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Selecting optimal screening items for delirium: An application of item response theory

  • Frances M. Yang(corresponding author)
    ,
  • Richard N. Jones
    ,
  • Sharon K. Inouye
    ,
  • Douglas Tommet
    ,
  • Paul K. Crane
    ,
  • James L. Rudolph
*Corresponding author for this work
  • Harvard University
    ,
  • University of Washington
    ,
  • Brigham and Women’s Hospital
Scholary Output:
Contribution to journal
Article
Peer-review

Open access

Abstract

Background: Delirium (acute confusion), is a common, morbid, and costly complication of acute illness in older adults. Yet, researchers and clinicians lack short, efficient, and sensitive case identification tools for delirium. Though the Confusion Assessment Method (CAM) is the most widely used algorithm for delirium, the existing assessments that operationalize the CAM algorithm may be too long or complicated for routine clinical use. Item response theory (IRT) models help facilitate the development of short screening tools for use in clinical applications or research studies. This study utilizes IRT to identify a reduced set of optimally performing screening indicators for the four CAM features of delirium. Methods. Older adults were screened for enrollment in a large scale delirium study conducted in Boston-area post-acute facilities (n = 4,598). Trained interviewers conducted a structured delirium assessment that culminated in rating the presence or absence of four features of delirium based on the CAM. A pool of 135 indicators from established cognitive testing and delirium assessment tools were assigned by an expert panel into two indicator sets per CAM feature representing (a) direct interview questions, including cognitive testing, and (b) interviewer observations. We used IRT models to identify the best items to screen for each feature of delirium. Results: We identified 10 dimensions and chose up to five indicators per dimension. Preference was given to items with peak psychometric information in the latent trait region relevant for screening for delirium. The final set of 48 indicators, derived from 39 items, maintains fidelity to clinical constructs of delirium and maximizes psychometric information relevant for screening. Conclusions: We identified optimal indicators from a large item pool to screen for delirium. The selected indicators maintain fidelity to clinical constructs of delirium while maximizing psychometric information important for screening. This reduced item set facilitates development of short screening tools suitable for use in clinical applications or research studies. This study represents the first step in the establishment of an item bank for delirium screening with potential questions for clinical researchers to select from and tailor according to their research objectives.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Article number

8

Journal (Volume, Issue Number)

BMC Medical Research Methodology (Volume 13, Issue 1)

Publication milestones

  • Published - 2013

Publication status

Published - 2013

ISSN

1471-2288

Publication IDs

  • Scopus: 84872434172
  • PubMed: 23339752

Publication metrics

Metrics

Scopus
citations
SciVal
citations
17
SciVal
FWCI
1.11
SciVal
Author count
8
SciVal
Paper percentile
77
Fractional count
1
Fractional count
0.13
Fractional count
7
Fractional count
0.88
Fractional count
1
Fractional count
1

PlumX, opens in new tab

Captures
46
Citation count
18

Funding Details

This work was funded in part by grants from the National Institute on Aging: R01AG030618 (ERM), K24 AG035075 (ERM), R03AG025262 (RNJ), R01AG17649 (ERM), and P01AG031720 (SKI). Dr. Inouye is supported by the Milton and Shirley F. Levy Family Chair.
FunderFunding numbers
NIA
R01AG17649, P01AG031720, R03AG025262, K24AG035075, R01AG030618