Objectives: To develop and explore the feasibility of a functional staging system (defined as the process of assigning subjects, according to predetermined standards, into a set of hierarchic levels with regard to their functioning performance in mobility, daily activities, and cognitive skills) based on item response theory (IRT) methods using short forms of the Activity Measure for Post-Acute Care (AM-PAC) and to compare the criterion validity and sensitivity of the IRT-based staging system to a non-IRT-based staging system developed for the FIM instrument.
Design: Prospective, longitudinal cohort study of patients interviewed at hospital discharge and 1, 6, and 12 months after inpatient rehabilitation.
Setting: Follow-up interviews conducted in patients' homes.
Participants: Convenience sample of 516 patients (47% men; sample mean age, 68.3y) at baseline (retention at the final follow-up, 65%) with neurologic, lower-extremity orthopedic, or complex medical conditions.
Interventions: Not applicable.
Main outcome measures: AM-PAC basic mobility, daily activity, and applied cognitive activity stages; FIM executive control, mobility, activities of daily living, and sphincter stages. Stages refer to the hierarchic levels assigned to patients' functioning performances.
Results: We were able to define IRT-based staging definitions and create meaningful cut scores based on the 3 AM-PAC short forms. The IRT stages correlated as well or better to the criterion items than the FIM stages. Both the IRT-based stages and the FIM stages were sensitive to changes throughout the 6-month follow-up period. The FIM stages were more sensitive in detecting changes between baseline and 1-month follow-up visits. The AM-PAC stages were more discriminant in the follow-up visits.
Conclusions: An IRT-based staging approach appeared feasible and effective in classifying patients throughout long-term follow-up. Although these stages were developed from short forms, this staging methodology could also be applied to improve the meaning of scores generated from IRT-based computerized adaptive testing in future work.