TY - JOUR
T1 - Combining Multiple Treatment Comparisons with Personalized Patient Preferences
T2 - A Randomized Trial of an Interactive Platform for Statin Treatment Selection
AU - Hopkin, Gareth
AU - Au, Anson
AU - Collier, Verena Jane
AU - Yudkin, John S.
AU - Basu, Sanjay
AU - Naci, Huseyin
N1 - Funding Information:
Department of Health Policy, London School of Economics and Political Science, London, UK (GH, HN); Department of Sociology, University of Toronto, Toronto, ON, Canada (AA); King’s College London, London, UK (VJC); University College London, London, UK (JSY); and Stanford University School of Medicine, Palo Alto, CA, USA (SB). The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Financial support for this study was provided in part by a grant from STICERD, LSE Suntory, and Toyota International Centre for Economics and Related Disciplines, a research institute within the London School of Economics and Political Science. The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report.
Publisher Copyright:
© The Author(s) 2019.
PY - 2019/4/1
Y1 - 2019/4/1
N2 - Background. Patients and clinicians are often required to make tradeoffs between the relative benefits and harms of multiple treatment options. Combining network meta-analysis results with user preferences can be useful when choosing among several treatment alternatives. Objective. Using cholesterol-lowering statin drugs as a case study, we aimed to determine whether an interactive web-based platform that combines network meta-analysis findings with patient preferences had an effect on the decision-making process in a general population sample. Method. This was a pilot parallel randomized controlled trial. We used Amazon’s Mechanical Turk to recruit adults residing in the United States. A total of 349 participants were randomly allocated to view either the interactive tool (intervention) or a series of bar charts (control). The primary endpoint was decisional conflict, and secondary endpoints included decision self-efficacy, preparation for decision making, and the overall ranking of statins. Results. A total of 258 participants completed the trial and were included in the analysis. On the primary outcome, participants randomized to the interactive tool had significantly lower levels of decisional conflict than those in the control group (difference, –8.53; 95% confidence interval [CI], −12.96 to −4.11 on a 100-point scale; P = 0.001). They also appeared to have higher levels of preparation for decision making (difference, 4.19; 95% CI, –0.24 to 8.63 on a 100-point scale; P = 0.031). No difference was found for decision self-efficacy, although groups were statistically significantly different in how they ranked different statins. Conclusion. The findings of our proof-of-concept evaluation suggest that an interactive web-based tool combining published clinical evidence with individual preferences can reduce decisional conflict and better prepare individuals for decision making.
AB - Background. Patients and clinicians are often required to make tradeoffs between the relative benefits and harms of multiple treatment options. Combining network meta-analysis results with user preferences can be useful when choosing among several treatment alternatives. Objective. Using cholesterol-lowering statin drugs as a case study, we aimed to determine whether an interactive web-based platform that combines network meta-analysis findings with patient preferences had an effect on the decision-making process in a general population sample. Method. This was a pilot parallel randomized controlled trial. We used Amazon’s Mechanical Turk to recruit adults residing in the United States. A total of 349 participants were randomly allocated to view either the interactive tool (intervention) or a series of bar charts (control). The primary endpoint was decisional conflict, and secondary endpoints included decision self-efficacy, preparation for decision making, and the overall ranking of statins. Results. A total of 258 participants completed the trial and were included in the analysis. On the primary outcome, participants randomized to the interactive tool had significantly lower levels of decisional conflict than those in the control group (difference, –8.53; 95% confidence interval [CI], −12.96 to −4.11 on a 100-point scale; P = 0.001). They also appeared to have higher levels of preparation for decision making (difference, 4.19; 95% CI, –0.24 to 8.63 on a 100-point scale; P = 0.031). No difference was found for decision self-efficacy, although groups were statistically significantly different in how they ranked different statins. Conclusion. The findings of our proof-of-concept evaluation suggest that an interactive web-based tool combining published clinical evidence with individual preferences can reduce decisional conflict and better prepare individuals for decision making.
KW - decision aid
KW - decision making
KW - network meta-analysis
KW - patient preferences
KW - statins
UR - http://www.scopus.com/inward/record.url?scp=85063064543&partnerID=8YFLogxK
U2 - 10.1177/0272989X19835239
DO - 10.1177/0272989X19835239
M3 - Journal article
C2 - 30873906
AN - SCOPUS:85063064543
VL - 39
SP - 264
EP - 277
JO - Medical Decision Making
JF - Medical Decision Making
SN - 0272-989X
IS - 3
ER -
