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Large health system transforms data for better outcomes and efficiency

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Background

Having clear, actionable data is vital for health systems to thrive in today’s environment — but data silos, accessibility issues and the sheer volume of information can make effective data management a challenge for even the most sophisticated health systems. To tackle these issues and modernize their data infrastructure, a national healthcare provider headquartered in the southeastern United States embarked on a cloud transformation journey with Google Health Data Engine (HDE). Along the way, they consolidated data sources, migrated siloed data to one consolidated data store, and created centralized, longitudinal patient views that supported care variation reduction, national quality program initiatives, improved data analytics, and insight generation.

Challenge

Complexities of integration and standardization

The provider was dealing with the challenge of handling a vast amount of data generated from various sources. This data, if properly managed and analyzed, could provide invaluable insights into patient care, quality measures, and healthcare service efficiency. However, the existing data management system was not equipped to handle this volume of data or provide the necessary insights.

They began a cloud transformation project with Google HDE to address these and other issues. Initial objectives of the large-scale project were:

  • Populate Google Health Data Engine (HDE) with hospital Electronic Health Record (EHR) HL7 v2x ADT data with standardized data to perform analysis. This required:
    • Defining a unique enterprise patient id for each patient
    • Standardizing the data across multiple applications
  • Ingesting data in the Fast Healthcare Interoperability Resources (FHIR) format
  • Normalize and standardize daily batched data from 60 subacute hospitals for care variation improvement and national quality program measures into health catalyst analytical platform
  • Handle the complexity of 10 different EHR applications

“One of the things for care variation that we wanted to obtain is to decrease our mortality. We’ve successfully been able to do it with the data migration strategy that we’ve had....So truly having the right data migration strategy does make a difference.”

AVP IT Clinical Analytics

Solution

Adopting solutions for seamless data integration

The provider adopted the Verato hMDM™ platform and Clinical Architecture solutions to support their Big Data Strategy for migrating to Google HDE. These integrated platforms offered a comprehensive solution tailored to their needs for resolving, standardizing, and managing vast amounts of data in preparation for cloud migration. The Verato hMDM platform delivered a robust healthcare master data management (hMDM) solution, defining unique person IDs while ensuring data completeness and quality. Meanwhile, the Clinical Architecture solutions provided advanced capabilities for clinical data normalization and decision support.

In choosing partners for the project, the provider focused on critical capabilities and characteristics, including:

  • Dynamic, cloud-native solutions that would grow with them and seamlessly support the current project as well as future use cases
  • Highest levels of accuracy for patient matching and identity data management, to support their complex and fragmented ecosystem of data sources
  • Proven solutions with a track record at respected and complex healthcare organizations like theirs, with references from trusted peers
  • Data security specifically for healthcare and able to pass a rigorous risk assessment

Results

Achieving improved patient outcomes and efficiency

With the implementation of Verato and Clinical Architecture solutions, this provider was able to:

  • Generate insights to decrease mortality rates: The new big data architecture enabled them to effectively analyze large sets of patient data and identify patterns that could help decrease mortality rates, saving 41 lives to date.
  • Decrease care variation: The strategy enabled the organization to decrease variation and improve the outcomes of its care processes, thereby enhancing the value delivered to patients and increasing efficiency.
  • Lay the foundation for future digital applications: The big data platform lays the foundation for future digital applications such as patient marketing campaigns, clinical decision support systems, and mobile patient engagement applications.
  • Achieve a 360-degree view for each patient: Developed a comprehensive profile for each individual using fragmented information gathered from dozens of siloed systems.
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