Interoperability: How to Measure Data Interoperability and Communication Across Health Systems

Data interoperability

Rapid technological changes to the infrastructure that supports medical data represents a historic opportunity for the health industry to understand and optimize digital health transformation. Its goal: realize the power of interconnected systems to focus on the needs of individual patients.

To achieve this outcome, each interconnected component of a healthcare ecosystem (governance and workforce, interoperability, predictive analytics, and person-enabled health) must align with and enable every other component.

Ensuring that each component achieves its potential requires that outcomes for each are measured in a standardized, repeatable way. In the second of a four-part series, we consider the elements that must be measured to verify the effectiveness of interoperability.

Advancing Interoperability

As digital devices and the infrastructures that support them have grown more sophisticated, so has data interoperability among information systems, devices and applications in healthcare organizations.

While analog patient records and other data were limited in their scope and physically scattered, digital transformation allows clinicians and their organizations to access, exchange, integrate and cooperatively use data dynamically. To optimize patient outcomes, data may cross organizational, regional and national boundaries.

Data interoperability requires increasingly sophisticated data exchange architectures, application interfaces and standards. These provide the data tools necessary to access and share information appropriately and securely across the complete spectrum of care, within all applicable settings and with relevant stakeholders, including individuals.

These capabilities comprise interoperability, which HIMSS measures within the following parameters:

  1. Foundational interoperability, which describes interconnectivity requirements for one system or application to securely communicate data to, and receive data from, another. HIMSS defines it as data exchange at the individual level that is accessible across clinical, social and community institutions. Foundational features include data and information capture, data storage and management capacities, access to data that informs communication between individuals and clinicians, teams and organizations, speed of multimedia exchange over physical networks and wireless connections, and virtual/remote information exchange.
  2. Structural interoperability, which describes the format, syntax and organization of data exchanges from the data field level. Structural interoperability measures levels of data integrity across systems as well as automated flow of data and information across multiple, heterogeneous sources. It also takes into account the performance of data reporting and access functions, the structure of data centers, and rates of information exchange across multiple, varied platforms.
  3. Semantic interoperability, which establishes common models and codification of data that are mutually intelligible to users. These parameters include employing standardized definitions of data elements, using publicly available value sets and coding vocabularies.
  4. Organizational interoperability, which includes governance, policy and social, legal and organizational considerations. The objective of organizational interoperability is to facilitate the secure, seamless and timely communication and use of data within and between organizations, entities and individuals. It enables shared consent and trust as well as integrated processes and workflows for end users. In operation, it ensures secure access to individual-level data, identity and access management, centralized authentication, firewall integration, web and email security, and cloud orchestration and coordination (both private and public cloud infrastructure). Organizational indicators also address quality of service and experience for users.

Benefits of Measuring Interoperability

Assessed via standardized performance metrics, interoperability is the key to unity among disparate specialties and functions within and across healthcare organizations.

Simply put, validated interoperability ensures all relevant data is focused on patient needs. Combined with the other three components of the healthcare ecosystem, it gauges organizational effectiveness in providing optimal outcomes for the patients it serves.

The next post in our series on measuring digital health transformation will explore predictive analytics.

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