What is Healthcare Data Interoperability?

Healthcare Data Interoperability is when data can be freely exchanged between two or more systems and used by various stakeholders for easier access to health information. Healthcare management systems (HMS) and electronic health records (EHRs) work together as a single integrated unit to seamlessly share and interpret health data. The data can be accessed by similar systems in outside facilities, making the Continuum of Care accessible throughout and across different hospitals, pharmacies, insurers, and clinics. Patients become more engaged in their treatment plans, and providers can leverage large amounts of health data to create care plans that consider all aspects of a patient's medical journey.

According to the Healthcare Information and Management Systems Society (HIMSS), interoperability means "the ability of health information systems to work together within and across organizational boundaries to advance the effective delivery of healthcare for individuals and communities."

Interoperability modernizes systems communications for better and quicker access to patient files across multiple healthcare facilities by using a common language. Hospitals, labs, and patients can easily share data according to content standards that guide data exchanges and transport standards that guide health information formats. Health information exchanges are made secure with the Health Insurance Portability and Accountability Act (HIPAA) guidance.

How Does Healthcare Data Interoperability Work?

FHIR (Fast Healthcare Interoperability Resources) facilitates Healthcare Data Interoperability, which provides common data structures that one or more healthcare systems use to transmit data to external systems. Data is standardized to be understood across different information systems, providing a unified environment for multipart data exchanges. Data becomes easily accessible across multiple healthcare systems.

FHIR can also use APIs to enhance the connection between two separate healthcare systems, making data exchanges smoother through commands from a standard interface.

Four Levels of Healthcare Interoperability

Health data must be accessed, shared, and secured across the care continuum, within the correct application settings, and with appropriate stakeholders. The health data exchange architectures and application interfaces perform the following functions:

Foundational – Establishes interconnected channels where data can flow to and from two or more health systems.
Structural – Defines the format of data exchange at the data field level.
Semantic – Provides codification of data and leverages data in a standardized way as systems share information. Multiple systems can exchange data and use it across disparate systems.
Organizational - Includes organizational facets to enable secure communication. The data is used both within and between organizations. This process allows for shared consent and cohesive workflows.

Why is Healthcare Data Interoperability Important?

Healthcare IT will continue to evolve with the changing demands of systems operations and data accessibility. Today, the number of connected healthcare systems is ever-increasing. Hospitals have multiple systems and user-operated medical devices that need to connect, exchange, and store data using common standards.

There is growing demand to overcome the fragmentation of various healthcare technologies to improve the utilization of clinical data and increase operational efficiencies.

Healthcare data interoperability removes complexities and manual steps, helping format and organize information to reach the correct access point to help providers make quick and accurate decisions.

Healthcare Data Interoperability can benefit healthcare organizations in the following ways:

Quality of Care – This allows for integrated healthcare IT system for full access to patient data for the healthcare organization and the patient. A patient's medical history from multiple clinics and hospitals is accessible through one portal, giving providers a full spectrum of procedures and past symptoms. This helps with better diagnostics and preventive care plans.
Personalized Care - Systems that allow for population-level data analysis can use social determinants of a patient's health data to identify possible health risks. This enables healthcare organizations to build care plans that proactively mitigate factors that lead to adverse outcomes.
Efficiency – Health data is easily accessible, diminishes paperwork, and decreases repetitive tasks with the help of real-time results. Providers have precise health information at their fingertips, allowing them to create treatment plans that correlate to patients' historical and current medical issues and needs.
Reduced Costs – Standardized data formats can be automated for the electronic exchange of patient data, reducing the need for manual effort. This helps lower costs associated with reworks to medical information.

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