The lack of patient-centered healthcare infrastructure leads to disparities and distrust of the healthcare system, resulting in decreased health outcomes and non-adherence. Underrepresented and marginalized communities are disproportionately affected by disparities based upon race, socio-economic factors, structural racism, and interpersonal biases. Hundreds of research studies have been conducted and they all point to the same conclusion, with the most recent exemplification of disparities being the disproportionately high COVID-19 infection and mortality rates among African Americans. Angela Brown, the CEO of the STL Regional Health Committee, which helps provide coverage to 80,000 otherwise uninsured residents, mentioned to us she has lost count the amount of times patients have complained to her about being mistreated, judged, and not taken seriously by their physician. How can we blame them for not adhering to their doctor’s recommended treatment when they don’t even feel listened to? This is why so many patients end up in the ER with serious conditions and having to undergo expensive procedures when it could have been avoided if they felt like they could trust their doctor. This is a reason why there are 125,000 deaths/year due to non-adherence, and it costs $300 billion annually to our healthcare system. And yet what have we done to alleviate this problem? What tools or technologies have been created that are patient-centered and designed to combat these disparities? Why is that modern medicine is standardized, yet certain populations have greater risks and worse healthcare outcomes than the general population?
After 3 years of researching and interviewing hundreds of patients and physicians, we’ve found 51 traits amongst demographics, personal values, and social determinants of health that directly affect trust, which impacts non-adherence. We’ve integrated these 51 traits into a novel, 3-layered machine learning algorithm into a beautiful and streamlined physician recommendation engine and matching platform that allows patients to find compatible doctors based on what actually matters to them in a care setting. Our recommendation engine also factors in location, insurance, and availability, the three limiting factors that patients look for when finding a physician. Dr. Tharakan, an ENT physician we trailed the product with, mentions that as a physician herself, empowering patients with a adaptive algorithm that’s not just based on first availability but more humanistic factors means that patients care about her values and interests before walking into the room, which jumpstarts repoire-building during time-limited visits, which increases trust, patient satisfaction, and allows the formation of longitudinal connections. Physicians can also get targeted feedback and training via the Caralyst Review system instead of generic modules for all staff, which provides granular, causal, and personalized reviews based on each patient’s selected traits that they matched with.

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