Time adjusted sensitivity analysis: A new statistical test for the optimization of delta check rules

Background: The comparison of current and past test results by delta check rules is performed to identify possible errors, but the effect of time on the efficiency of error detection is frequently not considered in the design of these rules. A new approach is described for optimizing delta check rules, in terms of the time interval between tests, as well as their sensitivity and specificity. Methods: Analysis was performed on test pair data for 20 general chemistry analytes. Delta check rules were established to yield a specificity of 99%, and the optimum delta check rule was identified by using a Time-Adjusted-Sensitivity Score (TAS), which is an index of the efficiency of error detection and is the product of sensitivity times the relative cumulative frequency for repeat testing. Results: Based on TAS scores, the time-dependent decay in the correlation of test pairs and the test ordering pattern were found to have a large effect on the efficiency of error detection. In general, the optimum time interval for delta check analysis for most tests was found to be between 2 and 5 days. The maximum TAS scores for most enzyme tests were relatively high (10-40%), whereas TAS scores for most electrolytes were relatively low (4-13%). Several analytes, namely glucose, and magnesium, had such low TAS scores (<2%) that the use of delta check rules for these tests has limited value. Conclusion: TAS analysis can be used for systematically assessing the performance of delta check analysis and for improving error detection by the optimization of delta check rules and their time limits.