Every healthcare practice and hospital has endured a tough technology adoption. A new system introduced with big promise, but that took months (or years) to implement and disrupted and frustrated clinicians. All without the anticipated improvements in care delivery or efficiency.
And then there are stories like this.
“It gave us exactly what we needed right away. There wasn’t a lot of laborious magic math or data warehouse or any of those things that would [take] six months or a year to realize the effects. It immediately began to provide those patient-level [risk propensities] which were highly accurate. Over time it is getting even better with our interventions as the machine learns even more. It’s instantaneous. It becomes valuable on day one.”
That’s Edye Cleary, Chief Quality Officer at Health First in central Florida, describing the immediate positive impact of the Cognitive Clinical Success Machine at her hospital. Fast, easy implementation and adoption with rapid positive results for patient care.
We are the first to acknowledge that the science and technology behind the cognitive clinical machine can be complex. It’s tough to keep up with all the terminology and sciences that get lumped together and conflated—artificial intelligence, machine learning, cognitive science, deep learning, big data, predictive analytics. And what does it all mean to you in your mission to deliver excellent care?
So let’s simplify. Start with a machine, a physical box that plugs right into your healthcare and data environment. This elegant, sophisticated machine acts as a “brain” that understands and continuously learns from the clinical and cultural data of all of your patients. It uses that knowledge to guide clinicians in the best decisions for optimum patient outcomes.
There are many unique advantages of this Cognitive Clinical Success Machine for healthcare:
- Plug-and-play technology
- Immediate delivery of insights
- Answers the question of who is at risk and what clinicians should do, all with machine precision
- Overcomes the persistent problems of predictive analytics. (See more here about the limitations of predictive analytics in the context of polls and politics.)
- Simplicity and fast deployment encourages enthusiastic adoption
- The foundations for clinical decisions that enhance both patient experience and care quality
The cognitive machine facilitates unprecedented speed to knowledge and value. The pre-tuned, pre-tested, pre-wired machine plugs right in. It takes only weeks to calibrate to the local patient population and develop the patient profiles that provide total insight. Then it turns information into value right away, improving patient care and experience as well as business impact.
The machine also provides a comprehensive and increasingly intelligent understanding of patients and the right clinical choices for quality outcomes. This high-definition patient “biography” comprises the factors that influence risk and intervention effectiveness now and over time. The machine embodies events such as risk of hospitalization, length of stay, and patient deterioration as clinical success “vectors.” Each vector determines risk, contributing factors, and the broad and specific actions that will drive the best outcomes.
“The JVION machine for us was really just like plugging in a standalone appliance and it worked immediately,” said Ben McKeeby, CIO of Grady Health System in Atlanta. “We fed it data and very quickly we were receiving [patient risk propensities] back. The whole process was extremely seamless for us.”