Data integration involves the collection of data from multiple sources and the combination of this data into meaningful and valuable information. Healthcare data integration helps to improve the cost and quality of healthcare and to generate useful insights for patients and researchers. The process of data integration is made simple with the help of data integration tools that are designed according to data integration requirements. These tools are responsible for performing transformation, mapping, and cleansing of data.
Know anyone building innovative solutions that belong in this 'Data Integration'?
Translate various data sources into FHIR® for easy analysis
The complexity of healthcare organizations and their many care solutions makes interoperability a challenge for providers, payers, and others across the industry. Data liquidity is an urgent priority as access to electronic health records (EHR) and other data is mandated across a variety of use cases. Organizations who want to convert their data into FHIR® are often caught in the “build vs. buy” decision.
Redox provides a bi-directional data exchange that quickly connects provider networks, digital health products, and insurers to Amazon HealthLake. Watch this webinar to learn how Redox can help convert your healthcare data into FHIR, and how you can utilize Amazon HealthLake to store, transform, query, and analyze that data at scale.
In this webinar, you'll learn how to:
Understand the advantages of scaling integration as a service with Redox
Process and analyze data utilizing specialized machine learning (ML) models
Automate conversion of data into FHIR and leverage Amazon HealthLake for insights
Who should attend?
CTOs, CIOs, CISOs, VPs of IT C-Level or LOB Managers (CEO, CMO, COO, VPs, LOB Directors) Software Developers, Software Development Managers, System Architects.
Rhapsody is the enabler that brings systems together through seamless data integration. The proven, high-performing interoperability platform has built-in FHIR capabilities and is designed for robust …
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