Artificial intelligence (AI) in the form of machine learning (ML) enables computer programs to forecast outcomes more accurately without having been expressly taught to do so. Machine learning algorithms forecast new output values using past data as input. Machine learning is the study of, and development of, “learning” methods, or systems that use data to enhance performance on a given set of tasks. As a component of artificial intelligence, it is considered. It’s a contemporary invention that has improved a lot of business and professional operations as well as our everyday lives. A subset of digital healthcare, digital therapeutics are evidence-based interventions that use high-quality software programs to treat, prevent, or manage a disease or medical condition.
Rich Krutsch, ArcBest’s vice president for people services, opened the discussion by emphasizing that patients need to have a better experience seeking care. Krutsch said that there are two mechanisms in behavioral economics to increase fuel and friction. He stated that if anyone reduces friction in the provision of health care, people are more likely to accept it. However, incentives and fuel can only do so much. ArcBest, in partnership with Included Health, developed a chat-based coaching program that reduces friction. A coach helps triage patients to the right type and level. The system uses machine learning to assign patients to wellness groups, determine individual health care costs, and “prescribe” other actions to improve patient outcomes. It has been proven to increase wellness and reduce expenses.
Krutsch stated that while this type of machine-learning approach helps a single patient, it also helps to predict and understand a larger population of patients. Companies can and should also learn from this approach. He said that “to make a real difference in the future, and to effectively guide people through the health-care supply chain, it’s necessary to have better holistic data. This is the essence of our approach.” Bradley Kirkpatrick of Hydrogen, the chief commercial officer, elaborated on this point, pointing out that highly personalized care does not only help individual patients but also helps to close health equity gaps.
Kirkpatrick said that it’s not about just collecting data but also using artificial intelligence (AI), while still being able to recognize when traditional brick and mortar is necessary, to understand the next steps, and to start a conversation. Kirkpatrick said that it creates a healthy dialogue with an AI layer that is available 24/7 to someone and gives the feeling that “maybe there’s somebody here for me all day.” The machine learning approach was able to produce a diagnosis with an accuracy of 85% using the information patients provide.
It helps to filter through which patients require medical attention and uses data gathered from millions of patients to provide a more tailored prescription for each patient. This is not just a way to group them into one drug class, but also allows the system to help you create a better diagnosis. Kirkpatrick pointed out that while machine learning is used, it doesn’t use an algorithmic approach. It instead uses information from the patient’s last answer to help the discussion progress and understand the next steps. Kirkpatrick explained that 20 percent of people require this peace of mind. “But 80% of people can just click one button to reach a physician in minutes. Then whatever the issue is, it will be addressed and treated.”
Patients have had difficulty finding therapists, both in person and online, since the COVID-19 pandemic. Madeline Makori (PharmD), senior medical science liaison at Big Health, emphasized the importance of accessibility for patients. Makori says that digital therapy combines the best of both therapy and medication. Although therapy can provide behavioral interventions, access to it can be difficult and expensive. However, while medications are affordable and can sometimes be ineffective, they can also cause side effects for some patients.
However, approved digital treatments are supported by clinical evidence, offer behavioral therapy that is suggested by guidelines, and are both inexpensive and accessible. According to Big Health’s digital treatment, 70% of patients have shown signs of clinical improvement and are moving toward clinical remission. According to Makori, similar research will be done in the future to validate efficacy and safety. Makori said that in order to guarantee that the app is usable by a wide audience, it was crucial to do a thorough analysis of comparable applications. Three Orexo digital treatments for the treatment of depression, opioid addiction disorder, and alcohol misuse management were discussed by Paul Hering, Orexo US senior director of market access, contracts, and pricing, to conclude the conversation.