Methods: This study is an accuracy assessment of 69 consecutive patients seen in an urban asthma subspecialty clinic between August 1 and November 30, 2004. Patients' asthma was classified as “severe” or “mild” both by the decision support system and expert asthma clinicians who were blinded to the assessment of the decision support system. Accuracy was quantified using percent accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and positive and negative likelihood ratios using the expert asthma clinicians as the reference standard.
Results: The decision support system had a 91% accuracy of recognizing severe asthma defined by expert asthma clinicians. The sensitivity of the decision support system for severe asthma was 96%, the specificity was 73%, the positive predictive value was 93%, the negative predictive value was 85%, the positive likelihood ratio was 3.6 (95% CI: 1.6, 8.4), and the negative likelihood ratio was 0.05 (95% CI: 0.012, 0.21).
Conclusions: The asthma decision support system was able to discern “mild” from “severe” asthma in a similar fashion to expert asthma clinicians. The effect of the decision support system on patient outcomes should be assessed.