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Points of Light 2025 Case Study 4
Utilizing Near Real-Time Data from Payer HIEs to Identify Qualifying Events & Close Time-Sensitive Care Gaps
Author
Boyd Stewart
Author
Aurene Wilford
Providing timely post-discharge care to at-risk patients is a national challenge. Due to lags in claims processing, clinicians often struggle to identify recently discharged patients and schedule needed follow-up visits within the limited time frame required by HEDIS. This challenge can result in suboptimal care, costly readmissions, and avoidable acute care episodes. Working with InterSystems’ interoperability tools, Healthfirst—a provider-sponsored health plan—began leveraging clinical data from near real-time HIE feeds to identify members experiencing a qualifying event for a time-sensitive HEDIS measure. The tools then send automated alerts to clinicians so they have sufficient time to schedule follow-up care. Additionally, Healthcare Organizations 4-1 and 4-2 worked with Healthfirst to refine workflows and processes to enable quick action on the alerts. Outcomes include improved performance with targeted HEDIS measures and a reduced administrative burden.
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Key Findings:
- Executive Summary
- The Collaborators
- Points of Friction—Challenges to Be Solved
- Action Plan—How the Collaborators Worked Together to Reduce Friction
- Points of Light—Outcomes Achieved Through Collaboration
- Lessons Learned—What Best Practices Can Other Organizations Replicate?
- What's Next?—Vision for the Future
Writer
Natalie Hopkins
Designer
Jess Wallace-Simpson
Project Manager
Joel Sanchez
This material is copyrighted. Any organization gaining unauthorized access to this report will be liable to compensate KLAS for the full retail price. Please see the KLAS DATA USE POLICY for information regarding use of this report. © 2025 KLAS Research, LLC. All Rights Reserved. NOTE: Performance scores may change significantly when including newly interviewed provider organizations, especially when added to a smaller sample size like in emerging markets with a small number of live clients. The findings presented are not meant to be conclusive data for an entire client base.