How do consumers respond when presented with novel doctor performance information? A multivariate regression analysis

Abstract

Background: There is an array of attributes one may consider when selecting a doctor. Consumers must generally select providers in the absence of any standardized performance information about these attributes at the doctor level. Some attributes may be less salient to consumers until presented with novel performance data. Innate decision-making regret, style and skill may be important, given the complexity of processing and trading off on numerous attributes. Objective: There has been limited opportunity to study consumer behaviour in the presence of doctor-level quality information, as these data are not widely available. This study explores how consumers interact with doctor-level performance data, considering their decision-making regret, style and skill. Specifically, it examines how consumers rate 10 doctor attributes before and after exposure to doctor-level quality information. Methods: The study utilizes data from the SelectMD 2.0 Provider Choice Experiment. Respondents (n = 1247) were presented with a mock website reporting quality information and asked to choose a doctor. Difference scores are calculated based on participants' ratings of 10 attributes before and after the experiment and a multivariate ordered probit regression is considered to study the association between the predictors and 10 response outcomes. Results: Consumers change their valuation of doctor attributes following exposure to quality data. As expected, consumers upgrade their valuation of the safety and technical quality attributes, but this is specifically associated with a greater tendency to regret decisions. Instead, those with a more dependent decision-making style downgrade reputation, while those with better decision-making skill downgrade the bedside manner and safety attributes. Patient or Public Contribution: Consumers/patients participated in the pilot testing of the website used for the experiment.