[Experience with the linkage of primary and secondary claims data in an intervention trial]

Gesundheitswesen. 2011 Dec;73(12):e126-32. doi: 10.1055/s-0031-1280754. Epub 2011 Jul 13.
[Article in German]

Abstract

The data linkage of health-related primary and secondary data provides new opportunities for health services research. The advantages of both data sources can be used synergistically, in this way their disadvantages can be overcome. In the context of the evaluation of a health intervention - the integrated health services project ('Gesundes Kinzigtal') - the conditions and requirements for an individualised data linkage of primary data (survey) and claims data of a statutory health insurance are described in this paper. The integration of secondary data permits us not only to assess the intervention concerning physical activity, nutrition and social participation of elderly people ('AGil') but, above all, also to measure and analyse the program effects on the utilisation of health care services. Recommendations regarding the data linkage of primary and secondary data in health services research are derived from the results and experiences of the AGil study. Suggestions are made concerning the suitable pseudonymisation algorithm for primary and secondary data, the matching method, approaches to reduce mismatching and their validation, as well as the legal basis for such a data linkage. Overall, an individualised data linkage of primary and secondary data does not pose any technical problems. Nevertheless a couple of data protection rules have to be followed; the data linkage offers a high knowledge insight to many health and epidemiological research questions and might be the new gold standard for health services research.

Publication types

  • English Abstract

MeSH terms

  • Clinical Trials as Topic / statistics & numerical data*
  • Data Collection / methods*
  • Data Mining / methods*
  • Databases, Factual*
  • Germany
  • Insurance Claim Review / statistics & numerical data*
  • Insurance, Health, Reimbursement / statistics & numerical data*