title: Creating peer groups for assessing and comparing nursing home performance.
abstract: BACKGROUND
  Publicly reported performance data for hospitals and nursing homes are becoming ubiquitous. For such comparisons to be fair, facilities must be compared with their peers.
  
  
  OBJECTIVE
  To adapt a previously published methodology for developing hospital peer groupings so that it is applicable to nursing homes and to explore the characteristics of "nearest-neighbor" peer groupings.
  
  
  METHODS
  Analysis of Department of Veterans Affairs administrative databases and nursing home facility characteristics.
  
  
  METHODS
  The nearest-neighbor methodology for developing peer groupings involves calculating the Euclidean distance between facilities based on facility characteristics. We describe our steps in selection of facility characteristics, describe the characteristics of nearest-neighbor peer groups, and compare them with peer groups derived through classical cluster analysis.
  
  
  RESULTS
  The facility characteristics most pertinent to nursing home groupings were found to be different from those that were most relevant for hospitals. Unlike classical cluster groups, nearest neighbor groups are not mutually exclusive, and the nearest-neighbor methodology resulted in nursing home peer groupings that were substantially less diffuse than nursing home peer groups created using traditional cluster analysis.
  
  
  CONCLUSIONS
  It is essential that healthcare policy makers and administrators have a means of fairly grouping facilities for the purposes of quality, cost, or efficiency comparisons. In this research, we show that a previously published methodology can be successfully applied to a nursing home setting. The same approach could be applied in other clinical settings such as primary care.
authors: Department of Epidemiology and Public Health, University of Miami, 1120 NW 14th St, Miami, FL 33136. E-mail: mbyrne2@med.miami.edu.
authors: Margaret M
authors: MM
authors: Byrne
authors: Christina
authors: C
authors: Daw
authors: Ken
authors: K
authors: Pietz
authors: Brian
authors: B
authors: Reis
authors: Laura A
authors: LA
authors: Petersen
mesh_terms: D016000:Cluster Analysis; D006801:Humans; D015233:Models, Statistical; D009735:Nursing Homes / Q000592:standards*; D010043:Outcome and Process Assessment, Health Care / Q000592:standards*; D018024:Peer Review, Health Care; D011366:Professional Review Organizations; D014481:United States; D014493:United States Department of Veterans Affairs