Knowledge representation of critical laboratory results in using the SAGE framework and challenges to its implementation.

When a laboratory result is abnormal, the Computerized Critical Laboratory Results Alerting System should notify clinicians promptly. Use of this system can decrease the length of time spent in life-threatening situations, the average length of stay and the cost. 10 criteria oriented not to the individual but to a large number of patients were defined, these criteria were encoded using the SAGE framework. This type of modeling is utilized to validate a knowledge converter that converts the SAGE output to a knowledge engine.