Geisinger's Steele Institute for Healthcare Innovation taps Jvion's AI
Geisinger has selected Jvion’s Cognitive Clinical Success Machine as one of the organization’s critical artificial intelligence assets. The deal follows a successful pilot and validation of Jvion’s performance with industry peers.
The initial scope of the Jvion cognitive machine application will be COPD – chronic obstructive pulmonary disease-related readmissions, and avoidable COPD admissions for patients of the Geisinger Medical Center, the health system’s largest hospital.
"The integration of Jvion’s solution is another step in the Institute’s plan to transform healthcare delivery by improving quality, outcomes, and patient experience, while optimizing efficiencies," said Karen Murphy, RN, executive vice president, chief innovation officer and founding director of the Steele Institute for Healthcare Innovation at Geisinger, in a statement.
"Our goal is to apply the capabilities of the machine to drive significant improvements for some of the largest and most debilitating challenges that we face as healthcare providers," she added.
The use Jvion Cognitive Machine is another manifestation of Geisinger’s focus on elevating the patient journey to provide the highest quality care in the most efficient and effective way.
By integrating leading, proven AI into the technology landscape, Murphy and the care teams at Geisinger Medical Center are leading the industry in applied innovation that results in real patient impact.
"We are excited to be part of this project and an AI partner for Geisinger’s Steele Institute for Healthcare Innovation," said Ritesh Sharma, Jvion's chief operations officer.
Sharma sees Geisinger as a strategic addition to Jvion’s community of clients – one that is paving a path for the provider market to improve how care is delivered.
Jvion’s Cognitive Machine uses Eigen-based technology to help providers take the actions that will improve health. In starts with providers asking 50 or more questions about a patient’s health risk, and how it might be changed.
For each question, the technology can deliver an assessment of individual patients' risk, the clinical and non-clinical factors contributing to it and the most effective actions or interventions to take.