Collecting Physicians’ Preferences on Medical Devices: Are We Doing It Right? Evidence from Italian Orthopedists Using 2 Different Stated Preference Methods

Abstract

Objectives Physician preference items (PPIs) are high-cost medical devices for which clinicians express firm preferences with respect to a particular manufacturer or product. This study aims to identify the most important factors in the choice of new PPIs (hip or knee prosthesis) and infer about the existence of possible response biases in using 2 alternative stated preference techniques. Methods Six key attributes with 3 levels each were identified based on a literature review and clinical experts’ opinions. An online survey was administered to Italian hospital orthopedists using type 1 best-worst scaling (BWS) and binary discrete choice experiment (DCE). BWS data were analyzed through descriptive statistics and conditional logit model. A mixed logit regression model was applied to DCE data, and willingness-to-pay (WTP) was estimated. All analyses were conducted using Stata 16. Results A sample of 108 orthopedists were enrolled. In BWS, the most important attribute was “clinical evidence,” followed by “quality of products,” while the least relevant items were “relationship with the sales representative” and “cost.” DCE results suggested instead that orthopedists prefer high-quality products with robust clinical evidence, positive health technology assessment recommendation and affordable cost, and for which they have a consolidated experience of use and a good relationship with the sales representative. Conclusions The elicitation of preferences for PPIs using alternative methods can lead to different results. The BWS of type 1, which is similar to a ranking exercise, seems to be more affected by acquiescent responding and social desirability than the DCE, which introduces tradeoffs in the choice task and is likely to reveal more about true preferences. Highlights Physician preference items (PPIs) are medical devices particularly exposed to physicians’ choice with regard to type of product and supplier. Some established techniques of collecting preferences can be affected by response biases such as acquiescent responding and social desirability. Discrete choice experiments, introducing more complex tradeoffs in the choice task, are likely to mitigate such biases and reveal true physicians’ preferences for PPIs.