Leverage machine learning to:

  • Reduce rehospitalizations with focused interventions

  • Increase census – identify at-risk patients early and treat in place

  • Better prioritize resources for patients most at risk for near-term decline

  • Improve quality of care and patient satisfaction

  • Strengthen preferred provider status with ACOs, BCPI providers and I-SNPs

Predict and rank which patients are at the highest risk so that you can take action

Demonstrated results:

  • 52% reduction in 30-day rehospitalization rates

  • 32.5% increase in resident days, year on year

How SAIVA’s system works:

01.

Train

Using 24-months of historical EHR data and then daily feeds, we optimize machine learning models for your specific facility and patient population.

02.

Identify

Two weeks later, patients are identified and ranked for those most at risk for hospitalization or decline. The Daily Risk Report is then delivered directly to the nurse’s inbox.

03.

Act

Based on the Daily Patient Risk Report the nurse investigates and triages.

04.

Improve

SAIVA customers realize reduced hospitalizations, improved outcomes, and increased census.

Better Resource Utilization

Operational Benefits

Clinical Benefits

Improve patient outcomes and quality of care at your organization

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