This Article Full Text Full Text (PDF) All Versions of this Article: M2371v1 14/4/527    most recent Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by McMurry, A. J. Articles by Mandl, K. D. Search for Related Content PubMed PubMed Citation Articles by McMurry, A. J. Articles by Mandl, K. D.

A Self-scaling, Distributed Information Architecture for Public Health, Research, and Clinical Care

^a Children’s Hospital Informatics Program at the Harvard–MIT Division of Health Sciences and Technology, Boston, MA
^b Dana-Farber/Harvard Cancer Center, Boston, MA
^c Harvard Medical School, Boston, MA
^d 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 (Email: amcmurry{at}chip.org).

Received for publication: 01/07/07; accepted for publication: 04/09/07.

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.

This article has been cited by other articles:

				C. C. Diamond, F. Mostashari, and C. Shirky Collecting And Sharing Data For Population Health: A New Paradigm Health Aff., March 1, 2009; 28(2): 454 - 466. [Abstract] [Full Text] [PDF]

				B. Y. Reis, C. Kirby, L. E. Hadden, K. Olson, A. J. McMurry, J. B. Daniel, and K. D. Mandl AEGIS: A Robust and Scalable Real-time Public Health Surveillance System J. Am. Med. Inform. Assoc., September 1, 2007; 14(5): 581 - 588. [Abstract] [Full Text] [PDF]