• Annals of family medicine · May 2005

    Review

    Infrastructure requirements for practice-based research networks.

    • Lee A Green, Linda L White, Henry C Barry, Donald E Nease, and Brenda L Hudson.
    • Department of Family Medicine, University of Michigan, Ann Arbor, Michigan, USA. greenla@umich.edu
    • Ann Fam Med. 2005 May 1; 3 Suppl 1 (Suppl 1): S5S11S5-11.

    BackgroundThe practice-based research network (PBRN) is the basic laboratory for primary care research. Although most PBRNs include some common elements, their infrastructures vary widely. We offer suggestions for developing and supporting infrastructures to enhance PBRN research success.MethodsInformation was compiled based on published articles, the PBRN Resource Center survey of 2003, our PBRN experiences, and discussions with directors and coordinators from other PBRNs.ResultsPBRN research ranges from observational studies, through intervention studies, clinical trials, and quality of care research, to large-scale practice change interventions. Basic infrastructure elements such as a membership roster, a board, a director, a coordinator, a news-sharing function, a means of addressing requirements of institutional review boards and the Health Insurance Portability and Accountability Act, and a network meeting must exist to support these initiatives. Desirable elements such as support staff, electronic medical records, multiuser databases, mentoring and development programs, mock study sections, and research training are costly and difficult to sustain through project grant funds. These infrastructure elements must be selected, configured, and sized according to the PBRN's self-defined research mission. Annual infrastructure costs are estimated to range from $69,700 for a basic network to $287,600 for a moderately complex network.ConclusionsWell-designed and properly supported PBRN infrastructures can support a wide range of research of great direct value to patients and society. Increased and more consistent infrastructure support could generate an explosion of pragmatic, generalizable knowledge about currently understudied populations, settings, and health care problems.

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