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. (C) 2019 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd.