Reduce Specialty Appointment Wait Times With Active Patient Navigation
Streamline appointment booking process for patients while load balancing office schedules.
Expertly crafted AI and machine learning that identifies and prioritizes patients most in need of navigation.
Experience measurable operational impacts and ROI within 120 days of program launch.
More than 2 million patients navigated for the nation's leading health systems.
Client Impact with Specialty Referral Optimization Patient Navigation
The Long Wait For Specialty Appointments
Across the United States, health systems in major metropolitan areas are facing shockingly long average wait times for specialty appointments. According to a study from ECG Management Consultants, on average, patients are waiting over a month for an appointment in most specialties, with some stretching to beyond two months. In some cases, appointments wait times are stretching beyond 100 days, going as long as 186 days (gastroenterology in Boston).
Of the 253 metro area and specialty combinations, there were only 16 that had a wait time of 14 days or less.
These long wait times to see a specialist is a symptom of fast growing cities and shrinking numbers of physicians, making managing specialty referrals more challenging than ever for health systems.
Care Continuity’s Specialty Referral Optimization patient navigation solution is powered by AI and machine learning, making it easier for providers to manage their specialty referrals and has seen, on average, a 20% reduction to specialty wait times.
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.
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.
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.
- National health system with multiple advanced specialty networks
Challenge:
Improve post-discharge care plan compliance by managing appointments with multiple providers for at-risk patients
Navigator Solution Elements:
Predict Software, Staffed Concierges
Significant decrease in ED and inpatient readmissions within the first 30 days after discharge
