Healthcare enterprises are generating more data than ever before. Yet, much of this information remains siloed across disparate systems, including electronic health records (EHRs), lab reports, telehealth platforms, and payer databases.
To unlock the full value of this data, the industry must make data interoperability a strategic priority. It enables healthcare systems and technologies to seamlessly exchange, interpret, and utilize member information across platforms. Interoperability ensures that insurers and care providers have timely and secure access to the information they need, driving better coordination, decision-making, and outcomes.
As the healthcare ecosystem becomes increasingly member-centric, efficient and reliable data sharing is no longer optional—it’s essential. According to a Rock Health study, 95% of physicians believe that better healthcare data sharing improves care quality, while 86% say it supports faster and more accurate diagnoses.
That’s why data interoperability in healthcare is more than a technological milestone—it’s a foundational enabler of modern, connected healthcare. It fosters collaboration across teams, eliminates redundant testing and delays, and empowers members with the information they need to actively manage their health.
In this blog, we’ll explore how platforms like AVIZVA’s VIZCare Connect are helping healthcare enterprises unlock the full potential of connected care.
The Current Healthcare Data Landscape
Diverse Data Sources and the Need for Integration
Every time a patient visits a doctor, undergoes a test, files an insurance claim, or uses a health device, new data is generated. However, much of this information remains fragmented across various disconnected systems, underscoring the importance of data interoperability in healthcare information exchange.
Here are some of the primary sources where healthcare data is stored:
- Electronic Health Records (EHRs): Contain patient histories, medications, treatment plans, and physician notes.
- Claims Data: Managed by insurance providers to track treatments, billing, and reimbursements.
- Medical Devices: Devices like heart monitors, glucose meters, and fitness trackers collect continuous health data that is often siloed within proprietary systems.
- Lab and Imaging Reports: Diagnostic test results and scans are frequently stored in standalone systems, limiting their accessibility across teams.
Challenges Posed by Data Silos and Inconsistent Formats
One of the most persistent challenges of implementing data interoperability in healthcare today is that member data remains locked in disparate systems that don’t easily communicate with one another. This fragmentation makes it difficult to build a unified view of a member’s health journey. Key issues include:
- High Integration Effort of HL7: While HL7 is a widely used standard for sharing health data, it often requires complex integration and customization to work with modern platforms, slowing down interoperability efforts.
- Slow Adoption of FHIR: FHIR offers a more flexible and modern approach to data exchange. However, adoption is still uneven across the industry, as many healthcare enterprises continue to rely on legacy systems that lack compatibility.
- Limitations of Proprietary and Legacy Systems: Smaller clinics and providers often operate with outdated, proprietary technologies that weren’t built for healthcare data sharing. Limited budgets and IT resources further hinder their ability to upgrade or integrate with broader networks.
Impact of a Fragmented & Complex Healthcare Data Landscape
The fragmentation of healthcare data continues to create significant challenges across the industry, impacting care delivery, claims management, and consumer outcomes.
- Compromised Care Delivery and Operational Overhead: Fragmented data across EHRs, labs, and external systems limits a provider’s ability to access complete patient records in real-time. This leads to care coordination breakdowns, redundant diagnostic tests, and delays in treatment decisions. Additionally, teams must often rely on manual processes to reconcile data between systems, increasing administrative burden and reducing time spent on patient care.
- Inefficient Claims Management and Risk Visibility: For payers, inconsistent data formats and disconnected systems disrupt the claims lifecycle—from adjudication to fraud detection. Without timely, structured clinical data, payers face challenges in validating claims, managing costs, and assessing member risk. This fragmentation also hampers efforts to implement value-based care models and population health strategies.
- Poor Consumers’ Experience and Health Outcomes: When data is siloed, healthcare consumers are often forced to repeat tests, retell their medical histories, or wait longer for accurate diagnoses. The lack of data continuity across touchpoints results in fragmented care journeys, lower trust in the system, and ultimately, suboptimal health outcomes. Consumers are also left with limited access to their own data, restricting their ability to make informed decisions.
What Is Data Interoperability?
In a rapidly evolving landscape, data interoperability in healthcare is critical to delivering connected, coordinated care. It enables diverse systems, devices, and platforms to seamlessly exchange, understand, and utilize data—without compatibility issues—across organizational and technological boundaries.
Key Components of Data Interoperability
Technical Interoperability: Technical interoperability refers to the ability of systems built on different technologies to exchange data reliably and accurately. It focuses on the transport and communication layer, ensuring that electronic health records (EHRs), lab systems, pharmacy platforms, and other software can transmit and receive information without data loss or corruption.
This layer of interoperability is enabled by standardized technologies such as APIs and data formats like XML and JSON, which facilitate seamless “conversations” between otherwise incompatible systems.
Semantic Interoperability: Semantic interoperability ensures that once data is exchanged between systems, it is interpreted consistently by both the sender and the receiver. It focuses on preserving the meaning and context of the information, so that clinical and administrative data retains its integrity across different platforms.
This level of interoperability is made possible through the use of industry standards such as HL7 and FHIR, which define common structures, terminologies, and data models to ensure that systems “understand” the information in the same way.
Organizational Interoperability: Organizational interoperability refers to the ability of different healthcare organizations and stakeholders to collaborate effectively by aligning policies, workflows, and governance structures that support seamless data exchange. It ensures that data sharing is not only technically possible and semantically clear, but also operationally coordinated across departments, systems, and organizations.
This level of interoperability focuses on standardizing procedures, establishing trust frameworks, and aligning compliance and regulatory practices to enable secure, efficient, and scalable health information exchange.
The Role of Standards in Enabling Interoperability
Industry standards play a critical role in making healthcare interoperability possible. They provide the common language and framework needed for different systems to exchange, interpret, and use data consistently and accurately. Some of the most widely adopted standards and technologies include:
FHIR (Fast Healthcare Interoperability Resources): A modern, flexible standard designed to simplify the exchange of healthcare data. FHIR utilizes web-based technologies to facilitate clear and consistent communication between systems, thereby simplifying the integration of data across various platforms and applications.
HL7 (Health Level Seven): A foundational standard that has long supported the exchange of clinical and administrative data. Although older, HL7 remains widely used and has paved the way for newer models, such as FHIR.
APIs (Application Programming Interfaces): APIs serve as secure digital connectors, enabling healthcare applications, platforms, and devices to communicate with each other in real-time. They enable systems to access, send, and update health information seamlessly across different environments.
How Interoperability Differs from Simple Data Exchange
While often used interchangeably, interoperability and data exchange are not the same. Interoperability goes far beyond simply moving data between systems — it ensures that data is understood, trusted, and usable in its new environment.
Data Exchange: Basic data exchange refers to the transfer of information from one system to another. However, it does not guarantee that the receiving system can interpret or utilize the data in a meaningful way. The data may arrive, but its structure, context, or terminology may not be compatible with the destination system.
Data Interoperability: True interoperability ensures that the exchanged data is not only delivered but also interpreted accurately, retains its original meaning, and can be acted upon. It supports effective clinical decision-making, care coordination, and automation by enabling systems to work in harmony, regardless of their technical differences.
Why Data Interoperability Is the Backbone of Connected Care
Data interoperability is fundamental to establishing a connected and efficient healthcare ecosystem. By enabling seamless communication among key stakeholders – providers, payers, and patients – it serves as a catalyst for innovation, improving financial efficiency, preventing fraud, enabling holistic member views, and reducing administrative burdens.
Improving Financial Efficiency and Preventing Fraud
The Challenge:
Fragmented healthcare systems often result in inefficient claims processing, billing inaccuracies, and an increased risk of fraud. Insurers frequently face delays in payment processing or claim denials due to incomplete or inconsistent information.
The Solution:
Interoperable systems enable real-time, secure exchange of accurate medical and financial data between insurers and healthcare providers. This transparency reduces errors and fraudulent activities, allowing payers to make more informed risk assessments and streamline claims management.
The Benefit:
For healthcare insurance providers, this translates to more accurate billing, faster claims adjudication, and a significant reduction in fraudulent claims. For members, it means clear, consistent billing and fewer unexpected financial burdens. Ultimately, interoperability enhances financial efficiency, accountability, and trust across the entire healthcare ecosystem.
Enabling Real-Time, Holistic Member Views
The Challenge:
Healthcare data is often siloed across multiple systems, making it difficult for payers and care teams to obtain a complete, real-time view of a member’s health history, treatments, and ongoing needs. This fragmentation can lead to gaps in care, delayed interventions, and a lack of personalized engagement.
The Solution:
Interoperability integrates data from various sources—such as electronic health records (EHRs), pharmacy systems, labs, and wellness platforms—into a unified, real-time view of each member. This comprehensive perspective enables more informed decision-making, proactive care management, and targeted member engagement.
The Benefit:
For healthcare insurers and care providers, a holistic member view facilitates earlier interventions, improved care coordination, and personalized health strategies. For members, it ensures more seamless care experiences, timely support, and better health outcomes. Interoperability empowers stakeholders to move from reactive to proactive care delivery, strengthening overall population health management.
Reducing Administrative Burdens
The Challenge:
Healthcare enterprises often face high administrative overhead due to manual processes, redundant data entry, and inefficient communication between systems. This lack of interoperability leads to time-consuming tasks for providers and payers alike, diverting valuable resources away from member care and driving up operational costs.
The Solution:
Interoperable systems automate and streamline data exchange across healthcare stakeholders, reducing duplication, minimizing manual intervention, and improving accuracy. By ensuring that data flows seamlessly between clinical, financial, and administrative systems, enterprises can eliminate inefficiencies and simplify workflows.
The Benefit:
For providers and payers, this means less time spent on administrative tasks, faster access to critical information, and improved staff productivity. For members, it translates to quicker service delivery, fewer errors in documentation, and a more efficient care experience. Ultimately, interoperability reduces operational friction, enabling healthcare organizations to focus more on value-driven care and member satisfaction.
Overcoming Challenges to Achieve True Interoperability
Achieving true data interoperability in healthcare involves navigating a complex mix of technical, organizational, security, and strategic hurdles. Here’s a breakdown of the most common barriers — and how to address them effectively.
1. Technical Barriers: Overcoming Legacy Systems and Inconsistent Standards
The Challenge:
One of the most significant obstacles to interoperability is the widespread use of legacy systems that were never designed to support modern data exchange. These outdated platforms often lack the flexibility or compatibility to integrate with newer technologies, yet they remain deeply embedded in healthcare workflows.
Compounding the issue is the lack of standardization across data formats. Healthcare data exists in a variety of forms — from proprietary structures to standards like HL7 and FHIR — each with different levels of adoption and interoperability readiness. This diversity makes data exchange complex, error-prone, and resource-intensive.
How to Overcome It:
- Modernize or extend legacy systems using middleware or integration layers.
- Standardize on widely accepted data models, such as HL7 and FHIR.
- Leverage APIs to enable seamless, real-time communication across systems.
2. Organizational Barriers: Aligning Stakeholders and Strengthening Governance
The Challenge:
Even with the right technologies in place, achieving data interoperability in healthcare requires strong organizational alignment and robust data governance. Many healthcare enterprises operate in silos, where departments have conflicting priorities and limited visibility into each other’s workflows.
Without clearly defined policies around data ownership, access, and stewardship, it becomes difficult to implement consistent governance practices. This lack of alignment often leads to inefficient data sharing, delayed decision-making, and resistance to cross-functional collaboration — all of which hinder true interoperability.
How to Overcome It:
- Establish clear data ownership and access control policies.
- Promote cross-functional collaboration between departments and teams.
- Secure executive sponsorship and leadership buy-in for interoperability goals.
3. Security Barriers: Safeguarding Data Privacy In Multi-System Environments
The Challenge:
As healthcare data moves across multiple systems — including EHRs, payer databases, labs, and third-party platforms — ensuring data security and patient privacy becomes increasingly complex. Sensitive information such as personal identifiers, medical histories, and insurance details is highly vulnerable to unauthorized access, breaches, or misuse if not properly protected.
The risk is further amplified when interoperability efforts lack standardized security protocols or rely on outdated infrastructure. Without strong safeguards, even well-intentioned data sharing can expose organizations to compliance violations and reputational damage.
How to Overcome It:
- Encrypt data in transit and at rest.
- Implement multi-factor authentication (MFA) for system access.
- Use secure, standards-compliant APIs and platforms.
- Partner with trusted technology providers like AVIZVA to ensure end-to-end security and compliance.
4. Strategic Barriers: Selecting The Right Technology Partner For Long-Term Success
The Challenge:
Building true data interoperability in healthcare goes beyond technology; it requires deep expertise in healthcare architecture, compliance, stakeholder alignment, and change management. Many healthcare organizations lack the in-house capabilities to effectively navigate these complexities. As a result, they must rely on trusted technology partners to help implement scalable, secure, and standards-compliant interoperability solutions.
Choosing the wrong partner can lead to delays, misaligned strategies, and solutions that are not future-ready or compliant with evolving regulations.
How to Overcome It:
- Partner with vendors who have deep healthcare expertise and regulatory understanding.
- Leverage purpose-built solutions like VIZCare Connect for seamless integration.
- Engage experts to support stakeholder alignment and change management.
- Ensure platforms are scalable, secure, and future-proof.
The Road Ahead: Future Trends in Healthcare Interoperability
1. AI and Machine Learning: Advancing Semantic Interoperability
The Trend:
Artificial Intelligence (AI) and Machine Learning (ML) are playing a growing role in enhancing semantic interoperability — the ability of systems to not only exchange data but also understand and interpret it meaningfully. These technologies help normalize and structure healthcare data across disparate formats, sources, and standards.
The Impact:
- Accelerated and more accurate data interpretation
- AI-driven clinical and operational insights
- Streamlined workflows and decision-making across systems
2. Open APIs and Cloud Platforms: Enabling Scalable, System-Wide Interoperability
The Trend:
The growing adoption of open APIs and cloud-based platforms is breaking down traditional data silos in healthcare. Open APIs facilitate seamless integration between disparate systems, while cloud infrastructure provides scalable, secure, and always-available environments to support real-time data exchange and interoperability.
The Impact:
- Simplified, system-wide integrations across vendors and platforms
- Scalable, secure storage with real-time accessibility
- Enhanced remote access for providers, payers, and patients
3. Policy Initiatives and Industry Alliances: Accelerating Standards Adoption
The Trend:
Governments, regulatory bodies, and industry stakeholders are increasingly collaborating to promote the adoption of unified data standards such as FHIR and HL7. These efforts are laying the groundwork for widespread, consistent interoperability by creating clear guidelines and incentives for compliance.
The Impact:
- Accelerated implementation of interoperable systems across the ecosystem
- Greater consistency and standardization of healthcare data
- Shift in focus from integration barriers to innovation and value delivery
4. A Connected, Member-Centric Ecosystem: Empowering Ownership and Personalization
The Trend:
The long-term vision for healthcare interoperability is a fully connected ecosystem where members have complete control over their health data, and providers and insurers can access a unified, longitudinal view of each individual’s health history. As interoperability standards, AI technologies, and regulatory frameworks continue to evolve, this vision is steadily becoming a reality.
The Impact:
- Increased member empowerment through secure access and ownership of health data
- A 360-degree, real-time view of member health across care settings and stakeholders
- More personalized, coordinated, and proactive care delivery
Use Cases Demonstrating the Power of Interoperability
In today’s rapidly evolving healthcare insurance landscape, data interoperability in healthcare has emerged as a key enabler of operational efficiency, enhanced member engagement, and improved service delivery. As insurance models shift and expectations rise, the ability to seamlessly share and interpret data across systems is no longer optional — it’s foundational.
Here are some real-world use cases that highlight how interoperability is actively transforming healthcare delivery:
Faster Decision-Making Through Unified Member Data
By integrating claims, customer service, and payment systems, insurers can access a consolidated, real-time view of member data. This empowers agents to quickly assess individual cases, make informed decisions, and significantly reduce approval turnaround times — improving both efficiency and customer satisfaction.
Seamless Multi-Channel Member Communication
Interoperable communication platforms enable insurers to deliver consistent, responsive support across multiple channels, including phone, email, chat, and self-service portals. With synchronized access to updated member data, all customer-facing teams can collaborate effectively and resolve issues faster.
Lower Administrative Costs Through Automation
By connecting systems across policy administration, claims processing, underwriting, and customer service, insurers can automate data entry and reduce manual workflows. This not only minimizes operational overhead but also improves accuracy and accelerates service delivery.
Enhanced Fraud Detection and Risk Management
Interoperable data environments enable insurers to identify anomalies and inconsistencies across claims in real-time. This integrated view supports earlier fraud detection, improves compliance, and allows for proactive risk mitigation strategies.
VIZCare Connect: The Key to Seamless Data Interoperability in Healthcare Insurance
At AVIZVA, we view data interoperability as the cornerstone of connected care, enabling seamless, real-time access to member information across diverse healthcare systems.
Our flagship solution, VIZCare Connect, is a robust data connectivity platform purpose-built to meet the end-to-end integration and interoperability needs of healthcare enterprises. As a first-of-its-kind solution, VIZCare Connect provides real-time visibility into data flows, dependencies, and potential bottlenecks, empowering organizations to make informed decisions, streamline operations, and manage the entire data lifecycle with precision and confidence.
Following are the key features of VIZCare Connect:
Real-Time Data Orchestration and Synchronization: The platform supports a wide range of integration protocols and formats, automates complex data flows, and leverages built-in AI to configure sources, map fields, and optimize transformations dynamically.
A Robust Suite Of 300+ Healthcare APIs: The platform offers a rich set of micro-services that support lookup, read, search, add, and update functions across all healthcare data types. The APIs are designed to accelerate internal product development and unlock enterprise-grade innovation at scale.
Preloaded & Continuously Updated Healthcare Industry Data: The platform provides an enriched, ready-to-use dataset that complements enterprise data, enabling enhanced analytics, decision-making, and AI-driven insights.
360 Degree Data Views for Business & Operational Intelligence: The platform delivers end-to-end visibility across all systems and touchpoints, providing real-time insights and analytics to drive scalable, accurate, and efficient healthcare operations.
Conclusion
Data interoperability in healthcare isn’t just a technological advancement—it’s a modern healthcare essential.
As the healthcare landscape continues to evolve, the ability to seamlessly share data across systems has become critical. Interoperability not only enhances the quality of care delivery but also improves end-to-end operational efficiency for healthcare enterprises.
To truly elevate care outcomes, organizations need robust healthcare connectivity platforms like VIZCare Connect – purpose-built to eliminate data silos and power enterprise-wide interoperability.
Still facing disconnected systems and fragmented data? Make interoperability seamless with VIZCare Connect. Let’s talk.
FAQs
1. What is data interoperability in healthcare?
Healthcare data interoperability enables different healthcare systems to share and utilize data with each other seamlessly across platforms, in real-time, and at every visit.
2. Why is data interoperability important in healthcare?
Data interoperability plays a crucial role, as it enables healthcare providers to access and share patient data. This leads to better care coordination, improved productivity, and, in the end, better results for patients.
3. What is connected care?
Integrated care takes a team approach where healthcare systems and providers join forces using up-to-the-minute data to offer team-based and patient-focused care to boost health outcomes.
4. How does data interoperability enable connected care?
When data can work together, it paves the way for smooth communication and exchange of live data between different healthcare systems. This ensures all key players have access to current and correct patient details, which is a must for coordinated and timely care delivery.
5. What are the key challenges in achieving data interoperability in healthcare?
The main problems are outdated systems standardizing data, handling privacy and security, and getting different healthcare departments to agree on common data-sharing rules. This leads to fewer errors and better-coordinated treatment.
6. How does data interoperability impact patient care?
Data interoperability enhances patient care by providing healthcare teams with an up-to-date view of a patient’s health data, leading to reduced errors and improved care coordination.
7. What are health information exchanges (HIEs) and their role in data interoperability?
HIEs, which stand for Health Information Exchanges, let organizations share patient records. They’re crucial for smooth data transfer and helping care teams work together.
8. What is the future of data interoperability in healthcare?
The future of data interoperability includes widespread use of open APIs, along with cloud and AI-driven tools. These make joining systems easier, help follow rules, and turn connected healthcare into the norm.
9. How can healthcare providers improve data interoperability in their organizations?
Healthcare providers can boost data sharing by using cutting-edge tech, making data formats like FHIR and HL7 the same for everyone, and sticking to rules like HIPAA.
10. How does data interoperability help in reducing healthcare costs?
Data interoperability reduces healthcare costs by reducing paperwork costs and helps doctors work together better, both of which lower the total healthcare bill.