A Self-scaling, Distributed Information Architecture for Public Health, Research, and Clinical Care
- Affiliations of the authors: Children’s Hospital Informatics Program at the Harvard–MIT Division of Health Sciences and Technology, Boston, MA; Dana-Farber/Harvard Cancer Center, Boston, MA; Harvard Medical School, Boston, MA; Laboratory of Computer Science, Massachusetts General Hospital, Boston, MA
- Correspondence and reprints: Andrew J. McMurry, Children’s Hospital Informatics Program at the Harvard–MIT Division of Health Sciences and Technology, 300 Longwood Ave., Enders Room 150, Boston, MA 02115; e-mail: <amcmurry{at}chip.org>
- Received 7 January 2007
- Accepted 9 April 2007
Abstract
Objective This study sought to define a scalable architecture to support the National Health Information Network (NHIN). This architecture must concurrently support a wide range of public health, research, and clinical care activities.
Study Design The architecture fulfils five desiderata: (1) adopt a distributed approach to data storage to protect privacy, (2) enable strong institutional autonomy to engender participation, (3) provide oversight and transparency to ensure patient trust, (4) allow variable levels of access according to investigator needs and institutional policies, (5) define a self-scaling architecture that encourages voluntary regional collaborations that coalesce to form a nationwide network.
Results Our model has been validated by a large-scale, multi-institution study involving seven medical centers for cancer research. It is the basis of one of four open architectures developed under funding from the Office of the National Coordinator of Health Information Technology, fulfilling the biosurveillance use case defined by the American Health Information Community. The model supports broad applicability for regional and national clinical information exchanges.
Conclusions This model shows the feasibility of an architecture wherein the requirements of care providers, investigators, and public health authorities are served by a distributed model that grants autonomy, protects privacy, and promotes participation.
Footnotes
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Supported by contract N01-LM-3-3515 and grant 1 R01 LM007677-01 from the National Library of Medicine, grant P01 CD000260-01 from the Centers for Disease Control and Prevention, grant 5P30CA06516-40 from the National Cancer Institute, and contract number 5225 3 338CHI from the Massachusetts Department of Public Health.
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The authors thank the dedicated members of the AEGIS development team, whose contributions were critical in making this effort a success: Lucy Hadden, Chaim Kirby, Chris Cassa, Karen Olson, and Lucas Jordan. Countless individuals contributed to the overall SPIN mission. Of those not mentioned above, the following people also contributed toward the development of SPIN for public health: Ana Holzbach, David Berkowicz, and Connie Gee.
