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Bounce-Back: Predicting Acute Readmission From Inpatient Rehabilitation for Patients With Stroke.

Pamela Roberts1, Harriet Aronow, Debra Ouellette

  • 1From the Department of Physical Medicine and Rehabilitation, Cedars-Sinai, Los Angeles, California (PR); Department of Biomedical Sciences, Cedars-Sinai, Los Angeles, California (PR, HA); Department of Nursing Research, Cedars-Sinai, Los Angeles, California (HA, MS); Casa Colina Hospital and Centers for Healthcare, Pomona, California (DO); and Health Department, State University of New York at Cortland, Cortland, New York (MD).

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Identifying stroke patients at risk for early hospital discharge or readmission is crucial. Factors like comorbidities, race, and functional status significantly impact these outcomes following inpatient rehabilitation.

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Area of Science:

  • Rehabilitation Medicine
  • Geriatric Medicine
  • Stroke Neurology

Background:

  • Inpatient rehabilitation is vital for stroke recovery.
  • Understanding readmission risks is key to improving patient outcomes and reducing healthcare costs.

Purpose of the Study:

  • To identify demographic, medical, and functional risk factors for acute hospital discharge before rehabilitation completion.
  • To identify risk factors for 7- and 30-day readmissions after inpatient rehabilitation for stroke patients.

Main Methods:

  • A large cohort study of 138,063 Medicare beneficiaries with new onset stroke.
  • Multivariate models analyzed data from 6 months pre-stroke to 30 days post-rehabilitation discharge.
  • Examined outcomes including acute hospital discharge and 7/30-day readmissions.

Main Results:

  • Comorbidities and complications increased acute discharge risk; longer stroke onset to rehabilitation admission also raised this risk.
  • Black patients, those with managed care Medicare, and complex comorbidities faced higher readmission rates.
  • Functional status was a significant factor across all analyzed outcomes.

Conclusions:

  • Demographic, medical, and functional characteristics are differentially associated with rehospitalization post-inpatient rehabilitation.
  • The model predicting discharge to an acute hospital demonstrated strong predictive power (c-statistic = 0.87).