Date Presented 04/01/2022

Functional impairments after stroke are heterogeneous. Standardized clinical assessments may not effectively capture the different functional subgroups of individuals after stroke. Using latent class analysis, five functional subgroups were identified within a sample of individuals hospitalized for ischemic stroke. The following outcomes varied across the functional subgroups: OT utilization, physical therapy utilization, and discharge disposition.

Primary Author and Speaker: Jessica Edelstein

Additional Authors and Speakers: Adam Kinney, Matthew Malcolm

Contributing Authors: James Graham, Tamera Keeney, Amanda L. Hoffman

PURPOSE: Stroke is one of the leading causes of disability in the United States. Occupational (OT) and physical therapy (PT) are vital services for hospitalized individuals after stroke who have functional impairments. In clinical practice, acute care occupational and physical therapists use standardized clinical assessments that provide summary scores of functional status. These summary scores are used to guide therapeutic interventions and discharge needs. However, summary scores do not comprehensively describe all persistent functional impairments. If the specific functional impairments of individuals after stroke are not accurately captured, individuals may be at risk for critical needs to go unaddressed. In this study, we sought to identify functional subgroups of individuals after stroke and determine the differences in OT/PT utilization and discharge disposition.

DESIGN: Retrospective, cross-sectional study of de-identified patient data. Data were collected from electronic medical records of 212,767 patients at five acute care hospitals within a single health care system. We used ICD-9/10 codes to identify patients hospitalized with ischemic stroke. Our final sample included 1,549 patients.

METHOD: Data from the basic mobility and daily activity domains (12 items) of the Activity Measure for Post-Acute Care (AMPAC) instrument were utilized to generate functional subgroups. For each AM-PAC item, patients were classified as independent or assistance needed. Latent class analysis was used to identify functional subgroups (i.e., latent classes). We examined whether the following patient factors predicted class membership: sex, age, significant other status, minority status, insurance type, and comorbidity burden. Lastly, the probability of OT utilization, PT utilization, and discharge disposition (home without services, home with services, and institution) was compared across functional subgroups.

RESULTS: Five subgroups were identified based on levels of assistance needed with items in the basic mobility and daily activity domains. The five subgroups were: (1) Impaired (42%), (2) Impaired Dynamic Balance (19%), (3) Impaired Self-Care (9%), (4) Impaired Mobility (11%), and (5) Independent (19%). When compared to the Independent subgroup, individuals who were older (p ≤ .001), lacked a significant other (p ≤ .001), were a racial/ethnic minority (p ≤ .05), had Medicare (p ≤ .05) or Medicaid (p ≤ .01; versus Commercial), and a greater comorbidity burden (p ≤ .001) were more likely to be a member of the Impaired subgroup. OT utilization (χ2 [4] = 122.97, p < .001), PT utilization (χ2 [4] = 113.21, p < .001), and discharge disposition (home without services: χ2 [4] = 246.61, p < .001; home health: χ2 [4] = 35.49, p < .001; and institution: χ2 [4] = 237.18, p < .001) varied significantly across all functional subgroups.

CONCLUSION: We identified 5 functional subgroups within individuals who were hospitalized with ischemic stroke, highlighting the heterogeneous nature of stroke recovery. Predictors of membership, acute care therapy utilization, and discharge disposition varied among the functional subgroups. Our findings demonstrate that a nuanced understanding of functional status may be useful to inform delivery of acute OT and PT services and discharge planning.

IMPACT STATEMENT: OT and PT are included service providers in the Bundled Payments for Care Improvement Advanced Model, which is improving the coordination, efficiency, and quality of care for patients in acute and post-acute settings. Understanding how unique functional subgroups impact care provision and disposition may help to improve the efficiency and access of care provided by OT and PT.


Collins, L. M., & Lanza, S. T. (2010). Latent Class and Latent Transition Analysis: With Applications in the Social Behavioral, and Health Sciences. Wiley.

Jette, D. U., Stilphen, M., Ranganathan, V. K., Passek, S., Frost, F. S., & Jette, A. M. (2015). Interrater reliability of AM-PAC “6-Clicks” basic mobility and daily activity short forms. Physical Therapy, 95(5), 758-766.

Morgan, G. B., Hodge, K. J., & Baggett, A. R. (2016). Latent profile analysis with nonnormal mixtures: A Monte Carlo examination of model selection using fit indices. Computational Statistics & Data Analysis, 93, 146-161.

Ovbiagele, B., Goldstein, L. B., Higashida, R. T., Howard, V. J., Johnston, S. C., Khavjou, O. A., Lackland, D. T., Lichtman, J. H., Mohl, S., Sacco, R. L., Saver, J. L., Trogdon, J. G., American Heart Association Advocacy Coordinating, C., & Stroke, C. (2013). Forecasting the future of stroke in the United States: a policy statement from the American Heart Association and American Stroke Association. Stroke, 44(8), 2361-2375.