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

Area of Science:

• Healthcare consumer behavior
• Medical decision-making
• Health services research

Background:

• Consumers often choose doctors without standardized performance data.
• Doctor-level quality information is scarce, limiting studies on consumer behavior.
• Decision-making factors like regret, style, and skill influence attribute valuation.

Purpose of the Study:

• To explore consumer interaction with doctor-level performance data.
• To examine how consumers rate doctor attributes before and after exposure to quality information.
• To understand the influence of decision-making regret, style, and skill on attribute valuation.

Main Methods:

• Utilized data from the SelectMD 2.0 Provider Choice Experiment (n=1247).
• Participants rated 10 doctor attributes before and after viewing mock website quality information.
• Multivariate ordered probit regression analyzed attribute rating changes.

Main Results:

• Exposure to quality data altered consumer valuation of doctor attributes.
• Consumers increased valuation of safety and technical quality, linked to higher decision regret.
• Dependent decision-makers devalued reputation; skilled decision-makers devalued bedside manner and safety.

Conclusions:

• Consumer attribute valuation is dynamic and influenced by quality data exposure.
• Individual decision-making styles and skills mediate the impact of quality information.
• Understanding these dynamics is crucial for effective healthcare consumer information design.