title: Validation of an improved area-based method of calculating general practice-level deprivation.
abstract: OBJECTIVE
  To compare the methods of calculating practice deprivation scores in the absence of patient-level data.
  
  
  METHODS
  Three methods of deriving general practice deprivation scores without patient-level data were compared against "gold standard" patient-level scores in 226 English practices. The three methods were lower super output area (LSOA), middle super output area (MSOA), and a geographical information systems (GIS) method. Working, if necessary, on the log scale, agreement between scores was assessed using Bland and Altman's method, Kappa statistics, and Pitman's test.
  
  
  RESULTS
  Based on the antilog 95% limits of agreement from Bland-Altman plots, GIS methods showed least variation compared with gold standard (0.66-1.47), followed by MSOA (0.61-1.70) and LSOA (0.38-2.29) methods. The differences in variances between both GIS and MSOA, and LSOA and MSOA comparisons, were greater than would be expected by chance (Pitman's P<0.001). High levels of agreement (kappa: 0.93, 0.86, and 0.80) were observed between GIS, MSOA, and LSOA methods compared with the "gold standard."
  
  
  CONCLUSIONS
  In situations where patient postcodes are unavailable, the GIS method is superior to area-based methods. However, where the GIS method cannot readily be applied, the MSOA method should be used in preference to the LSOA method.
authors.affiliation: The Academic Unit of Primary Health Care, Community Based Medicine, University of Bristol, Bristol, Avon, UK. tom.griffin@bristol.ac.uk
authors.forename: Thomas
authors.initials: T
authors.lastname: Griffin
authors.forename: Tim J
authors.initials: TJ
authors.lastname: Peters
authors.forename: Debbie
authors.initials: D
authors.lastname: Sharp
authors.forename: Chris
authors.initials: C
authors.lastname: Salisbury
authors.forename: Sarah
authors.initials: S
authors.lastname: Purdy
mesh_terms: D005194:Family Practice / Q000191:economics / Q000706:statistics & numerical data*; D040362:Geographic Information Systems; D006297:Health Services Accessibility / Q000191:economics / Q000706:statistics & numerical data*; D054625:Healthcare Disparities / Q000191:economics / Q000706:statistics & numerical data*; D006801:Humans; D011204:Poverty Areas; D006113:United Kingdom