Improving Efficiency of Patient-Reported Outcome Collection: Application of Computerized Adaptive Testing to DASH and...

Patient-reported outcome measures assess health status and treatment outcomes in orthopedic care, but they may burden patients with lengthy questionnaires. Predictive models using machine learning, known as computerized adaptive testing (CAT), offer a potential solution. This study evaluates the ability of CAT to improve efficiency of the 30-item Disabilities of the Arm, Shoulder, and Hand (DASH) and 11-item QuickDASH questionnaires.

A total of 2,860 DASH and 27,355 QuickDASH respondents were included in the analysis. The CAT system was retrospectively applied to each set of patient responses stored on the instrument to calculate a CAT-specific score for all DASH and QuickDASH entries. The accuracy of the CAT scores, viewed in the context of the minimal clinically important difference for both patient-reported outcome measures (DASH, 12; QuickDASH, 9), was determined through descriptive statistics, Pearson correlation coefficient, intraclass correlation coefficient, and distribution of scores and score differences.

The CAT model required an average of 15.3 questions to be answered for the DASH and 5.8 questions for the QuickDASH, representing a 49% and 47% decrease in question burden, respectively. Mean CAT score was the same for DASH and 0.1 points lower for QuickDASH with similar SDs (DASH, 12.9 ± 19.8 vs 12.9 ± 19.9; QuickDASH, 32.7 ± 24.7 vs 32.6 ± 24.6). Pearson coefficients (DASH, 0.99; QuickDASH, 0.98) and intraclass correlation coefficients (DASH, 1.0; QuickDASH, 0.98) indicated strong agreement between scores. The difference between the CAT and full score was less than the minimal clinically important difference in 99% of cases for DASH and approximately 95% of cases for QuickDASH.

The application of CAT to DASH and QuickDASH surveys demonstrated an ability to lessen the response burden with negligible effect on score integrity.

In the case of DASH and QuickDASH, CAT is an appropriate alternative to full questionnaire implementation for patient outcome score collection.