Data driven programs for optimal patient support and engagement

Amazon, Netflix and hosts of companies provide customers with personalized experiences and reminders. Patient support programs should be no different. In fact, if we truly want patient support to help brands stand out by driving treatment adherence to achieve better outcomes, then we must treat each patient as an individual, not just a member of a disease class. Effective patient support requires a comprehensive, behavior based, data-driven patient engagement program incorporating real-time, data-driven insights and risk assessments allowing us to continually support individual patients with next best actions.

To make this work, patient support program design should start with a deep dive into the patient population. There should be an assessment of the existing data sources on such things as demographics and product usage, and there should also be qualitative behavior-based interviews of patients conducted to best understand the belief set that underlies patient actions. A behavioral science-based approach should then be tapped to determine the interventions necessary to overcome the underlying perceptions driving patient motivation and the practicalities influencing the ability to adhere. In addition, each patient entering the patient support program should complete a simple intake questionnaire that will help identify that patient’s perceptions, motivation and actions.

All of this data can then lead to a program design tailored to the individual patient’s journey. This may include face-to-face interactions with clinical educators, virtual call center support and delivery of bespoke content via digital channels specified by the patient – all timed to best meet the patient’s needs and goals of the program. It is also important to take into account the patient’s care partner’s needs, as such individuals can provide much needed encouragement or potentially work against the program if not aligned.

With the advent of AI and other sophisticated data capture techniques, patient support programs are in a much better position to continuously learn from the behavioral and clinical data of the patient. Such systems can monitor the patients and support providers in real time and reach out as needed with encouragement, education, and reminders on adherence. Support plans should then adjust accordingly to best meet the patient’s current needs in order to drive ongoing adherence and persistence.