Interoperability in Healthcare: Better Outcomes with Connected Data

Interoperability in healthcare improves the quality of patient care. It moves beyond basic data sharing to improve patient outcomes, reduce costs, improve operational efficiency, and enhance the overall quality of care. But as simple as it sounds, technological and institutional barriers can make it difficult for healthcare professionals to share data across the healthcare ecosystem, ranging from pediatrics to government regulators. In this article, we’ll explore the benefits of interoperability in healthcare and how to solve common challenges to building out the data systems required to achieve interoperability.

What Is Interoperability in Healthcare?

Interoperability is the ability of different systems, devices, and applications to seamlessly communicate and exchange data. Interoperability in healthcare is achieved by creating a data sharing network that connects providers, payers, pharmacies, medical monitoring devices, and other relevant sources of patient health and organizational data. 

This network enables different healthcare providers to seamlessly access and share vital patient information in real time, regardless of the technology or cloud platforms each provider uses. Examples include an emergency room physician accessing a patient’s prescription information from their local pharmacy or a primary care doctor reviewing trend data gathered from a patient’s cellular-enabled blood pressure cuff. As healthcare organizations increase their reliance on technology to deliver high-quality care to patients, interoperability ensures that patient data is accurate, complete, up-to-date, and easily shareable.

Benefits of Interoperability in Healthcare

Making relevant patient health data instantly accessible enables high-quality clinical decision-making and improved care coordination. Achieving interoperability in healthcare provides numerous benefits for patients, providers, and payers.

Improved quality of care for patients

Broadened access to a patient’s complete health information improves clinical decision-making and the patient experience by creating a 360-degree view of patients (known as patient 360). This data may include current diagnoses, medications, treatment recommendations, lab tests, and historical data gathered from connected health devices. When this information is within easy reach, physicians can coordinate their treatment recommendations with those of other providers, avoid duplicate tests, and ensure the medications they prescribe will not interact with the patient’s current prescriptions. And, patients no longer have to repeat their medical history at each appointment.

Better operational efficiency 

Seamless data sharing in healthcare can also unlock insights to help departments across the organization operate more efficiently. One example of this is healthcare analytics that organizations can use to provide more responsive customer service, reduce patient no-shows, streamline supply chains, and eliminate inefficiencies in physician scheduling.  

Enables data-driven healthcare

Data sharing in healthcare reduces the administrative burden on doctors, nurses, and support staff. It also helps administrators quickly identify offices and providers who consistently score low on patient satisfaction surveys to prioritize training initiatives designed to improve patient care. 

Four Levels of Healthcare Interoperability 

The Four Levels of Healthcare Interoperability is a helpful construct created by the Healthcare Information and Management Systems Society (HIMSS) Board. This multitiered system provides medical, administrative, data science, and IT personnel with a framework for assessing their current data exchange and document management capabilities. Each level represents an increasingly sophisticated degree of data exchange and integration between healthcare systems, ranging from very basic data exchange to the full integration of electronic health records (EHRs). 

1. Foundational

The foundational level lays the groundwork for healthcare interoperability. At this level, data information technology solutions are able to securely communicate and exchange data. Although they can send and receive data, these systems cannot interpret data independently and remain reliant on human assistance or other technologies for interpretation. 

2. Structural

Structural interoperability, also known as structured transport, enables limited interpretation capabilities by defining the format, syntax, and organization of medical information. This standardization allows document management systems to locate and interpret data recorded in predefined fields. Although this level supports some basic interpretation functions, barriers such non-standardized content in structured messages create obstacles to deeper levels of understanding.

3. Semantic 

Semantic interoperability, also called semantic transport, is the level of integration at which two separate systems can exchange, interpret, and use medical information, including medical terminologies, nomenclatures, and ontologies. At the semantic level, systems are able to comprehend the meanings of medical concepts including procedures, diagnosis, and lab results.

4. Organizational

The organizational level represents the most advanced stage of interoperability. Through the establishment of common processes and workflows, patient health data can be seamlessly shared and interpreted across a diverse range of healthcare organizations, entities, and individuals involved in providing healthcare and related services. 

4 Common Barriers to Improving Interoperability in Healthcare

Although interoperability in healthcare benefits patients, providers, and payers, there are significant hurdles in obtaining the safe and efficient exchange of patient health and organizational data. Technical, legal, and cultural factors can impede the delivery of high-quality care and lead to inefficiencies in healthcare delivery. Here are some of the most common barriers to achieving interoperability in healthcare and how they can be overcome.

Poor coordination

The customized electronic health records (EHR) used by many healthcare providers and systems make it difficult to convert patient data to a standard format that can be easily shared with others. In addition, these organizations are often faced with the challenge of siloed data. This data is stored in various systems, databases, and applications, making it cumbersome and time-consuming to effectively cross-reference data or build multidimensional dashboards. A modern cloud data platform can integrate this data and serve as a centralized repository that provides a clear 360-degree view of patients and healthcare organization operations. 

Lack of common data standards 

Although standard record formats like Fast Healthcare Interoperability Resources 1 (FHIR) and Health Level Seven (HL7) are the gold standard, numerous providers and healthcare systems still use EHR systems that make it difficult to convert data into an easily shareable standard format. Accelerating the transition to standard record formats is worth the resources required.

Poor data security and governance

Securing protected health information (PHI) is essential to the exchange of patient health data. Allowing healthcare professionals to access data without adequate security and strategic governance in place creates significant risk and can result in inaccurate insights. For this reason, organizations must have a reliable framework for managing data, ensuring quality, minimizing risk, and meeting data-focused regulatory compliance mandates such as HIPAA. Healthcare organizations must ensure their data platform and data management tools are built with sufficient data security features such as dynamic data masking and end-to-end encryption for data in transit and at rest. Organizations should seek vendors with certifications such as HITRUST, SOC 1 and 2 Type II, PCI DSS, and FedRAMP.  

Legacy data infrastructure

When data is integrated into a single platform, analysis becomes faster and much simpler. But because healthcare providers need to analyze massive amounts of information, storage capacity is not the only requirement. Sufficient compute power and efficient analytics tools are also necessary. A cloud data platform provides near-infinite scalable data storage and compute resources, allowing healthcare organizations the flexibility to access these resources on demand. 

Improve Interoperability in Healthcare with Snowflake

Snowflake helps healthcare organizations realize the promise of interoperability. The Snowflake Healthcare and Life Sciences Data Cloud enables data from multiple sources and systems to be integrated on a single, scalable platform. Sensitive data is stored securely with built-in security and governance that supports HIPAA, HITRUST, SOC 1 and 2 Type II, PCI DSS, and FedRAMP (medium) requirements. Today’s healthcare organizations now have the depth of insight, analytical power, and collaborative tools required to operate efficiently and deliver the best results for patients.