Abstract
Background The Virtual Data Warehouse tumor registry enables important multi-site research in cancer prevention, treatment and outcomes, as well as health communications and quality. Ideally, data are collected from hospitals where the tumors are biopsied, staged, and reported to the state. These data can be difficult to obtain for HMOs such as Kaiser Permanente in the Mid-Atlantic States (KPMAS) that do not own their own hospitals. In such cases, the HMO must request tumor data from the state. This process is particularly complex at KPMAS, which represents three independent jurisdictions (Maryland, Virginia and the District of Columbia). Our end goal is to develop a KPMAS tumor registry that integrates data from electronic health record (EHR) systems and state tumor registries. A key intermediate objective was to develop a comprehensive understanding of tumor registry development at more advanced HMORN sites in order to efficiently build the KPMAS tumor registry.
Methods We used a multi-pronged approach to develop the technical structure for the KPMAS tumor registry. First, we surveyed other HMORN sites that have previously successfully developed tumor registries. Second, we reached out to existing tumor registry efforts within KPMAS to
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reduce duplication,
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capitalize on existing work in this area, and
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document the workflow: from data capture through state reporting and integration into our electronic health record.
Third, we developed relationships with key tumor registry managers in all three KPMAS jurisdictions to identify the processes required for obtaining tumor data corresponding to our members. During this process, we requested both a data dictionary and a set of dummy data from each of the external jurisdictions.
Results Using the data dictionaries and dummy data provided by the external tumor registries, we developed a technical solution for housing and managing tumor related information from multiple sources. Key considerations involved integrating data from external sources with data from the EHR and removing duplicate data that results from integrating data from three external agencies that cover a highly mobile geographic area.
Conclusions Integrating tumor data from multiple sources involves both technical challenges and requires that a complete understanding of the data meaning.
