Method: ACA software was used to create a web-based preference elicitation tool in English and in Spanish. Women with AUB were randomly assigned to ACA or usual counseling at the initial clinic visit. The ACA tool elicited preferences across eight attributes: treatment efficacy; sexual function; medical care; cost; fertility; frequency of medication use; permanence; and recovery time. For those randomized to ACA, printed results were provided to the patient and the physician for use during the patient consult. Approximately six weeks later, study participants were mailed two surveys—the Functional Assessment of Chronic Illness Therapy-Treatment Satisfaction-Patient Scale and the Decision Regret Scale. T-tests were used to compare differences in the primary outcomes of decision regret and treatment satisfaction.
Result: 183 participants were randomized to ACA and 191 to usual counseling, stratified by clinical site. The study was powered at 80% for the primary outcomes. Use of ACA did not reduce decision regret or improve treatment satisfaction as compared with usual counseling; however, planned subgroup analyses suggest populations for future study. Overall, mean (SD) treatment satisfaction was high at 35.71 (9.72) (scale of 0-44), and decision regret was low at 25.9 (21.0) (scale of 0-100). There was a strong inverse relationship between age and decision regret (p=0.007). Subgroup analysis in the youngest quartile comprising 64 women age 19-35 showed a statistically non-significant difference in mean regret scores for the ACA group versus usual counseling (24.6 vs. 34.6, respectively, p = 0.08).
Conclusion: The ACA survey is feasible and easily incorporated into routine clinical practice. However, the use of ACA at the initial consultation visit did not reduce decision regret or improve treatment satisfaction in the overall study population. Future research should explore the use of ACA beyond satisfaction and regret, as ceiling effects were an issue with these measures. There is a need to incorporate physician as well as patient feedback on the use of preference elicitation tools in future research.
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