Data quality and integration in collaborative environments

Abstract

The trend to merge medical practices into cooperatively operating networks and organizational units like Medical Supply Centers generates new challenges for an adequate IT support. In particular, new use cases for common economic planning, controlling and treatment coordination arise. This requires consolidation of data originating from heterogeneous and autonomous software systems. Heterogeneity and autonomy are core reasons for low data quality. The intuitive approach of initially integrating heterogeneous systems into a federated system creates a very high upfront effort before the system can become operable and does not adequately consider the fact that data quality requirements might change over time. To remedy this, we propose an approach for continuous data quality improvement which enables a demand driven step by step system integration. By adapting the generic Total Data Quality Management process to healthcare specific use cases, we are developing an extended model for continuous data quality management in cooperative healthcare settings. The IT tools which are needed to provide the information that drives this process are currently in development within a government supported project involving both industry and academia.