Translating research into practice: organizational issues in implementing automated decision support for hypertension in three medical centers

Abstract

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.

Figure 1.

Model of ATHENA DSS architecture.

Figure 2.

Sample ATHENA advisory recommendations.

Figure 3.

Sample ATHENA BP prescriptions graph: blood pressures and antihypertensive prescriptions on same time line. Target blood pressure is shown as a straight line.