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Continuously Patient Analysis
Orb Health utilizes cutting edge AI and data science to enable a historical and predictive look at many dimensions of care. Our customer dashboards provide unique insight into how Enterprise Virtual Care is helping better service diverse patient populations.
Patient data from individual health systems, hospitals, clinics, and ACOs is actively analyzed, including the related care metadata, to determine where care can be improved. The results are fed back to the our customers and into the workflows and processes that supports them in our Virtual Care Cloud.
Orb Health’s AI Engine further examines cross-system, de-identified patient data to find more non-intuitive correlations between like and disparate data sets to help advance care across the spectrum. Data scientists can use Orb Health’s data to further their own study and help advance healthcare for all.
Predictive Analytics and Alerting Saves Emergency Department Visits and Hospitalizations
Patient intelligence that leverages predictive data science to drive significant improvement
Performance Dashboards
Customer focused dashboards that show the performance of Orb Health's Enterprise Virtual Care teams and the resulting outcomes.
AI-Driven Insight
Machine Learning and Neural Networking techniques are applied to patient data and care metadata in to provide deep insights into improving care and more
Secured Third-Party Enablement
Secured API enables third-party tools to allow customers access to appropriate data using data visualization tools, financials systems, and more
Retention Machine Learning
Machine Learning algorithms applied to the factors that drive patient retention and reporting these findings back to the program managers for use
Best Contact Profiling
Our predictive modeling looks at patient information and determines the best places to contact them, the best times to contact, as well as the best methods
Interaction Typing
Patient interaction analysis that determines the best way to service needs, meet expectations, and encourage care engagement
Auto Summary
Automated and audit-ready summation of interactions and metadata that provides a comprehensive record that is synced to the EMR
Predictive Alerting
Multi-factor patient stats used to predictively determine if a patient exacerbation likelihood and head it off through proactive engagement
Enrollment Timing
Studies the best timing and patterns among a patient population to shape outreach campaigns that will have the highest chance of enrolling patients
Financial Outcomes
Show financial impact of improved patient outcome and HCC scoring that directly affects reimbursements and value-based care performance
HCC Scoring Assistance
Algorithms automate annual and ongoing HCC scoring so systems deliver comprehensive care that maximizes reimbursements and outcomes
