title: [Analysis of selection inventives for health insurances after introduction of the morbidity-oriented risk compensation scheme: an empirical analysis].
abstract: BACKGROUND
  The risk compensation scheme (RCS) in the Statutory Health Insurance (SHI) was implemented in 1994 to discourage risk selection between sickness funds. However, several expertise papers have concluded since then that the sociodemographic risk adjusters in place could not adequately curb risk selection. To minimise incentives for risk selection in the Statutory Health Insurance (SHI) further, the RCS was refined in 2009 by adding 80 diseases as additional risk adjusters. In spite of the better compensation of differences in morbidity, however, incentives for risk selection may still persist. In this study, we investigated the association of indicators such as region (number of inhabitants in the city), income, level of education and family status (children in the household) with health care costs to determine if risk selection is still attractive for sickness funds under the refined RCS.
  
  
  METHODS
  The analysis is based on a 2002 cross-section survey comprising 75,122 individuals. Health expenditures were estimated using self-documented utilisation data and were standardised for age, sex and diagnoses covered by the risk adjustment scheme. We included costs for inpatient care, outpatient care, pharmaceuticals, rehabilitation, and medical devices. To assess the effects of the above-mentioned individual characteristics on health-care expenditure, regression analyses and analyses of variances were performed.
  
  
  RESULTS
  Full documentation was available for 52,484 individuals (69.86%). From these the variables "family status (children in the household)", "higher educational level", and "higher income" were associated with lower costs for individuals without chronic conditions. For individuals with chronic conditions, results were mixed. "Family status", "education" and "income" showed no clear association with lower or higher costs and were not statistically significant. The variable "region" was neither significantly associated with chronically ill nor for healthy individuals.
  
  
  CONCLUSIONS
  With respect to age, sex, and morbidity, individuals with high income and education and without chronic diseases apparently cause lower costs. Thus, health status, income and education remain as possible selection criteria for sickness funds in Germany. However, the refined RCS compensates for the largest proportion of cost differences between insured with and without chronic disease. Possible causes of the small but remaining differences and whether improving preventive programmes or providing awareness campaigns may be appropriate strategies to tackle this issue should be investigated in future research.
authors.affiliation: Institut für Gesundheitsökonomie und Klinische Epidemiologie der Universität zu Köln. Markus.Luengen@uk-koeln.de
authors.forename: M
authors.initials: M
authors.lastname: Lüngen
authors.forename: A
authors.initials: A
authors.lastname: Drabik
authors.forename: G
authors.initials: G
authors.lastname: Büscher
authors.forename: A
authors.initials: A
authors.lastname: Passon
authors.forename: M
authors.initials: M
authors.lastname: Siegel
authors.forename: S
authors.initials: S
authors.lastname: Stock
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002908:Chronic Disease / Q000191:economics; D003695:Delivery of Health Care / Q000191:economics; D004522:Educational Status; D005260:Female; D005858:Germany; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006305:Health Status Indicators; D006801:Humans; D008297:Male; D008875:Middle Aged; D017059:Models, Econometric; D009017:Morbidity; D009313:National Health Programs / Q000191:economics*; D016017:Odds Ratio; D020379:Risk Adjustment / Q000191:economics*; D012737:Sex Factors; D012959:Socioeconomic Factors; D013223:Statistics as Topic; D055815:Young Adult