The major advantages of an Eigen-based approach are multifaceted. With the Cognitive Clinical Success Machine, providers can:
Personalize interventions: the machine not only finds high-risk patients, it can extend its effective view to identify the interventions that are tailored to the specific factors, risks, and engagement propensity attributed to an individual patient
Amplify clinical impact: this technique allows providers to expand the concept of intervention effectiveness to know which patients are not just high or medium risk but—more importantly—where a provider can impact a patient’s outcome
Drive resources where they are needed: the machine is proven to reduce the cognitive load of the caregiver team by ensuring that the right care is delivered to the right patient at the right time while lowering the cost of care by ensuring the best allocation of resources
The Next Generation in Clinical Impact
To really help control risk, the industry has to look to Eigen-based cognitive machines: the kinds of technologies that know what you are going to type in your search box before you hit a second key; the kinds of technologies that can outwit even the smartest quiz game genius; the kinds of technologies that deliver a glimpse into the future health of a person holistically and provide the most optimal path to prevent illness (which is what we do).
As an industry, we have to move past the idea of isolated risk events driven by use cases (readmission, pressure ulcer, etc.) and think about risk in terms of 1. the entire person and 2. what we can do about it. This holistic way of thinking about patients is the driver behind our Cognitive Clinical Success Machine. While we achieve this through a complex Eigenspace-based platform, the outcome is what really differentiates the machine from any other available predictive, machine learning algorithm. What we power is a vision into what will happen and the specific actions that will keep a person healthy.