Distributed Health Data Networks: A Practical and Preferred Approach to Multi-Institutional Evaluations of Comparative Effectiveness, Safety, and Quality of Care

Brown, Jeffrey S. PhD*; Holmes, John H. PhD†; Shah, Kiran BA‡; Hall, Ken MDIV§; Lazarus, Ross MBBS, MPH*; Platt, Richard MD, MSc*

doi: 10.1097/MLR.0b013e3181d9919f
Comparative Effectiveness

Background: Comparative effectiveness research, medical product safety evaluation, and quality measurement will require the ability to use electronic health data held by multiple organizations. There is no consensus about whether to create regional or national combined (eg, “all payer”) databases for these purposes, or distributed data networks that leave most Protected Health Information and proprietary data in the possession of the original data holders.

Objectives: Demonstrate functions of a distributed research network that supports research needs and also address data holders concerns about participation. Key design functions included strong local control of data uses and a centralized web-based querying interface.

Research Design: We implemented a pilot distributed research network and evaluated the design considerations, utility for research, and the acceptability to data holders of methods for menu-driven querying. We developed and tested a central, web-based interface with supporting network software. Specific functions assessed include query formation and distribution, query execution and review, and aggregation of results.

Results: This pilot successfully evaluated temporal trends in medication use and diagnoses at 5 separate sites, demonstrating some of the possibilities of using a distributed research network. The pilot demonstrated the potential utility of the design, which addressed the major concerns of both users and data holders. No serious obstacles were identified that would prevent development of a fully functional, scalable network.

Conclusions: Distributed networks are capable of addressing nearly all anticipated uses of routinely collected electronic healthcare data. Distributed networks would obviate the need for centralized databases, thus avoiding numerous obstacles.

From the *Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA; †Department of Biostatistics and Epidemiology, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, PA; ‡Lincoln Peak Partners, Westborough, MA; and §Deloitte, NCPHI/OD, Atlanta, GA.

Supported by Agency for Healthcare Research and Quality Contract No. 290–05–0033, US Department of Health and Human Services as part of the Developing Evidence to Inform Decisions about Effectiveness (DEcIDE) program.

The authors of this report are responsible for its content. Statements in this report should not be construed as endorsement by the Agency for Healthcare Research and Quality or the US Department of Health and Human Services.

Reprints: Jeffrey S. Brown, PhD, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 133 Brookline Ave, 6th floor, Boston, MA 02215. E-mail: jeff_brown@harvardpilgrim.org.

© 2010 Lippincott Williams & Wilkins, Inc.