Information alone cannot drive effective behavior change for patients and members. Everyone needs a nudge to be consistent on their health journey.
Powered by our proprietary Large Behavior Model, Lirio’s Personalization Engine combines behavioral science and AI to activate patients and members with hyper-personalized communications.
By creating and deploying interventions tailored to each person with the right content at the right time and via the right channel, we overcome specific barriers to action on individuals’ unique health journeys.
Rooted in Behavioral Science
To move their consumers toward better outcomes and make an impact on costly, chronic health challenges, healthcare organizations must approach population health with a behavioral lens.
People are incredibly complex and influenced by the contexts in which they live, work, and play. You must not only understand who they are and how they make decisions, but also how their behaviors differ across contexts and over time to effectively engage and move them along their unique journey to better health. We use evidence-based approaches to human behavior to help you do just that.
By designing for sustained change and prioritizing their next best action, you can:
Increase Consumer Acquisition
Close Gaps in Care
Promote Condition Management
Drive Long-term Satisfaction and Loyalty
Shaped by Four Continuous Elements
The old-school approach to behavior change is to tell people what they should do and hope it works – unfortunately, it doesn’t. Similarly, one-size-fits-all or even segment-specific efforts via email, SMS, calls, and mailings often don’t move the needle enough.
Our behavioral scientists have a clear understanding of this reality. As humans, we all have shared, unique, and behavior-specific factors that drive our decisions and actions. In addition, clinical care impacts only 20% of health outcomes, while the outstanding majority is driven by socioeconomic factors, the physical environment, and health behaviors.
We address this specific and evolving framework within our AI-informed personalization engine so that it makes decisions based on behavioral science via Precision Nudging®, which includes four continuous elements.
Clinical, demographic, financial, SDOH, historical engagement, and other data help us build a holistic view of how consumers live, work and play, and determine consumer eligibility for each intervention.
Leveraging behavioral science solutions and reinforcement learning agents, our technology optimizes the content, channel, and timing of interventions for each individual to maximize the likelihood of behavior change.
With behavioral science principles encoded in our data, we learn what makes consumers tick, which barriers prevent them from taking action, and which behavioral interventions will connect with their motivations.
Progressively smarter personalization that learns from individual and population-level encounters helps us build rich behavioral profiles and inform future interventions, supporting each consumer’s unique health journey. This leads to better health outcomes for both individuals and populations.
Implemented via Behavioral Reinforcement Learning
To digitally model behavioral science, modeling behaviors need to be broad. That’s why many AI techniques don’t work for behavior change – their modeling behavior is too limited and requires human experts to define the best solution.
What does work is Lirio’s construct of behavioral reinforcement learning (BRL). Our BRL agents autonomously explore an enormous series of options and unlock solutions in a timeframe human experts alone cannot.
Through ongoing interactions, the agents learn from each encounter to better engage them over time, optimizing interventions with a person’s motivations and barriers to move them toward the desired behaviors.
Measurable Results at Scale
Lirio’s personalization engine for digital health generates a progressive stream of learning that moves the consumer and population toward better health outcomes.
As we receive more consumer data and responses, the engine learns and optimizes each journey – first for whole populations, then for specific segments, and finally for individuals – matching each person to the intervention most likely to connect with their motivations.
The result is actionable insights that connect the dots between consumer activity and outcomes that scale with your organization.
How to Navigate the AI Maze in Healthcare
While AI is still relatively new to the industry, the global healthcare AI market is growing fast. Understanding its application is critical to determining which solutions can actually make a difference in care delivery and business operations.
Create seamless patient experiences that improve engagement and outcomes.
Move your members to engage with their benefits and support healthier populations.