Small regional federated data networks are used today for clinical research.
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National data networks with 100+ hospitals are being built.
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A conceptual framework was developed for evaluating networks of different sizes.
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A real four site network was compared to an imagined 4000 site network.
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Large networks have limitations but can take advantage of their heterogeneity.
Abstract
Federated networks of clinical research data repositories are rapidly growing in size from a handful of sites to true national networks with more than 100 hospitals. This study creates a conceptual framework for predicting how various properties of these systems will scale as they continue to expand. Starting with actual data from Harvard’s four-site Shared Health Research Information Network (SHRINE), the framework is used to imagine a future 4000 site network, representing the majority of hospitals in the United States. From this it becomes clear that several common assumptions of small networks fail to scale to a national level, such as all sites being online at all times or containing data from the same date range. On the other hand, a large network enables researchers to select subsets of sites that are most appropriate for particular research questions. Developers of federated clinical data networks should be aware of how the properties of these networks change at different scales and design their software accordingly.
