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Purpose: Develop and evaluate a clinical decision aid using a framework for breast cancer prevention care that provides clinical data in context to appropriately motivate women to choose interventions.
Methods: The decision algorithm includes a general health and breast cancer risk assessment using both the Gail and Claus risk models. Standard format for data presentation was implemented, using absolute risk information with consistent graphical presentation. Breast cancer risk over time is presented in the context of age-matched women and evidence-based models using biomarkers as risk discriminators and predictors of benefit from interventions. Physicians providing the prevention care were trained to use the shared decision making framework. Pilot testing in a randomized clinical trial compared physician training only versus physician training with use of the decision aid. Follow-up data was gathered at 6-12 months post consultation to track patient decisions.
Results: The shared decision making framework appeared to increase patient interest in prevention interventions. Initially, 13% of patients were interested in prevention interventions before the consultations, as compared to 23% after the consultation. This rate returned to baseline at follow-up. Similarly, patient interest in risk refinement interventions increased from 7% to 23%. At follow-up, this rate had decreased to 19%. The feasibility outcomes showed that the decision aid did not interfere with the consultation as measured by consultation duration, user satisfaction, patient knowledge and decisional conflict.
Conclusions: Initial results suggest that the decision aid is feasible for use in the consultation room. The decision framework provides access to key information during consultations and allows the integration of emerging biomarkers in the prevention setting. As compared to previously studied clinical behavior, the framework increased patient interest in both preventive interventions and learning more about their level of risk. The tendency for these rates to return to baseline at follow-up suggests the need for ongoing prevention decision support. Future applications of the decision aid include a randomized trial of three arms (a control arm, an arm with physician training only, and an arm with physician training and use of the decision aid) to determine impact on decision-making. The integration of tools to store, track, and present data to patients and physicians will be studied.
See more of Poster Session - Utility Theory; Health Economics; Patient & Physician Preferences; Simulation; Technology Assessment
See more of The 26th Annual Meeting of the Society for Medical Decision Making (October 17-20, 2004)