Computerised adaptive testing accurately predicts CLEFT-Q scores by selecting fewer, more patient-focused questions

Background: The International Consortium for Health Outcome Measurement (ICHOM) has recently agreed upon a core outcome set for the comprehensive appraisal of cleft care, which puts a greater emphasis on patient-reported outcome measures (PROMs) and, in particular, the CLEFT-Q. The CLEFT-Q comprises 12 scales with a total of 110 items, aimed to be answered by children as young as 8 years old. Objective: In this study, we aimed to use computerised adaptive testing (CAT) to reduce the number of items needed to predict results for each CLEFT-Q scale. Method: We used an open-source CAT simulation package to run item responses over each of the full-length scales and its CAT counterpart at varying degrees of precision, estimated by standard error (SE). The mean number of items needed to achieve a given SE was recorded for each scale's CAT, and the correlations between results from the full-length scales and those predicted by the CAT versions were calculated. Results: Using CATs for each of the 12 CLEFT-Q scales, we reduced the number of questions that participants needed to answer, that is, from 110 to a mean of 43.1 (range 34–60, SE < 0.55) while maintaining a 97% correlation between scores obtained with CAT and full-length scales. Conclusions: CAT is likely to play a fundamental role in the uptake of PROMs into clinical practice given the high degree of accuracy achievable with substantially fewer items.