Comparison of Methods in the Field of Epidemiology

Aim

As a first step for the evaluation against illnesses it is necessary to find out which persons are affected. This question starts with the overall number of persons affected in Austria and leads to more precise subdivisions concerning age, gender, origins and socio-economic factors. From the beginning on it was clear that some specific methods are just suitable to survey specific numbers of diseases. It is, for example, not possible to make statements on sample sizes on precise regional levels. This is the reason why it is important to get to know the state of the Austrian data in order to get reliable basic numbers to base on serious conclusions for the planning of care. Therefore, one of the aims is the creation of an overview table that shows which data can be collected in which granularity and with which methods. They are then compared following these characteristics. Furthermore, some methods are tested in order to compare the identified prevalence numbers, to identify deviations and later on develop better methods for these differences.

Methods

In a first step different methods are researched, that might be useful to determine epidemiological numbers such as incidence and prevalence estimates. Pharmacoeconomic approaches such as ATC ICD or Chini on the basis of the GAP-DRG database (Project 7.2) are viewed as potential collection methods, as well as the panel analysis on hospital data, simple quantitative counts of hospital diagnoses and the Austrian Health Survey ATHIS (project 7.3). Furthermore, characteristics of the methods are established and typified following these characteristics, in order to roughly present the possibilities of these methods. As a practical example, and to examine the hypotheses that were also used for the creation of the characteristics, subsequently the prevalence numbers for diabetes, cataracts and strokes are calculated with several of these methods. Afterwards, the effects of the different methods on the prevalence numbers are compared.