The SaaS cloud-based technology links to an EHR or other population health tool, enabling use at the point of care. Since healthcare treatment is not linear and can be very complex, the algorithm learns over time and can aid providers in the navigation of patient treatment or intervention as necessary – a “GPS for Patient Care.”
The Faros technology has been clinically proven using data from a national healthcare provider, demonstrating 40% better outcomes with a 40% reduction in cost (AI-predicted treatment vs. treatment-as-usual).
Let’s take the example of a patient showing signs of clinical depression. She may have been identified as being “at risk” using population health software or has had repeated visits to the ER. Not only is this expensive, but she is not getting clinically better.
After an intake, establishing a baseline and defining the symptoms the patient is experiencing, the clinician must decide a course of treatment. The traditional approach is for the clinician to pick the treatment option they may have read about in scientific literature, heard at a conference, or most likely based on experiences with their typical patients in the past.
In other words, treatment choice would be based on what worked for average patients before, not the individual characteristics of the current patient. In complex medical conditions – and behavioral health in particular – often what is prescribed for the “average” patient results in poor outcomes and high costs.
With Faros, the clinician has access to an AI tool which assists in making the optimal treatment choice(s). The tool can continue to be used by the clinician to define and revise the course of treatment to achieve the best results in the most efficient manner.