Moving beyond the buzzword to understand what seamless data exchange really requires
Interoperability in healthcare is the ability of different information systems, devices, and applications to exchange and use patient data seamlessly — within and across organisational boundaries — to support timely, coordinated, and effective care. True interoperability goes beyond technical connectivity: it requires standardised data formats, shared terminology, robust governance, and clinical workflows designed to use the data that becomes available.
In this article, you will understand what interoperability in healthcare actually means in practice — and what it takes to achieve it.
- The definition of interoperability and its four distinct levels
- The real barriers: data silos, legacy systems, and fragmented standards
- What true interoperability looks like in clinical and operational practice
- The standards enabling it — FHIR, HL7, and API-based integration
- The concrete benefits for patient care and operational efficiency
What Is Interoperability in Healthcare?
Definition and Types
Interoperability in healthcare refers to the capacity of different health information systems — electronic health records, laboratory platforms, imaging systems, pharmacy systems, wearable devices, and patient-facing applications — to exchange and use clinical data in a coordinated, meaningful, and secure way. It is not simply about technical connectivity. Two systems can be technically connected and still fail to achieve interoperability if the data they exchange is in incompatible formats, uses inconsistent terminology, or cannot be meaningfully interpreted by the receiving system without manual intervention.
Healthcare interoperability is commonly described at four levels. Foundational interoperability establishes the basic technical connection between systems — data can flow from one to another, but the receiving system may not understand its structure. Structural interoperability defines consistent data formats and message structures — HL7 v2 messages, FHIR resources, CDA documents — so that the receiving system can parse and store what it receives. Semantic interoperability ensures that the meaning of the data is preserved across systems: a diagnosis coded as SNOMED-CT in one system is understood correctly by another that uses ICD-10, because the terminology mapping has been applied. Organisational interoperability addresses the governance, policy, trust, and workflow dimensions that allow data to be shared not only technically but practically — across institutions with different ownership, legal frameworks, and operational processes.
True interoperability operates at all four levels simultaneously. A system that achieves foundational and structural interoperability but not semantic interoperability delivers data that must be manually reviewed and re-coded before it can be acted upon. Murphi’s EHR integration platform is built to address all four levels — ensuring that data exchanged between connected systems is not only transmitted but understood and usable at the point of care.
Why It Matters
The fragmentation of patient data across disconnected systems is one of the most significant structural problems in healthcare. A patient receiving care from a primary care physician, a specialist, a hospital, and a pharmacy may have their clinical information stored in four or more separate, incompatible systems — none of which automatically shares data with the others. The consequences are well documented: duplicate testing, medication errors from incomplete medication lists, delayed diagnoses from unavailable prior results, avoidable hospital admissions, and the administrative burden of manual data management that consumes clinician time and drives burnout.
Interoperability is the infrastructure-level solution to this fragmentation. When clinical data flows automatically and accurately between all the systems involved in a patient’s care, every clinician has the complete, current information they need to make the best possible decision — without phone calls, faxes, or manual record requests. The value is not theoretical: it is measured in time saved, errors prevented, care decisions improved, and costs avoided.
Current Challenges in Interoperability
Data Silos
Data silos are the dominant structural barrier to interoperability in healthcare. Each care setting — the hospital, the specialist clinic, the general practice, the pharmacy, the social care provider — maintains its own separate patient record system, typically purchased from a different vendor, built on a different data model, and with no obligation or incentive to share data with other institutions. The patient’s clinical history is scattered across these silos in incompatible formats, accessible only to the institution that holds it.
The consequences extend beyond inconvenience. When a patient presents at an emergency department, the treating clinician may have no access to that patient’s primary care record, specialist notes, or medication history — forcing clinical decisions based on incomplete information. When a patient is referred between providers, the referral letter contains only what the referring clinician chose to include, filtered through the limitations of manual summarisation, rather than the full structured record that an interoperable system would transmit automatically.
Addressing data silos requires both technical and governance solutions. Technically, it requires integrating previously disconnected systems through standards-based interfaces. From a governance perspective, it requires establishing the trust frameworks, data sharing agreements, and consent management processes that allow data to cross institutional boundaries legally and safely.
Legacy Systems
The majority of healthcare institutions run clinical systems that were not designed with modern interoperability in mind. Legacy EHRs, laboratory information systems built in the 1990s, radiology systems with proprietary data formats, and practice management platforms with no external API — these are the reality of the healthcare technology landscape in most countries. They communicate, if at all, through HL7 v2 messaging: a standard that is robust and widely deployed but which predates the web API era, lacks native support for modern interoperability patterns, and requires specialised interface engines to manage.
Replacing legacy systems entirely is rarely feasible — it is expensive, disruptive, and time-consuming, and the clinical risk of migrating to a new system in a live healthcare environment is significant. The practical solution is integration: building a standards-based interoperability layer on top of existing systems that translates their proprietary data formats into FHIR or HL7 v2 messages that can be exchanged with other systems, without requiring the source system to change. This is the approach that pragmatic healthcare interoperability solutions — including Murphi — are built around.
Our blog on HL7 integration explains how legacy HL7 v2 systems can be connected to modern interoperability infrastructure without replacing the underlying platforms.
What True Interoperability in Healthcare Looks Like
Seamless Data Exchange
True interoperability is invisible to the clinician. When it is working correctly, the clinician does not notice it — they simply have the information they need, presented in their primary workflow, without having to request it, wait for it, or find it elsewhere. A GP sees a discharge summary from last week’s hospitalisation automatically updated in their patient record. A specialist receives a structured referral with the patient’s complete problem list, medication list, and relevant investigations pre-populated. A pharmacist’s system automatically flags a potential interaction with a medication prescribed by a different provider at a different institution.
This level of seamless data exchange requires that every connected system is both a sender and a receiver of interoperable data — contributing its clinical information to the shared record and consuming information from other contributors. It requires standardised data formats so that data generated in one system’s proprietary format is automatically translated into a form that all other systems can interpret. And it requires continuous, event-driven exchange — not batch transfers or manual requests — so that the information available at any moment reflects the current state of the patient’s care.
Real-Time Access to Patient Data
Real-time data access is one of the defining characteristics of true interoperability, and one of the most significant departures from the historical norm. In a fragmented, silo-based healthcare system, data is typically available only to the institution that generated it, accessible only when requested, and often delivered with a delay of hours to days. In a truly interoperable system, a clinician can query a FHIR API and receive the patient’s current medication list, recent lab results, active diagnoses, and care plan within seconds — regardless of which systems hold that information or which organisations generated it.
Real-time access changes clinical decision-making. A physician prescribing a medication who can immediately see all of the patient’s current medications — not just the ones prescribed within their own system — can avoid interactions that an isolated view would have missed. A triage nurse who can see the patient’s last three hospital admissions, documented across two different health systems, can make a more accurate acuity assessment. The clinical value of interoperability is inseparable from its timeliness.
Standards Enabling Interoperability
FHIR and HL7
The technical foundation of modern healthcare interoperability is HL7 FHIR — Fast Healthcare Interoperability Resources. FHIR defines a set of resources — Patient, Observation, Medication, Encounter, Condition, and over 150 others — each with a standardised schema and a RESTful API interface. Any system that implements FHIR can exchange data with any other FHIR-compliant system, using standard HTTP requests, in JSON or XML format, without proprietary integration software. FHIR is mandated by the ONC and CMS in the United States for patient data access, and is rapidly becoming the global default for new healthcare system integrations.
HL7 v2, while a legacy standard, remains the dominant protocol for internal clinical messaging in most hospitals globally — handling lab results, admissions, orders, and pharmacy events through structured text messages. Both standards are relevant and often complementary: HL7 v2 for within-institution messaging where legacy systems are involved, and FHIR for cross-system and cross-organisation data exchange. Murphi’s FHIR integration platform and HL7 integration capabilities support both standards, allowing organisations to achieve interoperability across their full technology landscape — not just the modern parts.
API-Based Integrations
The shift from file-based and batch data exchange to API-based integration is one of the most significant changes in healthcare interoperability. FHIR RESTful APIs allow clinical applications to query patient data on demand, in real time, from any connected system — enabling the kind of instantaneous cross-system data access that clinical workflows increasingly require. Beyond basic data retrieval, the SMART on FHIR framework provides standardised application authorisation and launch protocols that allow third-party clinical applications to be embedded directly in EHR workflows, accessing patient context and data through the host system’s FHIR API.
API-based healthcare data exchange also enables the architecture of healthcare data ecosystems: a central FHIR server or health data platform that aggregates data from multiple source systems and exposes it through a consistent API, allowing any authorised application to retrieve what it needs without requiring a separate point-to-point integration with each source. This hub-and-spoke model is both more scalable and more secure than the traditional mesh of bilateral interface connections.
Murphi’s white-label automation platform uses this API-first architecture, enabling healthcare platforms to embed Murphi’s interoperability and AI capabilities within their own products without custom integration work for each new data source.
Benefits of Interoperability in Healthcare
Improved Patient Care
The most direct benefit of interoperability is better clinical decision-making. When a clinician has access to a complete, current, and accurate patient record — drawing from every system involved in that patient’s care — they are less likely to prescribe a contraindicated medication, order a test whose result is already available, miss a relevant diagnosis from a previous provider, or make an admission decision based on incomplete history. The evidence base for these benefits is strong and growing: studies consistently find that cross-system data sharing is associated with reduced medication errors, lower rates of duplicate testing, fewer preventable admissions, and improved management of patients with complex, multi-system conditions.
Interoperability also improves the patient experience directly. Patients who receive coordinated care — where every provider has access to the same complete record — experience fewer requests to repeat their medical history, fewer redundant tests, and more coherent care plans. Patient-facing interoperability, through FHIR-enabled personal health record applications, additionally gives patients direct access to their own health data — supporting self-management of chronic conditions and more informed participation in care decisions.
Operational Efficiency
Beyond clinical outcomes, interoperability delivers substantial operational benefits. Administrative staff time spent on manual record requests, data re-entry, and reconciliation is reduced or eliminated. Referral workflows that previously required phone calls and faxes are replaced by structured, automated digital exchange. Billing and coding accuracy improves when clinicians have access to the complete clinical context at the time of documentation. Regulatory reporting obligations — quality measures, public health surveillance, audit requirements — can be met through automated extraction from a unified data layer rather than manual compilation from multiple systems.
The aggregate administrative savings are significant. Healthcare organisations that have implemented comprehensive interoperability report reductions in administrative cost per encounter, improvements in claims first-pass rates, and meaningful reductions in the clinical documentation burden that drives physician burnout — all of which translate to a quantifiable return on the investment in interoperability infrastructure.
Visual 1: Healthcare Interoperability Architecture — Layers and Components
| Layer | Components | Role in Interoperability |
| Source Systems | EHRs, practice management systems, lab platforms, imaging systems, devices | Generate and hold clinical data — the origin of every patient record in the exchange |
| Integration Engine | HL7 v2 interface engine, FHIR server, API gateway, message broker | Receives, translates, routes, and acknowledges data between source and destination systems |
| Standards Layer | FHIR R4/R5 resources, HL7 v2 messages, CDA/C-CDA documents, DICOM for imaging | Defines the common language — data formats and terminologies — that all systems use to communicate |
| Data Exchange Network | Health information exchange (HIE), TEFCA-aligned network, payer-provider APIs | The infrastructure through which data travels across organisational boundaries |
| Terminology Services | SNOMED CT, LOINC, RxNorm, ICD-10, CPT code mappings | Ensures that the same clinical concept is represented consistently across all connected systems |
| Consuming Applications | Care coordination platforms, analytics tools, patient portals, population health systems | Receive and act on interoperable data to deliver clinical and operational value |
Visual 2: Healthcare Data Exchange Flow — From Clinical Event to Care Application
| Step | What Happens | Standard or Technology Used |
| 1 | A clinical event occurs — a diagnosis is recorded, a lab result is verified, a patient is admitted | Clinical source system (EHR, LIS, ADT) |
| 2 | The source system generates a structured clinical message or triggers an API event | HL7 v2 message (ADT, ORU, ORM) or FHIR resource event notification |
| 3 | The integration engine receives the message, parses it, validates it, and maps it to the target format | Integration engine (Murphi, Mirth Connect, Rhapsody) with FHIR or HL7 mapping rules |
| 4 | Terminology services translate local codes to standardised terminologies (SNOMED, LOINC, RxNorm) | Terminology server with mapping tables |
| 5 | The translated, standardised data is routed to all authorised destination systems or stored in a shared repository | FHIR API, HIE network, or care coordination platform |
| 6 | Consuming applications — EHRs, portals, analytics tools — retrieve and present the data to clinicians or patients | FHIR RESTful query, CDS Hooks, patient-facing APIs |
| 7 | Access logs, audit trails, and consent records are maintained for compliance and governance | Audit logging, consent management, HIPAA access controls |
Frequently Asked Questions
What is interoperability in healthcare?
Interoperability in healthcare is the ability of different health information systems — EHRs, laboratory platforms, imaging systems, and patient-facing applications — to exchange and use patient data seamlessly, within and across organisational boundaries, to support coordinated and effective care. It operates at four levels: foundational, structural, semantic, and organisational — each addressing a different dimension of data exchange.
Why is interoperability important in healthcare?
Interoperability is important because fragmented patient data leads to medication errors, duplicate testing, delayed diagnoses, avoidable admissions, and unsustainable administrative burden. When patient information flows automatically and accurately between all systems involved in a patient’s care, clinicians make better decisions, care coordination improves, costs fall, and patients experience safer and more coherent care across all settings.
What are the common challenges in achieving healthcare interoperability?
The most persistent challenges are data silos — patient records distributed across incompatible systems at different institutions — and legacy technology that was not designed for modern data exchange. Compounding these are inconsistent data standards, proprietary EHR formats, gaps in governance and trust frameworks that prevent cross-organisational sharing, and the absence of standardised terminology that allows clinical concepts to be consistently interpreted across systems.
What standards are used to achieve healthcare interoperability?
The primary standards are HL7 FHIR (Fast Healthcare Interoperability Resources) — which defines RESTful APIs and structured data resources for modern healthcare data exchange — and HL7 v2, which remains the dominant messaging standard for internal clinical workflows in most hospitals. Complementary standards include SNOMED CT, LOINC, and RxNorm for clinical terminology, DICOM for medical imaging, and ICD-10 and CPT for diagnostic and procedural coding.
How can interoperability in healthcare be improved?
Improvement requires action at multiple levels: implementing FHIR-compliant API layers on top of existing systems, migrating from legacy HL7 v2 point-to-point interfaces to standards-based integration platforms, establishing governance frameworks for cross-organisational data sharing, standardising terminology mapping, and designing clinical workflows that make use of the data that interoperability makes available. Partnering with a specialist platform such as Murphi accelerates this at every stage.