Free
Poster Session
Issue Date: August 2016
Published Online: August 01, 2016
Updated: January 01, 2021
Developing Continuum of Care Assessment Across Postacute Care in Veterans
Author Affiliations
  • Medical University of South Carolina
  • Medical University of South Carolina
  • Medical University of South Carolina
  • Medical University of South Carolina
  • Medical University of South Carolina
  • Medical University of South Carolina
  • University of Florida
Article Information
Military Rehabilitation / Assessment/Measurement
Poster Session   |   August 01, 2016
Developing Continuum of Care Assessment Across Postacute Care in Veterans
American Journal of Occupational Therapy, August 2016, Vol. 70, 7011500014. https://doi.org/10.5014/ajot.2016.70S1-PO1043
American Journal of Occupational Therapy, August 2016, Vol. 70, 7011500014. https://doi.org/10.5014/ajot.2016.70S1-PO1043
Abstract

Date Presented 4/7/2016

This study used Rasch common person equating method to link FIM™ and Minimum Data Set with a retrospective national veterans dataset to create a continuum-of-care measure.

Primary Author and Speaker: Chih-Ying Li

Additional Authors and Speakers: Ickpyo Hong, Craig Velozo, Annie Simpson, Kit Simpson, Heather Bonilha, Sergio Romero

PURPOSE: This study aimed to link two commonly used instruments, the FIM™, typically used in inpatient rehabilitation facilities (IRF), and the Minimum Data Set (MDS) typically used in community living centers (CLCs), measuring activities of daily living (ADL) physical function across the continuum of postacute care veterans settings. The overall objective of this study was to investigate if two similar measures could be combined into a single item bank to measure individuals transitioning between IRFs and skilled nursing facilities. Our hypotheses were that the FIM–MDS item bank would (1) measure a single construct and (2) fit the Rasch model.
RATIONALE: We challenged a widely accepted belief that developing a new single instrument is the only solution to assess patients’ function across the continuum of care. In addition, linking existing instruments had lower demands of cost, time, and resources than developing a new single instrument, and exempt retraining burdens of new tool use for the practitioners.
DESIGN: This is a retrospective secondary data analysis study using a national veterans dataset.
PARTICIPANTS: Participants had a mean age of 67.0 yr (standard deviation [SD] = 11.0), with a range from 22 to 90 yr. The majority of the participants in this study were male (n = 354, 95.4%), White (n = 233, 62.8%), and married (n = 161, 43.4%). The average time since onset was about 6 mo. There were 164 (44.2%) veterans with stroke, 77 (20.8%) with lower-extremity amputation, 74 (19.9%) with knee replacement, and 56 (15.1%) with hip replacement.
METHOD: The data were retrieved from the existing databases maintained by the Veterans Austin Information Technology Center. Three hundred seventy-one out of the original 500 veterans with consistent responses on both FIM and MDS and who completed both instruments in the IRF and the CLC within 6 days through October 2008 to September 2010 were analyzed. The mean days between the administrations of the FIM and the MDS was 3.1 (SD = 2.1), with a range from 0 to 6 days.
ANALYSIS: An Item Response Theory–based common person equating method was used. Factor analyses, fit statistics, principal-component analysis (PCA) of Rasch residuals, and differential item functioning (DIF) were used to examine dimensionality, model fit, local independence, monotonicity, and DIF items across age groups (equal/under or beyond 65 yr old).
RESULTS: The FIM–MDS item bank demonstrated good internal consistency (Cronbach’s α = .98), met three rating scale criteria (i.e., monotonicity) and three of four model fit criteria (comparative fit index/Tucker–Lewis Index = .98, root mean square error of approximation = .14, standardized root mean square residual = .07). One item (MDS walk in corridor) was local dependence (residual correlation ≥ .2). PCA of Rasch residuals showed that the item bank explained 94.2% variance. The item bank covered the range of theta from −1.50 to 1.26 (item), –3.57 to 4.21 (person) with person strata of 6.3. One item (3.8%) had slight to moderate DIF (MDS bowel control) across age groups (less than vs. greater than 65 yr), with DIF contrast from Winsteps larger than .43 (p < .05). The overall results supported the idea of linking different instruments measuring the same construct.
DISCUSSION: The findings indicated the ADL physical function FIM–MDS item bank was unidimensional and fit the Rasch measurement model. These findings supported using the item bank as a source for developing the continuum of care assessment.
IMPACT STATEMENT: This study was the first step to examine the argument of using existing instruments to establish a continuum-of-care assessment by examining dimensionality and item-level psychometric properties of the item bank. Compared with developing a new single new tool, our finding supported that linking existing instruments can be a cost-efficient method of developing a continuum-of-care assessment.