Your Own Digital Health Advocate (YODHA) Platform
Applies AI/ML to personalize behavior science driven chats via voice or text that activates self-care from home
Data acquisition and management
Data Acquisition and Management
The AIHS comprehensive approach to data acquisition and integration is foundational to our ability to deliver transformational care management solutions. Episodic health information from claims, EMRs, labs and other public data sources serves as the data foundation for each person served on the platform. Through structured chat conversations with participants we are able to integrate additional insights into their habits, concerns, social barriers to health, emotional states and levels of motivation and self-confidence to create robust insightful patient profiles.
Omni-channel conversational AI platform
Consumer preferences have evolved dramatically over recent years, requiring more digital access to information, self-service options, and more engagement in their own healthcare from the convenience of their home. There also have been dramatic advances in AI, machine learning, large language models and natural language processing (NLP). AIHS is takiong advantage of these technological and analytic advances in our platform. Participants can engage on the Your Own Digital Health Advocate platform by voice and/or text. Taking a conservative approach to large language models, chat interactions with YODHA are via conversational AI which builds and curates the appropriate responses to conversations, questions, or requests via our guided behavior scienc driven chat approach. Participants can download a smart application, use a supplied url link to access the website or use a secure messaging platform.
AI/ML Utilization
Based on the health data from claims, EMRs, and labs, our analytic model performs an initial risk identification and stratification identifying the current level of health risk By combining the data captured in discovery chats with available health data, we are able to create robust patient profiles spanning physical, mental/emotional and social health factors. Our machine learning algorithms identify shared characteristics across participants that can be grouped into cohorts or sub-groups, enabling personalization of engagement approaches to achieve optimal success for participants reaching their health and wellness goals..
Personalized Activation
The journey toward lasting change begins with understanding where each person is today. The Transtheoretical Model of Change provides a framework that guides us through six stages of behavior change from precontemplation to maintenance. By identifying each individual’s stage, we meet them where they are and build momentum from there. Our approach also draws on the power of Cognitive Behavioral Therapy (CBT), a proven method for helping individuals overcome challenges like anxiety, depression, and eating disorders—barriers that can often stand in the way of change. Our unique insights into patient health risks and behaviors enable us to apply targeted, science-based strategies that meet participants where they are and guide them toward greater engagement. Each success boosts motivation and confidence, helping them continue their journey toward lasting health and wellness goals
Performance Management
Performance reporting is provided at the participant, cohort and population level for each client. Care management teams can review the progress of their people and receive alerts when action needs to be taken. The performance metrics are customizable for each client based on the scope services being provided. This may include number of people reached, number engaged, level of engagement, achievements such as goals acchieved, gaps in care closed, chronic disease management management metrics, preventative health services enabled, or discharge plan compliance with self-care from home. Each participant will also have access to their own engagement and achievement information as well as curated reference material that is provided for frequently asked questions.
