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WHITE PAPER

Leveraging AI to Streamline Access, Capacity, and Patient Engagement

Learn how a large health system’s ongoing partnership with Care Continuity consists of leveraging artificial intelligence and machine learning to streamline patient engagement and mitigate capacity constraints across 15 hospitals and clinics.

Learn how AI and machine learning can: 

– Accurately prioritize patients most in need of navigation and most likely to accept assistance

– Streamline navigation to connect with patients in their preferred method to maximize outcome and minimize workload

– Provide data and analytics that can give valuable insights into your network dynamics

– And more

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How Specialty Referral Optimization Works

Patient Navigation Powered by Machine Learning 

Care Continuity’s Specialty Referral Optimization patient navigation solution leverages machine learning to prioritize patients for navigation based on their clinical needs and characteristics, as well as your program goals and network dynamics.

When a patient receives a specialist referral from their PCP, they enter the Navigator Predict pool. Navigator Predict ingests information from the triggering encounter, including patient engagement and clinical history, and details of your provider network dynamics. These details are combined with over 50 weighted navigation variables. 

These datapoints make up what results in hundreds of machine learning models that are ran against your patient cohort to find the most optimal navigational outcome for your patients and your health system. 

Navigator Predict assigns a Navigation Score to each patient receiving a referral, rating them on a scale of 0.01 to 1.00. The closer the score gets to 1.00 the more in need the patient is for navigation and the more likely the patient is to accept the navigational assistance. 

While all patients who enter the Navigator Predict pool receive navigation, the prediction score allows for better prioritization and better program results for your health system.

Navigation 3.5x More Efficient Than Traditional Methods

This approach to Specialty Referral Optimization has allowed leading health systems to realize 3.5x better results than compared to traditional navigation methods. 

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The blue-dashed line above shows the trend line for traditional navigational efforts. For a health system to navigate 60% of their patients who are likely to accept the assistance (aka the “Yes” population), they would need to contact 60% of their entire patient pool, on average. 

With Care Continuity’s Specialty Referral Optimization module, a health system would only need to contact 22% of their patient pool in order to navigate 60% of their total “Yes” population. 

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Read About Care Continuity's Specialty Referral Optimization in Hospitalogy

“Care Continuity brings drastic efficiency to this identification process for its clients, increasing navigation results by 2.6x to 3.5x over baseline efforts. Their solution is ~3 times more efficient than what a typical health system, ACO, or health plan could do with its own in-house resources.

Simply put, Care Continuity has the data and expertise.”

Care Continuity delivers proven results, and fast.

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Challenge:

Improve post-discharge care plan compliance by managing appointments with multiple providers for at-risk patients

Navigator Solution Elements:

Predict Software, Staffed Concierges

Result:

Significant decrease in ED and inpatient readmissions within the first 30 days after discharge