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What Do Our Patients Truly Want? Conjoint Analysis of an Aesthetic Plastic Surgery Practice using Internet Crowdsourcing: A Pilot Study
Cindy Wu, Medical Doctor, Steven J. Hermiz, Medical Doctor, Roja Garimella, undergraduate/medical student, Paul Diegidio, Medical Doctor, Scott Hultman, Medical Doctor, Clara Lee, Medical Doctor.
University of North Carolina, Chapel Hill, Chapel Hill, NC, USA.

Purpose: Inadequate evidence exists regarding which aesthetic surgery practice attributes are most important to patients. Conjoint analysis is a technique to identify what is most important to consumers, by requiring simultaneous tradeoffs among multiple product attributes. Its application in aesthetic surgery practices hasn’t been well studied.
Methods: Anonymous participants from an academic teaching hospital were asked, via electronic survey, to pick a surgeon for facelift surgery based on five attributes (pricing, photos, testimonials, reputation, training), each with three levels (i.e. low, medium, high pricing). Attribute importance (difference each attribute could make in the total utility of the product) and attribute preference (after trading off other attributes) was calculated using empirical Bayes modeling.
Results: With a 69% (179/261) completion rate, mean age was 43.1 years; 86% were female; 78% Caucasian; 54% married; 95% college educated and 63% with annual household incomes over \,000. Without tradeoffs, surgeon pedigree was ranked most important. With tradeoffs, excellent testimonials, excellent photos, then top tier training pedigree, were preferred over national reputation and lowest price.
Conclusion: Participants placed higher relative importance on training pedigree. Conjoint analysis revealed excellent testimonials, excellent photos, and top tier training was preferred over national reputation and lowest price. This discrepancy revealed actual behaviors compared to stated preferences. Future directions include conjoint analysis in breast augmentation and combined breast-abdominal surgery cohorts using an internet crowdsourcing service.
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