CMS Announces LEAD, the Next Evolution of ACO REACH. Read More >
X

ANALYTICS CAPABILITY GAP

Immediate Investment Required
for Competitive Parity

Limited analytics and real-time capabilities represent a critical competitive disadvantage in the current and future value-based care landscape. Without predictive analytics and real-time insights, you’re managing risk blindly – delayed data means care teams learn about critical events days or weeks too late to intervene effectively. Success in bundled payments, shared savings, and capitation requires these capabilities.

Begin immediately by assessing current data latency by source, query response times, and system performance during peak loads to establish baseline metrics.

Critical Next Steps

Prioritize 2-3 high-value real-time use cases (such as hospital admission alerts, ED visit notifications, or care gap identification at point of care) and reduce latency incrementally.

Increase batch frequency to every 6-8 hours, then implement micro-batch processing (hourly), then streaming. Deploy pre-built predictive models from vendors rather than building from scratch (on average 18-24 months faster).

Address scalability issues immediately and consider cloud migration for elastic scaling. Cedar Gate’s platform provides near-real-time streaming, 20+ healthcare-specific predictive models, and enterprise scalability out of the box, accelerating transformation from two or three years to as little as 6-12 months.

While a full transformation will take longer (18+ months), it’s critical to achieve at least these minimum capabilities in the coming months to remain competitive.

Compliance & Security

CMS & ONC
Our data is aligned with federal interoperability mandates, and our data vendor monitors new requirements to ensure future compliance.
FHIR
Our enterprise data management system supports HL7 FHIR APIs to exchange data with other healthcare organizations.
Security
Our data infrastructure is fully compliant with all HIPAA and HITRUST standards.
Scalability
Our security processes are built to scale seamlessly with rising data demands. Dynamic data masking applied to raw data — without manual intervention — strengthens protection while enabling rapid, secure scaling of analytics.

 

Your browser is out-of-date!

Update your browser to view this website correctly. Outdated Browser

×

Enter to View

Enter your Email to Access