title: Opinion versus practice regarding the use of rehabilitation services in home care: an investigation using machine learning algorithms.
abstract: BACKGROUND
  Resources for home care rehabilitation are limited, and many home care clients who could benefit do not receive rehabilitation therapy. The interRAI Contact Assessment (CA) is a new screening instrument comprised of a subset of interRAI Home Care (HC) items, designed to be used as a preliminary assessment to identify which potential home care clients should be referred for a full assessment, or for services such as rehabilitation. We investigated which client characteristics are most relevant in predicting rehabilitation use in the full interRAI HC assessment.
  
  
  METHODS
  We applied two algorithms from machine learning and data mining - the LASSO and the random forest - to frequency matched interRAI HC and service utilization data for home care clients in Ontario, Canada.
  
  
  RESULTS
  Analyses confirmed the importance of functional decline and mobility variables in targeting rehabilitation services, but suggested that other items in use as potential predictors may be less relevant. Six of the most highly ranked items related to ambulation. Diagnosis of cancer was highly associated with decreased rehabilitation use; however, cognitive status was not.
  
  
  CONCLUSIONS
  Inconsistencies between variables considered important for classifying clients who need rehabilitation and those identified in this study based on use may indicate a discrepancy in the client characteristics considered relevant in theory versus actual practice.
authors.affiliation: Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Mathematics Building No. 3, Waterloo, ON, N2L 3G1, Canada.
authors.forename: Lu
authors.initials: L
authors.lastname: Cheng
authors.affiliation: Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Mathematics Building No. 3, Waterloo, ON, N2L 3G1, Canada.
authors.forename: Mu
authors.initials: M
authors.lastname: Zhu
authors.affiliation: School of Public Health and Health Systems, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada.
authors.forename: Jeffrey W
authors.initials: JW
authors.lastname: Poss
authors.affiliation: School of Public Health and Health Systems, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada.
authors.forename: John P
authors.initials: JP
authors.lastname: Hirdes
authors.affiliation: School of Public Health and Health Systems, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada.
authors.forename: Christine
authors.initials: C
authors.lastname: Glenny
authors.affiliation: School of Public Health and Health Systems, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada. stolee@uwaterloo.ca.
authors.forename: Paul
authors.initials: P
authors.lastname: Stolee
mesh_terms: D000465:Algorithms; D057225:Data Mining; D003661:Decision Support Techniques; D005260:Female; D006699:Home Care Services; D006801:Humans; D000069550:Machine Learning; D008297:Male; D008491:Medical Informatics Applications; D008875:Middle Aged; D051346:Mobility Limitation; D012046:Rehabilitation