Article
Spatial distribution of demand and supply for dental services in Northern Germany: a longitudinal comparison
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Authors
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Ralf Jäger
- Ernst-Moritz Arndt Universität Greifswald, Institut für Community Medicine, Greifswald, Deutschland
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Neeltje van den Berg
- Ernst-Moritz-Arndt Universität Greifswald, Institut für Community Medicine, Greifswald, Deutschland
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Rainer Jordan
- Institut der deutschen Zahnärzte, Köln, Deutschland
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Wolfgang Hoffmann
- Ernst-Moritz-Arndt Universität Greifswald, Institut für Community Medicine, Greifwald, Deutschland
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Falk Schwendicke
- Charité Berlin, Zahnerhaltung und Präventivzahnmedizin, Berlin, Deutschland
| Published: | September 22, 2015 |
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Outline
Text
Background: Dental services planning needs to account for the spatial distribution of oral health/morbidity, the related demand, and changes in the local dental workforce, i.e. the supply with dental services.
Objectives: We aimed at assessing changes in demand, supply and the ratio of demand and supply between 2001-2011 in Northern Germany, and to identify spatial predictors for potential under- and over-servicing.
Methods: By linking working time of dentists and claim data to oral morbidity in different age groups, a demand model for dental services was constructed. This model was applied to the zip code area (ZCA) level population data of 2001 and 2011 in the federal state of Mecklenburg-Vorpommern in northern Germany. The supply with dental services was calculated using register data and reported gender-specific working time estimates. The ratio of demand and supply was evaluated using Gini-coefficients and spatial analysis. Prediction models for this ratio were assessed using generalized linear and geographically weighted regression modelling.
Results: Between 2001 and 2011, there was a significant decrease of the general population of Mecklenburg-Vorpommern (-7.0%), the annual demand of dental services (-13.1%), the dental workforce (-9.5%), and the annual supply (-12.9%). The demand-supply-ratio did not change significantly (p>0.05), but was more unequally distributed between ZCAs in 2011 than 2001 (Gini-coefficient: 44.4 versus 41.9). Few ZCAs were over-serviced, whilst many were under-serviced. Significant spatial clustering of dental practices was not observed (Moran’s I=0.18; Z=1.79, p>0.05 in 2001 and 2011). For 2001, population density significantly predicted the demand/supply ratio, this was confirmed via GWR (R²=0.59). For 2011, no variable had any statistically significant predictive value.
Discussion: A changing workforce and a demographic shift combined with a polarization of demand and supply challenges dental services planning. For Northern Germany, spatially specific dental under- and over-servicing aggravated between 2001 and 2011.
Practical implications: Spatial analyses should be standardly used for dental services planning; the established model is suitable for such analyses.
