Outcome prediction in home- and community-based brain injury rehabilitation using the Mayo-Portland Adaptability Inventory

Neuropsychol Rehabil. 2015;25(5):663-76. doi: 10.1080/09602011.2015.1013139. Epub 2015 Feb 24.

Abstract

The objective of the study was to develop statistical formulas to predict levels of community participation on discharge from post-hospital brain injury rehabilitation using retrospective data analysis. Data were collected from seven geographically distinct programmes in a home- and community-based brain injury rehabilitation provider network. Participants were 642 individuals with post-traumatic brain injury. Interventions consisted of home- and community-based brain injury rehabilitation. The main outcome measure was the Mayo-Portland Adaptability Inventory (MPAI-4) Participation Index. Linear discriminant models using admission MPAI-4 Participation Index score and log chronicity correctly predicted excellent (no to minimal participation limitations), very good (very mild participation limitations), good (mild participation limitations), and limited (significant participation limitations) outcome levels at discharge. Predicting broad outcome categories for post-hospital rehabilitation programmes based on admission assessment data appears feasible and valid. Equations to provide patients and families with probability statements on admission about expected levels of outcome are provided. It is unknown to what degree these prediction equations can be reliably applied and valid in other settings.

Keywords: Brain injury; Outcome; Prediction; Rehabilitation.

MeSH terms

  • Adult
  • Brain Injuries / rehabilitation*
  • Community Health Services / statistics & numerical data*
  • Female
  • Home Care Services / statistics & numerical data*
  • Humans
  • Male
  • Middle Aged
  • Severity of Illness Index
  • Statistics as Topic
  • Treatment Outcome