Test Results

sults is time-consuming, creating a demand for expert systems to automate this process. We have started to set up the program “LabRespond”, which covers five vali-dation levels: administrative, technical, sample, patient, and clinical validation. We present the evaluation of a prototype of an automated patient validation system based on statistical methods, in contrast to the commer-cially available program “VALAB”, a rule-based auto-mated validation system. Methods: In the present study, 163 willfully altered, erroneous test results out of 5421 were submitted for validation to LabRespond, VALAB, and to a group of clinical chemists (n 5 9) who validated these test results manually. The test results rejected by three or more clinical chemists (n 5 281) served as a secondary refer-ence standard. Results: The error recovery rates of clinical chemists ranged from 23.9 % to 71.2%. The recovery rates of LabRespond and VALAB were 77.9 % and 71.8%, respec-tively (difference not significant). The false-positive rates were 82.7 % for LabRespond, 83.6 % for VALAB, and 27.8–86.7 % for clinical chemists. Using the consen-sus of three or more clinical chemists as the secondary reference standard, we found error recovery rates o