Every year health systems assume more risk and manage the increased demand for their services. As the number of patients needing treatment grows and conditions become more severe, the cost of ineffective treatments is all the more damaging. GNS helps health systems identify specific interventions that enable the best possible treatment decision for a patient. Moving beyond standard analytical approaches, the GNS causal machine learning approach simulates and then optimizes all possible outcomes and then prescribes the interventions that optimize the health outcome for the individual patient.

At GNS Healthcare we are working to fundamentally change prevention, detection, and treatment of disease by helping providers predict individual risk and better predict and understand the efficacy of interventions for individual patients.

Bring certainty, precision, and predictive power to every intervention. 

patient-riskBetter patient detection and
risk identification

Identify patient risk factors from multiple sources of patient data to predict patient-specific medical problems.

decisionsBetter care decisions and matching to intervention

Provide your clinical team with the information they need to design a personalized intervention for every patient.

improve-green Better
outcomes

Maximize the likelihood of improved patient outcomes while minimizing costs.

sigle-quote

“At Intermountain Healthcare, we continually strive to improve healthcare outcomes and simultaneously reduce costs through better data and analytic capabilities. After reviewing several hundred data and analytic vendors and piloting fewer than ten, including the GNS Healthcare REFS platform, we have reached the conclusion that GNS has significantly more analytic successes in healthcare using machine learning — sometimes called cognitive computing, artificial intelligence, deep learning, etc. — than any other solution we have seen so far.”

 

Lonny Northrup
Senior Medical Informaticist
Intermountain Healthcare

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