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. 2016 Apr;9(2):161-9.
doi: 10.1007/s40271-015-0135-y.

Evaluating a Decision Aid for Improving Decision Making in Patients with Early-stage Breast Cancer

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Evaluating a Decision Aid for Improving Decision Making in Patients with Early-stage Breast Cancer

Sarah T Hawley et al. Patient. 2016 Apr.

Abstract

Background: Early-stage breast cancer patients face a series of complex treatment decisions, with the first typically being choice of locoregional treatment. There is a need for tools to support patients in this decision-making process.

Methods: We developed an innovative, online locoregional treatment tool based on International Patient Decision Aids Standards criteria. We evaluated its impact on patient knowledge about treatment and appraisal of decision making in a pilot study using a clinical sample of newly diagnosed, breast cancer patients who were randomized to view the decision aid website first or complete a survey prior to viewing the decision aid. Differences in knowledge and decision appraisal between the two groups were compared using t-tests and chi-square tests. Computer-generated preferences for treatment were compared with patients' stated preferences using chi-square tests.

Results: One hundred and one newly diagnosed patients were randomized to view the website first or take a survey first. Women who viewed the website first had slightly higher, though not significantly, knowledge about surgery (p = 0.29) and reconstruction (p = 0.10) than the survey-first group. Those who viewed the website first also appraised their decision process significantly more favorably than did those who took the survey first (p < 0.05 for most decision outcomes). There was very good concordance between computer-suggested and stated treatment preferences.

Conclusion: This pilot study suggests that an interactive decision tool shows promise for supporting early-stage breast cancer patients with complicated treatment decision making.

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Conflict of interest statement

Disclosures:

Conflict of interest: Sarah T. Hawley, Jennifer J. Griggs, Lisa Newman, Mary Ann Kosir and Steven J. Katz declare that they have no conflict of interest.

Figures

Figure 1
Figure 1
Example of one screenshot of interactive values clarification exercise using conjoint analysis

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