Health Information Exchanges and Health Information Networks

Don’t let big data become a big problem

For Health Information Exchanges (HIEs) and Health Information Networks (HINs), the quality of incoming data is crucial. Why? Because most revenue sources (Health Plans and Provider Organization Memberships) rely on this data to be timely and accurate to enhance patient safety, reduce re-admission rates, provide deeper insights to social determinants of health (SDOH), and improve operational efficiency. 


Why HIEs and HINs fail 

  • Unreliable Master Patient Index (MPI) matching quality
  • Big data implementation complexities 
  • High costs 


What should you do? Start the conversation. 

We’re here to help. Submit your information on the form you see here to start the conversation. Our team will follow-up to schedule a one-on-one consultation. This is important to us. 

Poor data management processes can lead to an avalanche of poor results.​

The 4medica Data Quality Platform

Utilizing the industry’s most technologically advanced MPI process, 4medica has revolutionized how HIEs & HINs can analyze and implement big data. Our 4-layer approach simplifies implementation and guarantees dramatic success of <1% patient duplication.

Good quality data is the foundation for accurate healthcare reporting, and statistical analysis, it creates an atmosphere of trust where healthcare data is usable and provides value to participants and ultimately patients.
4medica’s HDQ Consulting will help you achieve this success by working with you and your data partners to bring on the best quality data possible. Our unique approach provides a customized approach to your data quality needs. We are more than just a software vendor; we are your HDQ partner and want to pursue this journey with you. 4medica has a proven track record of success all while taking a personalized approach.

4medica helps improve health data quality once and for all.

We Help Simplify Big Data

We provide a multi-tier, cloud-based data quality platform that integrates data from different sources and normalizes it to improve consistency, while also creating a global ID for patients that allows providers to match them to their data.

How is bad data quality impacting your organization? We can help you find out.