Leveraging Data in Healthcare: Why It Matters

So much data, but is your organization using it to help members? 

Today's patients expect personalized and precise care, and data-driven decision-making is crucial for this. This can help, healthcare organizations improve care, streamline operations, and boost overall health outcomes. 

However, achieving seamless data integration while staying HIPAA-compliant and keeping data secure takes a lot of work. That's where RadiantGraph's Intelligent Personalization Platform comes in. It makes data integration easy, ensures HIPAA compliance, secures patient data, and delivers the personalized care patients expect.

Imagine having a complete view of  your members’ health, enabling proactive and personalized experiences. Sounds great, right? Our recently published case study shows how RadiantGraph helped our  client better connect with their audience through rich consumer profiles.

Understanding Data Silos in Healthcare

Data silos occur when vital healthcare information is scattered across various isolated systems or departments. This fragmentation creates several issues:

• Incomplete Medical Histories: Healthcare organizations may need more access to a patient's complete medical history, creating gaps in care.

• Inconsistent Data Formats: Different departments use varied data formats and standards, complicating data integration and analysis.

• Hindered AI Applications: Isolated data prevents effective use of AI, limiting informed decision-making and improved patient outcomes.

• Manual Processes: Consolidating and analyzing fragmented data manually is time-consuming and error-prone.

How RadiantGraph Breaks Down Data Silos

RadiantGraph's platform has powerful built-in capabilties that help tackle these challenges:

• Data Ingestion and Standardization: Our platform gathers data from multiple sources, like eligibility files, claims, and biometric data, and standardizes it for easy analysis while complying with HIPAA regulations.

• Identity Resolution: Our algorithms match data points from different sources to create a unified view of each patient, eliminating errors and duplicates.

• Data Enrichment: By incorporating Social Determinants of Health (SDOH) and other external data, RadiantGraph enriches existing data, providing deeper insights into patient needs and behaviors.

Real-World Success with RadiantGraph

One of our healthcare clients saw impressive results:

• 99.4% Match Rate: Our platform matched 99.4% of eligibles to corresponding SDOH signals, offering valuable insights for targeted patient engagement.

• 85.5% Reduction in Unknown Gender Labels: Our gender inference reduced "unknown/unclear" gender labels by 85.5%, enhancing patient profile accuracy.

• 31% Increase in Matched Medical Claims: Tie past medical claims and history to build a rich profile of the needs of every member and household.

• 51% Increase in Available Email Addresses: Enhanced digital communication with a 51% increase in available email addresses.

• 48% Reduction in Direct Mail Volume: By deduplicating across households, we cut direct mail volume by 48%, reducing costs and improving efficiency.

Conclusion

Data silos present significant challenges in healthcare, blocking access to valuable insights and powerful engagement challenges downstream. But with RadiantGraph's AI-powered solutions, advanced data integration and enrichment have become a reality, helping organizations unlock the full potential of their data, without any engineering or marketing work on their end.

If curious, check out our complete case study or request a personalized consultation. To read the detailed report along with insight from our client, click below to download the full case study.