Jvion’s Cognitive Clinical Success Machine is being applied to help hospitals identify patients who will have a longer than expected inpatient stay and determine the actions that will improve a patient’s health outcome.
Atlanta, GA, September 18, 2017 -- Jvion’s Cognitive Clinical Success Machine is being used by hospitals to help stop length of stay (LOS) outliers and optimize patient discharges. LOS outliers are those patients who have a longer than expected stay in the hospital. “What we know is that LOS outliers are at higher risk of complications and poor outcomes,” explained Dr. John Showalter, Chief Product Officer for Jvion. “And this risk adds up to higher costs for the hospital and for the patient.”
The company’s Cognitive Clinical Success Machine is identifying patients who are at risk of an extended stay and providing the actions that will optimize an individual patient’s discharge. This includes the actions that will decrease the likelihood of complications and nosocomial events. The machine is doing this for every patient regardless of the type of inpatient stay and even if a working diagnosis is not available.
“The underlying Eigenspace platform enables the machine to better identify those patients who are most likely to fall on the extremes of the bell curve for length of stay,” said Showalter. “And because of the clinical intelligence embedded within the machine’s Eigen Spheres, we are able to deliver the most effective actions that will move a patient’s stay toward the median while improving outcomes and the overall patient experience.”
Jvion, Inc. (Jvion) delivers a Cognitive Clinical Success Machine that serves as a high-performance appliance for providers and the healthcare community. It activates macro and micro-level recommendations that help healthcare providers who need ultra-definition patient-level prioritizations, clinical action insights, and suggestions produced with unmatched speed, clinical applicability, and verity. The machine delivers the action-level recommendations that will best reduce the likelihood of an adverse event. This capability is enabled by a cognitive engine driven by horsepower that is based on more than a quadrillion clinical and non-clinical considerations and thousands of data elements. The machine’s thousands of self-learning Eigen spheres are applied to this data for each patient in real time to render an Eigen Propensity Biography that delivers a view into a patient’s total health 30,60,90, up to 365 days in the future. This machine is helping hundreds of hospitals across the nation reduce target illnesses and diseases.
One of the reasons Jvion’s solution is independently ranked number one in clinical predictive science is because the machine is more than accurate, it is effective. Our approach mitigates the “accuracy fallacy” perpetuated within the industry by delivering a true picture of individual patient risk along with adjacent risks and actions that will lead to better health outcomes. Because Jvion’s machine works as a cognitive appliance, it plugs in directly to the existing Electronic Medical Record/clinical systems to deliver recommendations seamlessly into the organic workflow. Clinician and caregiver adoption of Jvion’s recommendations is accelerated because of the “on-demand” nature of the information. The machine outperforms and outsmarts even the highest performing predictive solutions/approaches available. And this performance hasn’t gone unnoticed; Jvion’s solution has won numerous external awards including designation as the #1 Predictive Provider in Healthcare by Black Book Market Research.