title: Predictive risk modelling in the Spanish population: a cross-sectional study.
abstract: BACKGROUND
  An increase in chronic conditions is currently the greatest threat to human health and to the sustainability of health systems. Risk adjustment systems may enable population stratification programmes to be developed and become instrumental in implementing new models of care.The objectives of this study are to evaluate the capability of ACG-PM, DCG-HCC and CRG-based models to predict healthcare costs and identify patients that will be high consumers and to analyse changes to predictive capacity when socio-economic variables are added.
  
  
  METHODS
  This cross-sectional study used data of all Basque Country citizens over 14 years of age (n = 1,964,337) collected in a period of 2 years. Data from the first 12 months (age, sex, area deprivation index, diagnoses, procedures, prescriptions and previous cost) were used to construct the explanatory variables. The ability of models to predict healthcare costs in the following 12 months was assessed using the coefficient of determination and to identify the patients with highest costs by means of receiver operating characteristic (ROC) curve analysis.
  
  
  RESULTS
  The coefficients of determination ranged from 0.18 to 0.21 for diagnosis-based models, 0.17-0.18 for prescription-based and 0.21-0.24 for the combination of both. The observed area under the ROC curve was 0.78-0.86 (identifying patients with a cost higher than P-95) and 0.83-0.90 (P-99). The values of the DCG-HCC models are slightly higher and those of the CRG models are lower, although prescription information could not be used in the latter. On adding previous cost data, differences between the three systems decrease appreciably. Inclusion of the deprivation index led to only marginal improvements in explanatory power.
  
  
  CONCLUSIONS
  The case-mix systems developed in the USA can be useful in a publicly financed healthcare system with universal coverage to identify people at risk of high health resource consumption and whose situation is potentially preventable through proactive interventions.
authors.affiliation: Osakidetza, Basque Health Service, Bilbao, Spain.
authors.forename: Juan F
authors.initials: JF
authors.lastname: Orueta
authors.forename: Roberto
authors.initials: R
authors.lastname: Nuño-Solinis
authors.forename: Maider
authors.initials: M
authors.lastname: Mateos
authors.forename: Itziar
authors.initials: I
authors.lastname: Vergara
authors.forename: Gonzalo
authors.initials: G
authors.lastname: Grandes
authors.forename: Santiago
authors.initials: S
authors.lastname: Esnaola
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D016001:Confidence Intervals; D017281:Cost of Illness; D003430:Cross-Sectional Studies; D003953:Diagnosis-Related Groups; D005260:Female; D017048:Health Care Costs; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D020379:Risk Adjustment / Q000379:methods*; D012923:Social Class; D013030:Spain; D055815:Young Adult