5 Questions On Exploring Healthcare Decision-Maker Sentiments

A Q&A with Darlena Le, PharmD, research fellow, Health Outcomes and Market Access

Artificial intelligence is rapidly transforming various sectors, and healthcare market access is no exception. While often used for process efficiency, researchers are now exploring AI's potential to unlock insights from complex qualitative data. A new study leverages natural language processing (NLP) to analyze sentiments expressed by healthcare decision-makers (HCDMs) regarding new therapies. By applying sentiment analysis to feedback on clinical efficacy, patient value, and economic value collected via FormularyDecisions, the research aimed to predict formulary coverage outcomes.

Darlena Le, PharmD, lead author of an upcoming AMCP poster on this topic, shares the surprising findings and implications of using AI to decode HCDM perceptions. Could understanding sentiment truly predict a drug's formulary success? Discover the key takeaways, unexpected results, and future directions of this innovative research. Access the full article here.