Health First Leverages Eigen-based Cognitive Machine Capability to improve lives in Central Florida
Health First - Central Florida's largest fully integrated delivery network-combined the leading Cognitive Clinical Success Machine with a focused, comprehensive program to reduce readmissions. Within less than three months, the system realized more than $895,000 in savings and significantly reduced readmissions for some of the community's most vulnerable and at-risk patients.
The Full Story:
Health First serves Central Florida and is the region's only fully integrated delivery network. The system comprises four hospitals, multiple outpatient and wellness services, and a payor arm that includes commercial and Medicare health plans. They are distinguished by a community-minded approach to care that focuses on local control and a sharp attention to community needs.
Like the other almost 1,560 hospitals facing readmission penalties over the next year, Health First is encouraging health promotion and wellness to reduce readmission rates. The system is implementing a prevention of disease progression program through individualized patient education. In an empowering approach, Health First leadership is taking a progressive stance against hospital readmissions. It is one that combines leading edge cognitive science technology with a comprehensive support structure to create a positive outcome.
Putting the Patient First
Health First chose Jvion's Cognitive Clinical Success Machine because the solution delivers individualized recommendations and patient risk. It out-predicts common approaches to readmission risk stratification like LACE and PLACE by delivering ten times more accurate views into patient predispositions, risk manifestations, and specific actions and interventions. This capability is enabled by and Eigen-based engine capable of making more than a quadrillion clinical and non-clinical considerations and thousands of data elements. To this data, more than 150 thousand self-learning Eigen Spheres are applied for each patient in real time. Where current tools fail because they are static and assign risk broadly, Jvion's Cognitive Clinical Success Machine excels because the tool is equipped with the power to drive individualized high-definition views into a patient's future that are more precise, comprehensive, and lead to more actionable interventions. The machine supports clinical decisions, helps drive engagement, and more effectively reduces risk across the entire care continuum.
Health First leadership integrated Jvion's Cognitive Clinical Success Machine into a comprehensive workflow designed to use the recommended actions and address the factors leading to an increased risk of readmission. There are two major stakeholder groups that consume the machine's outputs:
- Transitional Care Navigators: who work for the health plan and use the machine to identify at-risk patients once they are admitted into the hospital
- Inpatient Case Managers: who work with the transitional care navigators to make sure that recommended interventions are applied to at-risk patients
- Care Navigation Specialist: who make initial post discharge contact with patients to ensure support and care needs are met
- Central Care Navigation (CCN) Case Managers: who continue to follow discharge patients for 30 days to identify challenges and provide solutions in ensuring disease management and education telephonically
Interventions start once a person enters the hospital and is flagged at-risk by the Cognitive Clinical Success Machine. Transitional care navigators visit the at-risk patients to discuss the events that lead to hospital readmission. Through a Comprehensive Assessment, the Transitional Care Navigator can identify transitional care needs to ensure a smooth transition home. This list of at-risk patients is transitioned to the inpatient case managers who deliver care and interventions across a patient's stay. While an at-risk patient is in the hospital, transitional care navigators continue to monitor and document interventions into the cognitive engine. At discharge, an updated list of at-risk patients is pulled and communicated to the care navigation specialists who perform initial discharge calls and then refer patients to CCN Case Managers for continued monitoring.
The post-discharge program at Health First is one of the most comprehensive in the nation. This team works together to make sure that every risk, every need, and every question is addressed to improve care and reduce the likelihood of a readmission. Within 24 hours of leaving the hospital, a Care Navigation Specialist contacts the patient. They act as the first line of defense against patient deterioration. This team ensures that prescriptions are filled, follow up appointments have been made, and that outstanding needs - from financial to social - are addressed.
CCN Case Managers then monitor at risk individuals for 30 days or longer based on patient-centered outcomes. These highly trained registered nurses focus on health promotion, which encompasses disease management and education. Case managers assess a patient's readiness to change. Nurses facilitate and support patients to implement lifestyle modifications through empowerment with an individualized disease management plan. The CCN team strives to ensure that all patients understand their risk factors, what they can do to stay healthy, and how to prevent hospital readmissions.
Reduced Readmissions and Improved Health
In the just three months since going live with the entire program, Health First as an Integrated Delivery Network has avoided more than $895,000 in costs and saved more than 443 length of stay days. These results are in large part enabled by the ability to correctly identify the patients at-risk of readmission so that interventions and resources can be better targeted and applied.
Based on current results, there is a drive to increase adoption of the cognitive solution to further reduce patient risk and extend the value of the system. But the underlying capabilities of the machine-learning platform bring with them another inherent capability that will increase potential returns regardless of end user adoption. The machine learning capabilities within Jvion's Cognitive Clinical Success Machine get "smarter" with every new bit of data that is fed into the solution. This means that the longer the machine stays in place, the more accurate it becomes. Even if Health First maintains the current end user group, the increased accuracy and capability delivered by the cognitive machine over time will continuously deliver better and more high-definition views into the at-risk population.
Beyond hard numbers, Health First is realizing other benefits from their readmission program. By knowing who is at risk, Health First can better allocate resources-people, programs, and tools-to support those with the greatest needs. Jvion's Cognitive Clinical Success Machine is also able to take the intervention information entered during a patient's stay and use it to provide recommendations into which patients will benefit most from which interventions. This information is being used to increase patient engagement and drive better intervention effectiveness. And the improved outcomes driven by the program are translating into greater patient and caregiver satisfaction. Overall, by reducing readmissions and increasing efficiency, Health First is decreasing waste, lowering cost, and avoiding potential penalties while improving the health outcomes of their patient population.