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First published June 7, 2004 as JAMIA PrePrint; doi:10.1197/jamia.M1534
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J Am Med Inform Assoc. 2004;11:368-376. DOI 10.1197/jamia.M1534.
© 2004 American Medical Informatics Association


Application of Information Technology

Translating Research into Practice: Organizational Issues in Implementing Automated Decision Support for Hypertension in Three Medical Centers

Mary K. Goldstein, MD, MS, Robert W. Coleman, MS, Samson W. Tu, MS, Ravi D. Shankar, MS, Martin J. O'Connor, MSc, Mark A. Musen, MD, PhD, Susana B. Martins, MD, MSc, Philip W. Lavori, PhD, Michael G. Shlipak, MD, MPH, Eugene Oddone, MD, MHSc, Aneel A. Advani, MD, Parisa Gholami, MPH and Brian B. Hoffman, MD

Affiliations of the authors: Geriatrics Research Education and Clinical Center, VA Palo Alto Health Care System, Palo Alto, CA (MKG, RWC, SBM, PG): Center for Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, CA (MKG); Stanford Medical Informatics, Stanford University School of Medicine, Stanford, CA (MKG, SWT, RDS, MJO, MAM, AAA): Cooperative Studies Coordinating Center, VA Palo Alto Health Care System, Palo Alto, CA (PWL); San Francisco VA Medical Center, San Francisco, CA (MGS); Department of Medicine, University of California San Francisco, San Francisco, CA (MGS); Durham VA Medical Center, Durham, NC (EO); Department of Medicine, Duke University Medical Center, Durham, NC (EO); VA Boston Health Care System – West Roxbury Division, Boston, MA (BBH); Harvard Medical School, Boston, MA (BBH).

Correspondence and reprints: Mary K. Goldstein, MD, MS, GRECC 182 B, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA 94304; e-mail: <goldstein{at}stanford.edu>.

Received for publication: 01/13/04; accepted for publication: 05/21/04.

Information technology can support the implementation of clinical research findings in practice settings. Technology can address the quality gap in health care by providing automated decision support to clinicians that integrates guideline knowledge with electronic patient data to present real-time, patient-specific recommendations. However, technical success in implementing decision support systems may not translate directly into system use by clinicians. Successful technology integration into clinical work settings requires explicit attention to the organizational context. We describe the application of a "sociotechnical" approach to integration of ATHENA DSS, a decision support system for the treatment of hypertension, into geographically dispersed primary care clinics. We applied an iterative technical design in response to organizational input and obtained ongoing endorsements of the project by the organization's administrative and clinical leadership. Conscious attention to organizational context at the time of development, deployment, and maintenance of the system was associated with extensive clinician use of the system.




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