United StatesHealthcare and life sciences2024 – ongoingSt. Luke's University Health Network
Epic Deterioration Index with virtual nurse response
St. Luke's reported 34% fewer cardiac arrests after pairing AI monitoring with virtual nurses
Problem
Hospital teams needed to detect worsening patient conditions before an unexpected ICU transfer or cardiac arrest. Continuous manual risk assessment across admitted patients was impractical.
Approach
St. Luke's used Epic's Deterioration Index in medical-surgical units across its campuses. The model processed clinical observations and nursing documentation. Virtual Response Center nurses used deterioration scores to alert bedside staff or rapid response teams.
Results
Takeaway
The reported results covered a care workflow combining predictive scores with nurse escalation. They did not isolate the model's contribution.
Categories
- Size
- Large enterprise
- Industry
- Healthcare and life sciences
- Business function
- Production and quality
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and ML
- Adoption
- Vendor solution
- Goal
- Quality and risk
- Evidence
- Company's own claim
Sources
Source summaries
St. Luke's described predictive monitoring linked to its virtual nursing response center. It reported fewer cardiac arrests and fewer rapid response ICU transfers over a multiyear initiative.
Full details are in the original sources.