HCPs are presented with patient profiles with an agreed upon set of characteristics (TBC based on the specific business objectives), and who are prescribed different therapies.
HCPs are then prompted to work backwards to consider and prioritize the (non) clinical factors that led to the different prescribing outcomes.
Through a combined qual/quant methodology, we are able to validate which (non)clinical factors are most likely to impact prescribing – and how to address them.
RX Reflect uses reverse conjoint analysis to simulate real-world scenarios where HCPs work backward from a patient script to identify characteristics, attributes, and needs that influence treatment decisions.
Designed to understand how HCPs balance clinical and patient-centered treatment goals, Rx Reflect combines structured choice experiments with real-world clinical scenarios.
Patient attributes with tx preferences, while also uncovering hidden biases that lead to ‘blind spots’ in prescribing.
Identifies actionable strategies to bridge gaps between HCP intentions and patient outcomes.