AI innovation for the real-world journey through care
AI innovation for the real-world journey through care
How we use Augmented Intelligence (AI) to advance evidence-based practice and drive efficient, systematic member engagement—at scale
So many healthcare organizations seem to tout AI as the magic bullet for revolutionizing care. Often, however, we see style without substance.
But at Ontrak, we do things differently. Because for more than a decade we’ve been pushing continuous AI innovation to solve real-world, practical challenges associated with behavioral healthcare. That means infusing Augmented Intelligence (AI) across the entire behavioral healthcare value chain. We’re continuously automating the inefficient, manual processes that create fragmented member experiences—and undermine consistent engagement.
Today health plans and providers are striving to meaningfully engage members. But as provider panels expand, it becomes more and more difficult to reach everyone. And case managers can’t do everything.
So, how do we achieve true scale and efficiency?
Introducing the Ontrak Advanced Engagement System: A five-pronged approach that leverages AI to identify, reach, engage, and provide access to members throughout the behavioral healthcare journey – powered by 200+ member-specific AI-enabled care signals.
Below we describe each program component, illustrating how we use AI to advance evidence-based practice and drive efficient, systematic member engagement—at scale.
Ontrak Identify: The power of AI for uncovering hidden needs
The journey begins with Ontrak Identify, where we employ advanced AI and predictive algorithms to systematically analyze over half-a-billion member health records annually.
The magic is in our RINGS predictive model—a multi-source, risk-based analytics algorithm. This innovative tool allows us to identify members living with unaddressed behavioral health conditions even without a formal diagnosis. In other words, RINGS can find members with, for example, high-predicted probability of substance use disorder or depression, but no associated diagnosis in existing health records.
This capacity to identify those flying under the radar of traditional healthcare models exemplifies the real-world utility of AI. We’re truly moving beyond buzzwords to bring critical help to those who might otherwise remain overlooked or ignored.
Most importantly, this approach to finding mid- and high-acuity members helps drive pathways to more appropriate diagnosis and treatment. Members finally get the care they need. And health plans can perform more accurate risk adjustments to optimize access to care and maximize revenue.
Ontrak Outreach: AI-enhanced conversations that care
After we identify members who will benefit from our program, Ontrak Outreach takes the stage. Here, AI is more than just technology; it’s a bridge to human connection.
We use AI in a myriad of ways to achieve much greater efficiency in outreach, systematically bringing new members into the program. Here’s what it looks like.
Prioritization and accuracy
First, we use AI algorithms to prioritize outreach based on factors like risk, readiness, acuity, claims, prescriptions, and enrollment history. We prioritize those most in need—and most ready to engage with health benefits and commit to change.
Next, our technologies can scrub and triangulate member contact information. This configuration option lets us identify the best member number and time to call. And it also ensures we connect with the right members at the right time.
Taken together, our AI-driven outreach is light years ahead of the old model where case managers simply work their way down a call list.
Evidence-based motivational interviewing
Motivational interviewing is a conversational technique designed to strengthen a person’s motivation and commitment to change. We rely on this approach to maximize engagement. And we strengthen this approach using AI.
Outreach specialists get real-time skills-based training insight into how their motivational interviewing techniques perform, so they can select and tailor techniques most likely to resonate. To support this iterative approach, Al provides call summarization and customized dialogue prompts aligned with member readiness metrics.
It’s evidence-based practice at its best. A sophisticated dance of technology and empathy, where AI insights enable our specialists to build trust—and empower members to take the next step towards better health.
Ontrak Engage: AI-driven analytics support 1:1 Care Coaching
The next element of our approach is Ontrak Engage, where AI’s role shifts to systematic, evidence-based engagement to empower members on the behavioral healthcare journey
AI-powered journey mapping and 360-degree member visibility
AI tools give Care Coaches real-time insights through our Measurement Feedback System (MFS). These technologies enable Care Coaches to create personalized care plans, while enhancing care quality through performance analytics.
After each interaction, AI-powered speech-to-text tools generate theme-based summaries. Simultaneously, natural language processing (NLP) systematically analyzes notes and summaries to concretely measure care practices—and track member progress over time.
This is innovation where it’s needed most. Now Care Coaches, health plans, and providers can gain a clear, comprehensive view of care activities, delivering measurable evidence of impact and outcomes. In all cases, AI-driven analytics facilitate a continuous improvement loop, ensuring member interactions remain firmly rooted in evidence-based practice.
AI Virtual Assistant scaling for Omnichannel Engagement
Engaging members is also about meeting them where they are. And delivering specific interventions at precisely the right time. Our members drive how and when they get support. This can be through text, email, phone calls, chat or even AI virtual assistance.
As an example, while collecting Patient Reported Outcome Measures (PROMs) our AI Virtual Assistant can grasp, in real-time, the nuances of a member’s intent and sentiments. This technology utilizes conversational rhythm, voice intonation, and several other factors related to how and what members communicate.
Not only do we use call summaries from natural-language processing (NLP) and machine learning (ML), but it also generates critical care signals, highlighting any urgent issues that might require Care Coaches to take action.
Next-Best Action Engine
Based on AI-identified Care Signals and AI-generated call notes, our Next-Best Action Engine will also issue actionable recommendations to our Care Coaches. This empowers our team to drastically increase operational efficiency, ensuring we prioritize resources where they’re needed most.
Consider that managing large caseloads requires coaches, case workers, and providers to collect and integrate data from multiple sources. From there, teams must identify and prioritize high-risk patients. And only then implement evidence-based interventions, and monitor outcomes and progress.
These tasks are time-consuming and error-prone, and often require manual effort and coordination.
But now our Next-Best Action Engine automates virtually all of this. Leveraging advanced data analytics and machine learning algorithms provides Care Coaches with a centralized platform to assist them in making informed decisions, optimizing patient care pathways and delivering personalized care. All next-best action recommendations consider
– Each Care Coach’s case load
– Each member’s personal journey
– Existing workflows
– Provider and specialist interventions
– Care plans
– Existing priority list
The Next-best Action Engine may also trigger our generative AI clinical voice assistant. The AI Virtual Assistant calls members directly to facilitate evidence-based clinical assessments, appointment reminders, follow-up activities, and more. It’s a powerful tool to engage members at scale. It also facilitates data collection between sessions, helping to identify problems and validates member progress on the behavioral healthcare journey.
Ontrak Access: NCQA CVO, 7,900+ Behavioral Health providers
We have contracted with 7,900+ providers in 45 states to improve access, appointment availability, and accountability for our clients and members.
Provider Matching Engine
Ontrak Access is enhanced by our Provider Matching Engine, which selects the most appropriate specialist for each member based on their needs. The Provider Matching Engine considers more than a dozen specialties and 30 sub-specialties, performance, and outcomes as well as mode of delivery, diversity equity inclusion (DEI), and demographics. The information that feeds our matching capabilities includes patient preferences and results from initial assessments, prior claims, and imputed diagnoses. Connecting people with the best-fit provider increases their likeliness to remain actively engaged in treatment.
Through our Advanced Engagement System, we’re helping to ensure members get access to exactly the right provider for their unique needs.
Closed-loop, bi-directional HITRUST secure data sharing
Once we connect members with the right provider, our data infrastructure works to facilitate a closed-loop, bi-directional HITRUST secure data sharing ecosystem, seamlessly connecting health plans, providers, specialists, and our Care Coaches.
This integrated network ensures that the most current and comprehensive care information circulates in real time. As specialist providers tailor their interventions, they are informed by the latest insights from our Care Coaches through care coordinators and HITECH-certified interoperability frameworks, encompassing member interactions, progress, and challenges. Conversely, our Care Coaches receive timely updates from healthcare providers, including detailed care notes and treatment adjustments.
Beneath everything are next-generation AI-driven data management and analytics tools. For example, through a proprietary data infrastructure, the Data Exchange platform simplifies the process of managing electronic data interchange (EDI), while complying with federal requirements and best practices in the industry saving 80% in pipeline maintenance costs and delivered nearly 90% shorter turnaround times.
A continuous exchange of Augmented Intelligence (AI) empowers our Care Coaches to effectively guide members in adhering to their treatment plans and following through on provider recommendations. The Ontrak Advanced Engagement System is designed to support informed decision-making and coordinated care efforts, thereby enhancing treatment adherence, and fostering better health outcomes for our members.
AI Care Signals with purpose – Ontrak Advanced Engagement System
Our proprietary blend of 200+ AI-infused Care Signals is a testament to Ontrak Health’s commitment to practical, impactful innovation. In contrast to the vaporware that often characterizes the technology landscape, our AI solutions are squarely focused on solving real-world challenges in behavioral healthcare.
By integrating AI across the Identify, Outreach, Engage, Access and Quality components of our Advanced Engagement System, we’re not just talking about innovation, we’re delivering it.
This is AI with purpose: efficient, systematic member engagement—at scale. Powering care in ways that are both meaningful and measurable.
In a world where technology often promises more than it delivers, we’re proving that the right tools, applied with expertise and empathy, can truly transform lives.
Ontrak Quality: Closing HEDIS/STARS gaps in care
Closing HEDIS/STARS gaps in care
Finally, the last component of our AI-powered targeted approach is our Ontrak Quality offering, designed to help health plans and providers close gaps in care, thereby improving quality measures and ultimately quality scores. Quality scores play a vital role in shaping the healthcare landscape, impacting reimbursement rates, star ratings, and patient outcomes.
Ontrak Quality provides a comprehensive solution to identify, manage, and close care gaps through a combination of advanced technology, robust data management, and personalized patient outreach. The product is designed to address key quality measures such as HEDIS (Healthcare Effectiveness Data and Information Set) and Star Ratings, which are widely used by organizations like the Centers for Medicare & Medicaid Services (CMS) for quality assessment in Medicare Advantage plans and by many state Medicaid programs.
Core Features
Advanced Data Analytics – The solution utilizes AI-driven analytics to identify high-risk patients and gaps in care across multiple measure sets, prioritizing interventions based on impact and feasibility.
Integrated Patient Outreach and Engagement – Through tailored communication strategies, the solution facilitates personalized outreach and engagement strategies to members who are due for critical care services, increasing compliance rates.
Care Coordination and Integration – Seamless integration with existing Electronic Health Records (EHR) and care management systems allows care teams to access real-time data, coordinate care more effectively, and track patient progress.
Quality Improvement Dashboard – A user-friendly interface that offers real-time tracking of performance, enabling healthcare organizations to monitor their quality improvement efforts and adjust strategies accordingly.
Scalable Ecosystem – Advanced Engagement System capabilities that inherently scale along with configurable expansion of supported quality measures.
Closing gaps in care and improving quality scores
Ontrak has successes in closing care gaps for our members, including key areas such as diabetes screening, Follow-up post Hospitalization for Mental Health, and Adult Access to Primary Care. These initial results demonstrate the product’s effectiveness in real-world scenarios in its current product portfolio and its potential impact on improving quality scores.
As healthcare organizations increasingly focus on closing care gaps, the demand for targeted solutions that can deliver measurable results continues to rise. Ontrak’s Quality product aligns with this growing market need, providing healthcare payers and providers with a comprehensive, effective tool to enhance quality and operational efficiency.
