Advancing the efficiency and efficacy of patient reported outcomes with multivariate computer adaptive testing | Zendy

Scott B. Morris | Zendy; Mike Bass | Zendy; Mirinae Lee | Zendy; Richard E. Neapolitan | Zendy

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Advancing the efficiency and efficacy of patient reported outcomes with multivariate computer adaptive testing

Author(s) -

Scott B. Morris,

Mike Bass,

Mirinae Lee,

Richard E. Neapolitan

Publication year - 2017

Publication title -

journal of the american medical informatics association

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.614

H-Index - 150

eISSN - 1527-974X

pISSN - 1067-5027

DOI - 10.1093/jamia/ocx003

Subject(s) - computerized adaptive testing , item response theory , trait , anger , distress , multivariate statistics , item bank , clinical psychology , multivariate analysis , psychology , psychometrics , computer science , machine learning , programming language

The Patient Reported Outcomes Measurement Information System (PROMIS) initiative developed an array of patient reported outcome (PRO) measures. To reduce the number of questions administered, PROMIS utilizes unidimensional item response theory and unidimensional computer adaptive testing (UCAT), which means a separate set of questions is administered for each measured trait. Multidimensional item response theory (MIRT) and multidimensional computer adaptive testing (MCAT) simultaneously assess correlated traits. The objective was to investigate the extent to which MCAT reduces patient burden relative to UCAT in the case of PROs.

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