Adaptive Measurement of Change: A Novel Method to Reduce Respondent Burden and Detect Significant Individual-Level...

Area of Science:

• Health Outcomes Research
• Psychometrics
• Clinical Measurement

Background:

• Assessing functional changes in hospitalized patients is crucial for effective care.
• Traditional follow-up assessments can increase patient burden and reduce efficiency.
• Item response theory (IRT)-based methods offer potential for more precise measurement.

Purpose of the Study:

• To introduce and evaluate the adaptive measurement of change (AMC) method.
• To identify psychometrically significant changes in reported patient function.
• To reduce respondent burden in follow-up assessments for hospitalized patients.

Main Methods:

• Utilized multivariate computerized adaptive testing (CAT) and IRT-based hypothesis tests.
• Employed the Functional Assessment in Acute Care Multidimensional Computerized Adaptive Test (FAMCAT).
• Assessed intra-individual change over 2 or more testing occasions in 495 hospitalized patients.

Main Results:

• Significant multivariate change was observed in 22.1% to 23.4% of patients across multiple assessment sessions.
• AMC reduced the number of FAMCAT items administered by an average of 12.6 (55%) and test duration by 2.9 minutes (53%) for patients with significant changes.
• The AMC method demonstrated utility in clinical care with estimates of item reduction.

Conclusions:

• The AMC method is an effective and parsimonious approach for identifying significant changes in CAT scores.
• AMC significantly reduces patient burden by decreasing the number of items and duration of follow-up assessments.
• AMC provides actionable data for patient care without assumptions about the nature of change.