%0 Journal Article
%@ 1438-8871
%I JMIR Publications
%V 22
%N 10
%P e20950
%T Maximizing the Potential of Patient-Reported Assessments by Using the Open-Source Concerto Platform With Computerized Adaptive Testing and Machine Learning
%A Harrison,Conrad
%A Loe,Bao Sheng
%A Lis,Przemysław
%A Sidey-Gibbons,Chris
%+ Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, The Botnar Research Centre, Windmill Road, Oxford, OX3 7LD, United Kingdom, 44 1865227374, conrad.harrison@medsci.ox.ac.uk
%K computerized adaptive testing
%K computerized adaptive test
%K CAT
%K machine learning
%K patient reported outcome measures
%K outcome assessment
%K Concerto
%D 2020
%7 29.10.2020
%9 Tutorial
%J J Med Internet Res
%G English
%X Patient-reported assessments are transforming many facets of health care, but there is scope to modernize their delivery. Contemporary assessment techniques like computerized adaptive testing (CAT) and machine learning can be applied to patient-reported assessments to reduce burden on both patients and health care professionals; improve test accuracy; and provide individualized, actionable feedback. The Concerto platform is a highly adaptable, secure, and easy-to-use console that can harness the power of CAT and machine learning for developing and administering advanced patient-reported assessments. This paper introduces readers to contemporary assessment techniques and the Concerto platform. It reviews advances in the field of patient-reported assessment that have been driven by the Concerto platform and explains how to create an advanced, adaptive assessment, for free, with minimal prior experience with CAT or programming.
%M 33118937
%R 10.2196/20950
%U http://www.jmir.org/2020/10/e20950/
%U https://doi.org/10.2196/20950
%U http://www.ncbi.nlm.nih.gov/pubmed/33118937