1. Some Key Interoperability Standards in Digital Health

1. HL7: Health Level Seven

• It is one of the oldest and most commonly used messaging standards.
• Defines the rules for sending data like Admissions, Discharges, Transfers, Lab Results, Billings among others.
• Most of the legacy HMIS/HIS systems in South Asia are still heavily dependent on HL7 v2.x messages.

Why it matters:

That is, it makes sure that basic workflows like registration, laboratory orders, and radiology requests can be shared across systems even though they might be 20 years old.

2. FHIR: Fast Healthcare Interoperability Resources

• The modern standard. The future of digital health.
• FHIR is lightweight, API-driven, mobile-friendly, and cloud-ready.

It organizes health data into simple modules called Resources, for example, Patient, Encounter, Observation.

Why it matters today:

• Allows real-time transactions via REST APIs
• Perfect for digital apps, telemedicine, and patient portals.
• Required for modern national health stacks – ABDM, NHS etc

FHIR is also very extensible, meaning a country or state can adapt it without breaking global compatibility.

 3. DICOM stands for Digital Imaging and Communications in Medicine

• The global standard for storing and sharing medical images.
• Everything uses DICOM: radiology, CT scans, MRI, ultrasound.

Why it matters:

Ensures that images from Philips, GE, Siemens, or any PACS viewer remain accessible across platforms.

4. LOINC – Logical Observation Identifiers Names and Codes

Standardizes laboratory tests.

• Example: Glucose fasting test has one universal LOINC code — even when hospitals call it by different names.

This prevents mismatched lab data when aggregating or analyzing results.

5. SNOMED CT

• Standardized clinical terminology of symptoms, diagnoses, findings.

Why it matters:

Instead of each doctor writing different terms, for example (“BP high”, “HTN”, “hypertension”), SNOMED CT assigns one code — making analytics, AI, and dashboards possible.

6. ICD-10/ICD-11

• Used for diagnoses, billing, insurance claims, financial reporting, etc.

7. National Frameworks: Example – ABDM in India

ABDM enforces:

• Health ID (ABHA)
• Facility Registry
• Professional Registry
• FHIR-based Health Information Exchange
• Gateway for permission-based data sharing

Why it matters:

It becomes the bridge between state systems, private hospitals, labs, and insurance systems without forcing everyone to replace their software.

2. Why Health Systems Are Often Siloed

Real-world health IT systems are fragmented because:

• Each hospital or state bought different software over the years.
• Legacy systems were never designed for interoperability.
• Vendors lock data inside proprietary formats
• Paper-based processes were never fully migrated to digital.
• For many years, there was no unified national standard.
• Stakeholders fear data breaches or loss of control.
• IT budgets are limited, especially for public health.

The result?

Even with the intention to serve the same patient population, data sit isolated like islands.

3. How Health Systems Can Overcome Siloed Systems & Enable Real-Time Data Exchange

This requires a combination of technology, governance, standards, culture, and incentives.

A. Adopt FHIR-Based APIs as a Common Language

• This is the single most important step.
• Use FHIR adapters to wrap legacy systems, instead of replacing old systems.
• Establish a central Health Information Exchange layer.
• Use resources like Patient, Encounter, Observation, Claim, Medication, etc.

Think of FHIR as the “Google Translate” for all health systems.

B. Creating Master Patient Identity: For example, ABHA ID

• Without a universal patient identifier, interoperability falls apart.
• Ensures the same patient is recognized across hospital chains, labs, insurance systems.
• Reduces duplicate records, mismatched reports, fragmented history.

C. Use a Federated Architecture Instead of One Big Central Database

Modern systems do not pool all data in one place.

They:

• Keep data where it is (hospital, lab, insurer)
• Only move data when consent is given
• Exchange data with secure real-time APIs
• Use gateways for interoperability, as ABDM does.

This increases scalability and ensures privacy.

D. Require Vocabulary Standards

To get clean analytics:

• SNOMED CT for clinical terms
• LOINC for labs
• ICD-10/11 for diagnoses
• DICOM for images

This ensures uniformity, even when the systems are developed by different vendors.

E. Enable vendor-neutral platforms and open APIs

Health systems must shift from:

•  Vendor-Locked Applications
• to
• open platforms where any verified application can plug in.

This increases competition, innovation, and accountability.

F. Modernize Legacy Systems Gradually

Not everything needs replacement.

Practical approach:

• Identify key data points
• Build middleware or API gateways
• Enable incremental migration

Bring systems to ABDM Level-3 compliance (Indian context)

G. Organizational Interoperability Framework Implementation

Interoperability is not only technical it is cultural.

Hospitals and state health departments should:

• Define governance structures
• Establish data-sharing policies
• Establish committees that ensure interoperability compliance.

Establish KPIs: for example, % of digital prescriptions shared, % of facilities integrated

H. Use Consent Management & Strong Security

Real-time exchange works only when trust exists.

Key elements:

• Consent-driven sharing
• Encryption (at rest & in transit)
• Log auditing
• Role-based access
• Continuous monitoring
• Zero-trust architecture

A good example of this model is ABDM’s consent manager.

4. What Real-Time Data Exchange Enables

Once the silos are removed, the effect is huge:

• For Patients
• Unified medical history available anywhere
• Faster and safer treatment
• Reduced duplicate tests and costs
• For Doctors
• Complete 360° patient view
• Faster clinical decision-making
• Reduced documentation burden with AI
• For Hospitals & Health Departments
• Real-time dashboards like PMJAY, HMIS, RI dashboards
• Predictive analytics
• Better resource allocation

Fraud detection Policy level insights For Governments Data-driven health policies Better surveillance State–central alignment Care continuity across programmes

5. In One Line

Interoperability is not a technology project; it’s the foundation for safe, efficient, and patient-centric healthcare. FHIR provides the language, national frameworks provide the rules, and the cultural/organizational changes enable real-world adoption.

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