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A recent OptumIQ report found that the number of healthcare leaders implementing an artificial intelligence (AI) strategy in their organization had risen by 88 percent in the last year, to a total of 62 percent. What’s more, nine in 10 leaders are confident they will see a return on their AI investment sooner than previously expected. While AI will never be a replacement for a practitioner, these tools are gaining traction in hospitals for their ability to augment human intelligence. These “Narrow AI” techniques address very specific applications — think language translation, image recognition, and data analysis — to ease our human cognitive load and improve outcomes.

The volume of medical data for physicians to sort through is growing at an exponential rate and is projected to double every 73 days by 2020. Among healthcare executives, consensus is emerging that AI and other analytic tools will be essential to transform this expanding mountain of data into actionable insights that improve quality metrics and patient care. At the Center for Cancer and Blood Disorders (CCBD) in Fort Worth Texas, clinicians have turned to the Jvion Machine to harness CCBD’s vast clinical data to power improved oncology care while reducing costs under the Oncology Care Model (OCM).

Electronic health record (EHR) vendors consistently overrepresent their products as a one stop shop for clinicians with everything needed to manage patient care, but this is simply not true. These vendors claim that the risk scores generated by EHRs are all hospitals need for identifying patients requiring clinical intervention before medical conditions develop. Have you been hearing that from your EHR rep?

Hospitals leading the charge to change the way sepsis is diagnosed and treated are increasingly turning to artificial intelligence (AI) and powerful data analytics. AI-enabled analytics can help practitioners identify patients most likely to develop a deadly infection and take action often before symptoms are even present. This is exactly what’s happening at leading facilities like Southeast Health in Alabama and Sentara Healthcare in Virginia and North Carolina, where clinicians are harnessing the AI-enabled Jvion Machine to drive the primary prevention of sepsis and inhibit the progression of the condition.

In the hospital of the future, technology is helping empower caregivers, enable more personalized care, and optimize operational performance. Artificial Intelligence (AI) is and will continue to enhance the doctor-patient interaction by allowing physicians to focus on the patient rather than technology. In this augmented landscape, providers are pointed to the right patients at the right time and empowered with the information they need to drive to the best possible outcome. Beyond AI, technology will help ingest, manage, and store data to drive innovation. It’s the ability to bring all these data sources together to understand patient health that serves as the platform for true healthcare innovation and continued AI advancement. Watch this two-minute video for more information on Jvion's role in transforming healthcare.

Preventing Sepsis with Cognitive Machines

  • JVION Health

Sepsis confounds care providers because we should be able to avoid it. Nonetheless, it is the most preventable cause of death worldwide.

Sepsis is especially cruel because our own bodies cause it through the natural response to infection, working so hard to battle that they break down tissues and organs. And it is stealth, often not diagnosed until it is too late.

A Better Way to Prevent Inpatient Falls

  • JVION Health

No one likes falling down. For hospital patients, it can be life threatening and represents one of the most prevalent preventable harm conditions. Falls exacerbate patient pain and suffering while extending hospital stays. CMS regulations in place since 2008 have amplified the cost of falls for hospitals, with no reimbursements for treatment of traumas and other fall-related conditions acquired after admission.  Facilities risk further CMS financial penalties for not providing safe environments for patients and residents. The Joint Commission calculates the cost of hospital falls at $14,000 per incident.

Data feeds the Cognitive Clinical Success Machine. Anyone working in healthcare probably has a rough memory about adopting a new technology and struggling to connect new systems with data from existing ones. Not so with Jvion—swift, painless data integration means the machine is giving smart clinical guidance for patients within weeks. Customers share more in this video.

Jvion Chief Product Officer John Showalter

Predictive analytic companies have been latching on to the idea of “impactability” and it is masking the intent of the term and overstating the real capabilities of predictive analytic solutions. The idea behind “impactability” is this: there are patients whose outcomes can be changed with the right intervention and there are patients whose outcomes can’t be changed no matter what you do. This isn’t about caregiving. Clinicians should provide the best care to all patients regardless of the outcome. This is about focusing the right actions to the exact patients who can benefit.