How machine learning and digital therapy improve personalized care

Panelists from the National Alliance of Healthcare Buyer Coalitions 2022 Leadership Summit discussed the latest innovations in digital therapies and how they benefit patients on an individual and broad scale.

In a session at the National Alliance of Healthcare Buyer Coalitions 2022 Leadership Summit, leaders from various types of companies spoke about how the latest innovations in personalized health are changing the way patients receive care.

Machine learning and personalized healthcare

Rich Krutsch, vice president of People Services at ArcBest, opened the conversation by emphasizing the need for people-centric, data-driven approaches to improve the patient experience when seeking care.

According to Krutsch, from a behavioral economics perspective, there are 2 mechanisms: fuel and friction.

“If you reduce the friction with the health care that people need, they’re much more likely to take advantage of it,” he said, noting that fuel, or incentives, alone can do so much.

In collaboration with Inclusive Health, ArcBest has developed a chat-based coaching system that reduces friction as a coach helps patients find the right type and level of care. In particular, the system uses machine learning to help patients assign welfare groups, predict total health care costs at the individual level, and “prescribe” other actions to improve patient outcomes, and has been shown to improve well-being while reducing costs.

Krutsch said this type of machine learning approach not only helps the individual patient, but also helps understand and predict a population of patients, and other companies can and should learn from this method.

“In order to make a difference in the future and move people effectively through the healthcare supply chain, I think we need to be better at holistic data, and that’s kind of our approach,” he said.

Bradley Kirkpatrick, Chief Commercial Officer of Hydrogen Health, added by discussing how highly personalized care not only helps individual patients, but also closes gaps in health equity.

According to Kirkpatrick, it’s not just about collecting the data, but also using artificial intelligence (AI) – while still knowing when traditional bricks and mortar are needed – to understand the next steps and start a conversation. bring.

“It creates a health dialogue that’s an AI layer that’s available to someone 24/7 and creates that comfort level that ‘maybe someone is always there for me,'” he said.

When implemented, this machine learning approach delivered a diagnosis with 85% accuracy based on what patients communicate. It also helps filter out which patients need medical attention and uses data from millions of patients to create a more specific prescription for a patient, not just group them into a drug class.

Kirkpatrick also noted that while it uses machine learning, this isn’t an algorithmic approach, but instead uses information from the patient’s last response to further the discussion and better understand the next steps.

“Twenty percent of the time, people need that peace of mind, and they’re not going to seek care, they don’t need care, they’re going to treat it at home,” Kirkpatrick explained. “But 80% of the time they can click 1 button and go to a doctor in minutes and the problem can be solved and treated.”

The need for convenience in digital therapy

Especially since the onset of the COVID-19 pandemic, it has been a challenge for patients to find therapists, both in person and virtual for behavioral health.

Madleine Makori, PharmD, senior medical science liaison at Big Health, reiterated the idea that friction and inaccessibility is a major barrier to patients, and emphasized the importance of convenience to behavioral health care.

According to Makori, digital therapies combine the benefits of both therapy and medicine† While therapy offers behavioral interventions, it can be expensive and difficult to access. On the other hand, drugs can be affordable but can be ineffective or lead to side effects in some patients.

However, approved digital therapies provide guidelines-recommended behavioral care while also being affordable, accessible, and backed by clinical data.

For Big Health’s digital therapy, 70% of users were found to achieve clinical improvement and work towards clinical remission. Makori noted that the studies leading to this finding will be replicated to ensure efficacy and safety, and studies used to develop similar uses should be thoroughly investigated to ensure that much of the population that uses it benefits.

The talk was closed by Paul Hering, senior director of market access, contracts and pricing at Orexo US, who discussed 3 Orexo digital therapies for depression, alcohol use and opioid use disorder.

Like Hydrogen Health’s therapy, Orexo’s products use AI to interpret patient input and customize various exercises and next steps for the patient based on their responses.

These exercises include various texts, audio, videos, brochures, and checklists for patients to review. In addition to the need for convenience, patients do not need to get a prescription or download an app to use them, as they can be accessed through a browser.

Finally, Hering noted that every patient is different and therefore needs a personalized pathway to healthcare.

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