Interoperable Data: A Prescription for Better Health Outcomes

Updated on October 8, 2024
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U.S. healthcare costs rose by 4.1% in 2022, topping $4.5 trillion. That’s an average of $13,493 per person, which amounts to 17.3% of our national gross domestic product and it’s driven in large part by a fee-for-service healthcare system that relies entirely on volume. But there are promising trends that can drive down costs – namely, the transition to value-based care (VBC) models that incentivize outcomes over care volume. 

While value-based care has proven effective at reducing costs and maintaining high-quality care, the transition has been slow. One common challenge holding many payers, providers, and employers back from engaging in value-based care is the issue of data interoperability. Value-based care requires a high level of collaboration among all healthcare stakeholders. It emphasizes prevention, population health, and collaboration across the healthcare ecosystem, all of which rely on seamless data exchange. Our current data environment – with its fragmented, disjointed systems – makes that difficult. 

The Ongoing Interoperability Challenge

Data interoperability is a critical component for the success of VBC. Unfortunately, healthcare has proliferated in a system of fragmented data systems. Payers and providers operate on outdated systems that fail to communicate effectively, compounding issues such as:

  • Limited visibility into external data: Healthcare organizations often use data management systems that don’t seamlessly exchange information with external systems. Even when they can pull in external data, the information is often in a format that is unreadable, and thus useless for advanced analysis that could lead to lower costs or better care.
  • Inefficient collaboration between payers and providers: Disparate systems and data formats create silos, with payers often working from a different dataset (claims data) than providers (EHR data). Value-based care requires a preventive approach, with the capability to predict patient and member needs and address those efficiently. Payers and providers need to work from the same set of comprehensive claims and EHR data to create cohorts based on member needs, stratify risk, build workflows that address care gaps, and get effective clinical decision support at the point of care.
  • Patient frustration and engagement issues: Patients navigating disconnected systems often experience a lack of transparency and coordination in their care, causing frustration and reducing engagement and satisfaction with their healthcare providers.
  • Technological alignment barriers: Many payer and provider organizations operate in a tech environment with multiple point solutions to address various member needs, requiring complex APIs to connect systems. This increases the risk of data breaches or HIPAA violations, delays in data exchange, and operational inefficiencies. 

A Foundation for Success: Enterprise Data Management

To overcome these challenges, healthcare organizations must adopt enterprise data management systems with enhanced interoperability capabilities. Ultimately these platforms must have the capability to efficiently compile and standardize data from multiple sources. When they can effectively align data across the healthcare ecosystem, it offers several key benefits:

  • Unified data sources: The most advanced enterprise data management systems available today can pull data from disparate sources, including EHRs, claims data, and social determinants of health, into a comprehensive dataset by ingesting, cleaning, and enriching the data.
  • AI-driven decision support: This unified data can be connected to individual members, enabling seamless analytics, care management workflows, and payment. This allows more informed, real-time decision-making across the care continuum.
  • Simplified tech stacks: A simplified, centralized data management approach removes barriers to patient-provider collaboration, ensuring that everyone has access to the information that supports optimal care decisions.

VBC’s Data-Driven Edge

Technological alignment is critical for healthcare organizations as they navigate the complexities of VBC and alternative payment models that move us away from fee-for-service. Integrating and managing data seamlessly improves operational efficiency and enhances care quality and patient outcomes.

As the industry evolves, embracing these technologies will be essential for overcoming the data interoperability challenges that have long hindered healthcare stakeholders. The result is a more coordinated, patient-centered approach to care that drives better outcomes and reduces costs, and helps patients be more active participants in their health journey.

AshayThakur copy
Ashay Thakur
VP of Data Strategy at Cedar Gate Technologies

Ashay Thakur is the VP of Data Strategy at Cedar Gate Technologies. He oversees strategic development and governance of the organization's data foundation, driving innovation to enhance scalability, quality, and excellence across Cedar Gate's end-to-end value-based care platform.