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Combining difference and equivalence test results in spatial maps

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 c...

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Detalles Bibliográficos
Autores principales: Waldhoer, Thomas, Heinzl, Harald
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3032638/
https://www.ncbi.nlm.nih.gov/pubmed/21219612
http://dx.doi.org/10.1186/1476-072X-10-3
Descripción
Sumario: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.