Videos, Downloads and Infographics

How AI Can Reduce the Consequences for Both members and Payers

8 in 10 payers anticipate an increase in claims after stay-at-home orders are eased and fears about seeking medical care subside. Procedures are expected to increase in late 2020 or 2021, and insurance executives are warning that costs will be driven higher by more-intensive care for patients whose conditions worsened during the pandemic.

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Protecting Revenue While Improving Health Outcomes

Join Tom Lawry, National Director of Artificial Intelligence, Health and Life Sciences, Microsoft and Dr. John Showalter, Chief Product Officer, Jvion, for a discussion on how clinical AI transforms the Iron Triangle which attempts to balance cost, quality and access – into a value pyramid.

Watch the Webinar

Join panelists from Jvion and EnvisonRx soon to be Elixir as they reveal:

  • How an AI-driven approach can help cut through the clutter and identify factors that you can modify to improve care
  • The key to finding patients in your plan at risk of worsening chronic conditions
  • How medical conditions interact with individual socioeconomic determinants to affect medication adherence – and what to do about it
  • AI’s role in spotting patterns of opioid/pain medicine misuse
  • Which SDOH are preventing your members with diabetes and other chronic conditions from managing their disease
Access the Webinar

The key to balancing quality, cost and access to care in today’s landscape is technology. Clinical AI, when adopted successfully can create a value pyramid that streamlines the role of payers, providers and the community to drive optimal outcomes.

Artificial Intelligence (AI) has a lot of buzz around it, but how can it be applied to sepsis care and sepsis prevention?

During this 1-hour session, Michael H. Hooper, MD, Vice President Medical Affairs, Norfolk General Hospital, and Scott Stewart, Senior Process Improvement Engineer for Sentara Healthcare share their experience with AI and sepsis care. The discussion includes a brief overview of AI and its definition, the potential benefits of and challenges with AI, critical workflow and implementation considerations, and a case study of the AI solution in place at Sentara Healthcare.

Eigen-based cognitive machines better identify the patients that can be helped and provide the specific actions to mitigate risk for those individuals. Complete the form to download "The Eigen Difference" PDF to learn more.

Download: The Eigen Difference

Synopsis: Health First, a fully Integrated Delivery Network (IDN) serving the Central Florida area, is effectively saving lives using the latest cognitive science technology. The goal is to reduce all-cause 30-day readmissions by 10%.

The point: By applying Jvion's Clinical Cognitive Success Machine (CCSM), Heath First has realized close to $2M in savings and has reduced readmissions for some of the community's most vulnerable individuals.


Synopsis: Onslow Memorial Hospital serving the coastal North Carolina area, is looking for more effective ways to reduce readmissions. Driven by the Hospital Readmission Reduction Program (HRRP), the return of a patient to the hospital within 30 days of discharge has been a key focus area for the hospital.

The point: By incorporating the advanced cognitive capabilities delivered by cognitive clinical leader Jvion, Onslow Memorial Hospital has saved close to $1M in less than a year. The project has been championed by CEO Penney Burlingame Deal, DHA, as part of an overarching move to strengthen the hospital operationally, clinically, and financially.

Download: Onslow Client Snapshot

Synopsis: Emerging technologies like cognitive science have an adoption gap between technological capability and human adaptation. Such a disconnect diminishes the inherent power of new tools and the ability to effectively and quickly realize the value they deliver. With cognitive machines, there is a tremendous potential that can positively impact the health and lives of millions; but, the newness and sophistication of the solutions could act as speed bumps for easy adoption.

The point: Jvion's Cognitive Clinical Success Machine uses the CEAM approach to help drive adoption and quick value realization by producing compelling, easy to consume, actionable, and meaningful recommendations.


A Solution Comparison

Synopsis: When solutions for driving patient-specific and effective actions were compared against Jvion's Cognitive Clinical Success Machine, three categories emerged: enterprise data warehouses (EDWs)/data lakes, scoring methods, and electronic health/medical record (EH/MR) models. In other solutions, scoring methods fell short on delivering the granularity and specificity needed to enable effective and targeted action. EH/MRs require clean, complete data to target at-risk individuals which is nearly non-existent in healthcare. EDWs had the longest time to delivering returns. Across all other solutions and approaches, speed to value was slow and limited.

The point: Cognitive machines like Jvion's Cognitive Clinical Success Machine are gaining traction within healthcare by mitigating the problems posed by enterprise data warehouses (EDWs)/data lakes, scoring methods, and electronic health/medical record (EH/MR) models while producing recommendations for patient-level predictions and interventions rendered with unparalleled speed, clinical applicability, and patient verity.


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