developed for automatic integration, analysis, and interpretation of HAIs and related pathogens. Rule-based classification system was design and implement to facilitate healthcare-associated bloodstream infection (HABSI) surveillance. Electronic medical records from a 2200-bed teaching hospital in Taiwan were classified according to predefined criteria of HABSI. The detailed information in each HABSI was presented systematically to support infection control personnel decision. The accuracy of HABSI classification was 0.94, and the square of the sample correlation coefficient was 0.99.
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