title: Explaining regional variations in health care utilization between Swiss cantons using panel econometric models.
abstract: BACKGROUND
  In spite of a detailed and nation-wide legislation frame, there exist large cantonal disparities in consumed quantities of health care services in Switzerland. In this study, the most important factors of influence causing these regional disparities are determined. The findings can also be productive for discussing the containment of health care consumption in other countries.
  
  
  METHODS
  Based on the literature, relevant factors that cause geographic disparities of quantities and costs in western health care systems are identified. Using a selected set of these factors, individual panel econometric models are calculated to explain the variation of the utilization in each of the six largest health care service groups (general practitioners, specialist doctors, hospital inpatient, hospital outpatient, medication, and nursing homes) in Swiss mandatory health insurance (MHI). The main data source is 'Datenpool santésuisse', a database of Swiss health insurers.
  
  
  RESULTS
  For all six health care service groups, significant factors influencing the utilization frequency over time and across cantons are found. A greater supply of service providers tends to have strong interrelations with per capita consumption of MHI services. On the demand side, older populations and higher population densities represent the clearest driving factors.
  
  
  CONCLUSIONS
  Strategies to contain consumption and costs in health care should include several elements. In the federalist Swiss system, the structure of regional health care supply seems to generate significant effects. However, the extent of driving factors on the demand side (e.g., social deprivation) or financing instruments (e.g., high deductibles) should also be considered.
authors.affiliation: Swiss Health Observatory and University of Neuchâtel, Espace de l'Europe 10, 2010 Neuchâtel, Switzerland. paul.camenzind@bfs.admin.ch
authors.forename: Paul A
authors.initials: PA
authors.lastname: Camenzind
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D002391:Catchment Area, Health / Q000191:economics; D003669:Deductibles and Coinsurance / Q000706:statistics & numerical data; D016527:Drug Costs / Q000706:statistics & numerical data / Q000639:trends; D058005:General Practitioners / Q000191:economics / Q000706:statistics & numerical data*; D006123:Group Practice / Q000706:statistics & numerical data / Q000639:trends; D054625:Healthcare Disparities / Q000706:statistics & numerical data* / Q000639:trends; D006742:Hospital Bed Capacity / Q000706:statistics & numerical data; D006760:Hospitalization / Q000706:statistics & numerical data / Q000639:trends; D006801:Humans; D007182:Income / Q000706:statistics & numerical data; D037141:Mandatory Programs; D008511:Medicine; D017059:Models, Econometric; D009313:National Health Programs / Q000191:economics* / Q000706:statistics & numerical data / Q000639:trends; D009735:Nursing Homes / Q000706:statistics & numerical data / Q000639:trends; D011156:Population Density; D012017:Referral and Consultation / Q000592:standards / Q000706:statistics & numerical data; D013557:Switzerland; D014478:Unemployment / Q000706:statistics & numerical data; D019037:Urban Health Services / Q000191:economics / Q000706:statistics & numerical data* / Q000639:trends