HealthPrize combines the best of Artificial Intelligence with an exceptional team of Doctors, Engineers, and Support staff to create the industry leading solution for medication adherence, member engagement, and health behavior change. This post describes three areas where we’re leveraging Artificial Intelligence (“AI”) and Machine Learning (“ML”) to drive results and provide an engaging experience for our members.
Predictive Modeling
Our Intelligent Pathways™ process creates a personalized experience for each of our members which is highly effective at keeping them engaged. It delivers health content, actionable prompts, and enjoyable incentives with the right relevancy, at the right time and in the right amount to drive the greatest impact. In this process, embedded AI evaluates risk factors for churn, helping us to identify which members are at risk of disengaging. Knowing who may be on the verge of never returning allows us to intervene proactively, keeping them on track and in the program longer. Under the hood, we’ve built a Deep Learning model that uses neural networks to analyze vast amounts of data to arrive at these predictions. Over time we’ve seen our member retention numbers increase, which is directly correlated with sustained success in producing better long-term health outcomes.
Multiple data inputs are analyzed to generate an optimized, personalized experience.
Prescription Refill Processing
Ensuring that members have an adequate supply of their prescribed medication on hand is at the core of improving overall medication adherence. One way we do this is by verifying each refill then prompting the member to fill again on time. HealthPrize processes prescription refill data from a variety of sources and one of the most challenging formats is the prescription label image. These labels are not standardized and look completely different based on the pharmacy that dispensed the medication. That makes automating the verification process rather difficult. Some key fields on the label include Rx number, quantity, and expiration date. We’ve seen millions of these images over the years and with that experience we were able to leverage machine learning and computer vision to build a workflow that extracts these fields automatically. This efficient process is more accurate and faster which frees our team to focus on exceptions and other important member services.
Using secure computer vision, the Rx label data is interpreted to make verifying prescriptions faster and more accurate.
HealthPrize medical writers create prompts for machines to generate content ideas to make the writing, editing, and referencing process more efficient – no content goes live without final medical approval.
Content Co-creation
Providing our members with compelling educational content is how we improve their health literacy while keeping them engaged. It takes a high volume of content to keep the user experience fresh and exciting, especially for members who have been with us for many years. HealthPrize leverages Generative AI during the content generation process to suggest new health topics from relevant sources. This gives our team of doctors and medical writers a continuous supply to qualify, fact check and reference ensuring members receive the highest quality content experience.
Across all areas of our company, we are finding new ways to incorporate AI to drive better health outcomes and greater efficiency. We have not reached a point where AI can take over and dictate the member experience. Everything AI produces goes through a responsible, rigorous process to ensure relevance and accuracy. Our team is eager to explore and cautiously enhance our platform capabilities through the application of Gen AI and Machine Learning.