title: Combining difference and equivalence test results in spatial maps.
abstract: BACKGROUND
  Regionally partitioned health indicator values are commonly presented in choropleth maps. Policymakers and health authorities use them among others for health reporting, demand planning and quality assessment. Quite often there are concerns whether the health situation in certain areas can be considered different or equivalent to a reference value.
  
  
  RESULTS
  Highlighting statistically significant areas enables the statement that these areas differ from the reference value. However, this approach does not allow conclusions which areas are sufficiently close to the reference value, although these are crucial for health policy making as well. In order to overcome this weakness a combined integration of statistical difference and equivalence tests into choropleth maps is suggested and the approach is exemplified with health data of Austrian newborns.
  
  
  CONCLUSIONS
  The suggested method will improve the interpretability of choropleth maps for policymakers and health authorities.
authors.affiliation: Department of Epidemiology, Center for Public Health, Medical University of Vienna, Borschkegasse 8a, A-1090 Vienna, Austria.
authors.forename: Thomas
authors.initials: T
authors.lastname: Waldhoer
authors.forename: Harald
authors.initials: H
authors.lastname: Heinzl
mesh_terms: D001317:Austria; D001499:Bayes Theorem; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D004812:Epidemiologic Methods; D005260:Female; D005843:Geography / Q000379:methods*; D005865:Gestational Age; D006291:Health Policy; D006801:Humans; D007226:Infant Mortality / Q000639:trends; D007231:Infant, Newborn; D008377:Maps as Topic; D016012:Poisson Distribution; D011247:Pregnancy