Improving the Impact of Resources on Patient Engagement for a Biopharmaceutical Company

The success of a biopharmaceutical company, especially within the immunology sector, hinges greatly on its ability to effectively engage patients. To cater to patients' needs and risk profiles, the Patient Support Programme (PSP) team endeavors to optimize resource allocation while bolstering the impact of these resources on patient engagement. This project aimed to identify the next best resource for patient interaction, maximizing engagement by analyzing behavior and interaction patterns. A methodology was devised, involving patient segmentation based on unique transition counts, clustering within each segment, and employing Markov chains and probability transition tables to predict the optimal resource for patient interaction. Model validation was conducted using a hold-out test set, ensuring robustness and accuracy. By uncovering patterns in patient behavior and resource utilization, the model facilitates efficient resource allocation and heightened patient engagement. This initiative bears significant implications for biopharmaceutical companies, particularly those operating in the immunology domain. Through optimized resource allocation and improved patient engagement, businesses can enhance patient outcomes and satisfaction. Moreover, the adaptable nature of the model enables its potential application across diverse health care settings, promising advancements in patient involvement and resource utilization within biopharmaceutical enterprises.