Quick Overview
Valley Medical Center empowered care managers with AI-driven clinical merit analysis using Xsolis’ Dragonfly platform to guide patient status decisions, shifting from manual, inconsistent processes to data-driven clinical decisions embedded in EMR workflows.
Valley Medical Center
Company Size
Not publicly disclosed
Revenue Range
Not publicly disclosed
Primary Challenge
Improving case review accuracy and observation rates for discharged patients
Key Metrics
\- Case reviews increased from 60% to 100%\- Observation rate of discharged patients rose from 4% to 13%\- Extended observation improved by 25%
The Problem
Manual patient status determinations were inconsistent and inefficient
The Solution
Implemented Dragonfly Utilize AI platform integrated with EMR to provide clinical necessity scores and risk stratification, enabling timely, accurate patient status decisions
Results
\- More efficient workflows\- Accurate patient status determinations\- Staff reallocation and improved job satisfaction
“Our nurses were relieved they no longer had to go down the guideline path... They were empowered to look at clinical merit.”
Kim Petram, Director of Care Management
Details
Industry
Healthcare & Medical
Departments
Data & Analytics
Use Cases
Client Health Monitoring
Tags
Predictive Modeling
Machine Learning
Improved Accuracy
Enhanced Decision-Making
AI Tools Used
No items found.
Sources
https://www.xsolis.com/case-study/valley-medical-center/https://www.vktr.com/ai-disruption/5-ai-case-studies-in-health-care/
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