Healthcare is becoming increasingly digital. Patient records, diagnostic reports, medical images, prescriptions, insurance information, clinical research data and connected health applications are generating more information than ever before.
But there is a difference between having healthcare data and being able to access the right data when it matters.
For a doctor, delayed access to a patient record is more than an IT inconvenience. For a hospital, unavailable systems can disrupt operations. For a health-tech company, fragmented data can slow innovation. And for patients, the consequences can ultimately affect their experience of care.
India’s healthcare ecosystem is now reaching a scale where the underlying cloud and data infrastructure deserves as much attention as the applications running on it.
INDIA’S DIGITAL HEALTHCARE ECOSYSTEM IS ENTERING A NEW PHASE
The numbers tell an important story.
In September 2026, the Government of India reported that more than 97.8 crore ABHA accounts had been created and more than 121 crore health records had been linked. More than 5.6 lakh health facilities and 11 lakh healthcare professionals were registered within the ABDM ecosystem.
Earlier in May, ABDM crossed the milestone of 100 crore linked health records, doubling from 50 crore in February 2025 to more than 100 crore in just 15 months.
This is not simply a story about digitisation.
It represents a fundamental shift in how healthcare information is created, stored, exchanged and accessed across India.
The launch of the Unified Health Interface (UHI) in June 2026 further strengthened this direction by creating an open network intended to allow patients and healthcare providers to connect across different digital platforms.
As healthcare becomes more connected, the infrastructure supporting that connectivity becomes increasingly important.
The question is no longer whether healthcare organisations will generate more data. It is whether their infrastructure is prepared to manage it effectively.
HEALTHCARE DATA IS GROWING BUT IT IS ALSO BECOMING MORE COMPLEX
A modern healthcare organisation may manage very different types of information:
- Electronic medical records
- Patient histories
- Laboratory results
- Diagnostic reports
- Medical images
- Prescriptions
- Insurance and claims data
- Hospital management data
- Research information
- Application and system logs
Not all of this data has the same access requirements.
A patient’s current clinical record may need to be available immediately.
A medical image may require significant storage capacity.
An older record may need to be retained for a long period but accessed less frequently.
A backup may need to exist primarily for recovery rather than everyday access.
Treating all of this information as one category can create unnecessary cost and operational complexity.
The better approach?
Think in terms of data lifecycle:
Create → Use → Store → Protect → Archive → Retrieve
A healthcare cloud strategy should consider where data sits at each stage and what level of availability it actually requires.
This is where cloud infrastructure and long-term data archival become strategic rather than purely technical decisions.
ACCESSIBILITY MATTERS AS MUCH AS STORAGE
One of the biggest misconceptions about healthcare data is that storing it means it is available.
It doesn’t.
Data may exist somewhere in an organisation’s infrastructure but still be difficult to access because of:
- Fragmented systems
- Incompatible formats
- Legacy applications
- Poor integration
- Insufficient infrastructure capacity
- Network limitations
- Weak data management practices
KPMG’s 2026 analysis of India’s healthcare AI readiness highlights this challenge: healthcare data remains fragmented across hospitals, clinics, laboratories and insurers, while data readiness continues to be a significant barrier to scaling AI in healthcare.
This matters because emerging healthcare applications increasingly depend on data.
AI-assisted diagnostics, clinical analytics, patient portals, predictive models and digital health services all require access to reliable and appropriately managed information.
Better healthcare technology needs better data foundations.
HEALTHCARE ORGANISATIONS ARE UNDER PRESSURE TO MODERNISE
The pressure is coming from several directions simultaneously.
Healthcare providers are expanding capacity and adopting higher-acuity specialties. EY’s September 2026 healthcare update notes continued hospital capacity expansion, specialty-led growth and network development as India enters FY27.
At the same time, technology adoption is accelerating.
Healthcare organisations are investing in:
- Hospital Information Systems
- Electronic Medical Records
- Cloud platforms
- AI and analytics
- Patient applications
- Telehealth
- Digital diagnostics
- Interoperable health records
This creates an infrastructure challenge.
A hospital may modernise its application layer while still relying on infrastructure designed for a very different data environment.
That can result in data silos, capacity constraints and operational complexity.
The answer isn’t necessarily to replace everything.
It is to build an infrastructure foundation that can support the organisation’s existing systems while allowing new digital services to grow around them.
SECURITY CANNOT BE SEPARATED FROM ACCESSIBILITY
Healthcare data is highly sensitive.
The goal is not simply to make information accessible. It is to make it appropriately accessible.
That distinction matters.
The healthcare industry continues to face significant cyber risk. The India Cyber Threat Report 2026 reported that healthcare and pharmaceuticals recorded 3.79 million threat detections, representing 14.24% of detections in the report’s telemetry between October 2024 and September 2025.
This makes data protection an infrastructure priority.
A healthcare cloud environment needs to consider:
- Who can access the data?
- What data can they access?
- Where is the data stored?
- How is access monitored?
- What happens if an account or system is compromised?
- How can critical data be recovered?
India’s digital-health architecture itself places strong emphasis on privacy and consent. ABDM states that health data exchange occurs with patient consent, while integrated digital-health applications undergo validation and security audits before integration.
The Digital Personal Data Protection Rules, 2025, also establish a framework for protecting digital personal data in India, with provisions taking effect according to the notified implementation timeline.
For healthcare organisations, therefore, cloud infrastructure should be considered alongside data governance, security, access control and privacy requirements.
LONG-TERM DATA NEEDS A DIFFERENT STRATEGY
Healthcare organisations cannot simply keep every piece of historical information in their highest-performance storage forever.
That can become expensive and difficult to manage as data volumes increase.
At the same time, deleting information simply because it is old may not be appropriate where retention requirements, clinical needs, organisational policies or applicable laws require it to be retained.
This creates a need for long-term data archival.
A practical healthcare data strategy can distinguish between:
Active data
Frequently accessed information supporting current clinical and operational activity.
Backup data
Copies maintained primarily to support recovery from data loss or system failure.
Archived data
Information retained for longer-term requirements and accessed less frequently.
This distinction is important.
Backup and archival are not the same thing.
Backup answers:
“How do we recover?”
Archival answers:
“How do we retain and retrieve information over the longer term?”
For data-intensive healthcare organisations, separating these requirements can help create a more structured and cost-conscious storage strategy.
Cloud can provide the foundation but architecture still matters
Moving healthcare data to the cloud is not, by itself, a complete strategy.
The real value comes from designing the environment around the organisation’s workloads.
A healthcare cloud strategy should consider:
Scalability Can infrastructure accommodate changing workloads as patient volumes, applications and data grow?
Performance Can frequently accessed applications and records receive the resources they require?
Data protection Are appropriate backup and recovery mechanisms in place?
Security Are identity, access, monitoring and configuration controls appropriately implemented?
Archival Can long-term data be retained without treating every dataset as high-performance active storage?
Operational control Can authorised technology teams provision and manage infrastructure efficiently?
These considerations become increasingly important as healthcare moves from isolated digital applications toward interconnected ecosystems.
WHERE GATICLOUD FITS
For GatiCloud, the opportunity is not to position cloud as a magic solution to every healthcare challenge.
The more useful proposition is simpler:
Healthcare organisations need infrastructure that can support the way their data is actually created, used, protected and retained.
GatiCloud’s self-service cloud approach can provide a foundation for organisations that want greater flexibility and control over their cloud infrastructure.
For healthcare technology teams, that can mean approaching infrastructure through a more structured lens:
Workload → Resource → Protection → Retention → Access
A healthcare organisation may have different infrastructure requirements for its applications, databases, development environments and long-term data.
A self-service cloud model can help authorised teams provision and manage infrastructure resources according to those requirements, while the organisation applies its own security, governance, backup and compliance controls.
This distinction is important.
The cloud platform provides the infrastructure foundation. The healthcare organisation remains responsible for how its data, applications and processes are designed and governed.
THE HEALTHCARE CLOUD QUESTION HAS CHANGED
A few years ago, the question may have been:
“Should we move healthcare workloads to the cloud?”
Today, a more useful question is:
“Is our cloud and data infrastructure designed for the healthcare ecosystem we are becoming?”
That ecosystem is increasingly:
- Digital
- Interoperable
- Data-intensive
- AI-enabled
- Patient-centric
- Connected across providers
India’s healthcare transformation is already demonstrating the scale of this shift. ABDM’s rapid growth shows that digital health records are no longer a small pilot, they are becoming part of the country’s healthcare infrastructure.
The next challenge is making sure the infrastructure underneath this transformation can evolve with it.
THE FUTURE OF HEALTHCARE DEPENDS ON ACCESSIBLE DATA
Healthcare data has value only when it can be used appropriately.
A record that cannot be retrieved when needed does not deliver its full value.
A system that cannot scale with patient demand creates operational friction.
A data environment without appropriate protection creates unnecessary risk.
And an organisation that treats active data, backup and archival as the same problem may struggle to manage cost and complexity as its digital footprint expands.
For healthcare leaders, the priority should therefore be broader than simply “moving to cloud.”
It should be about building a scalable, accessible and well-governed healthcare cloud infrastructure that supports today’s workloads while preparing for tomorrow’s data demands.
At GatiCloud, we believe the cloud should empower technology teams to manage infrastructure with greater flexibility and control so they can focus on what ultimately matters:
Keeping healthcare services connected, data accessible and digital innovation moving forward.
FREQUENTLY ASKED QUESTIONS
What is healthcare cloud infrastructure?
Healthcare cloud infrastructure is the combination of computing, storage, networking and related services used to support healthcare applications and data, including electronic medical records, diagnostics, patient platforms, analytics and digital-health services.
Why is cloud infrastructure important for healthcare in India?
India’s digital-health ecosystem is expanding rapidly. With more than 121 crore health records linked to ABHA as reported in September 2026, healthcare organisations need infrastructure capable of supporting growing data volumes, interoperability, security and availability requirements.
What is the difference between healthcare data backup and archival?
Backup is primarily intended to help recover data after loss, corruption or system failure. Archival is focused on retaining information for longer periods and enabling retrieval when required. They serve different purposes and should be planned accordingly.
How can self-service cloud help healthcare organisations?
A self-service cloud model can give authorised technology teams a more direct way to provision and manage infrastructure resources. This can reduce routine provisioning friction while allowing organisations to maintain appropriate governance, security and access controls.
Is cloud automatically secure for healthcare data?
No. Cloud adoption does not automatically make healthcare data secure or compliant. Security depends on the architecture, configurations, identity controls, data protection mechanisms, monitoring, operational processes and responsibilities shared between the organisation and its technology providers.
OUR KEY SOURCES
Government of India / Primary Sources
- Ministry of Health & Family Welfare – PIB
Arogya Manthan 2026 / Ayushman Bharat Digital Mission update
Key data: 97.8 crore ABHAs, 121 crore linked health records, 5.6 lakh+ health facilities and 11 lakh healthcare professionals. - Ministry of Health & Family Welfare – PIB
ABDM crosses 100 crore linked health records
Supports the rapid expansion of India’s digital healthcare ecosystem. - Ayushman Bharat Digital Mission (ABDM)
Health Data Management Policy
Supports claims around privacy-by-design, consent, federated architecture, interoperability and health-data protection. - Ministry of Electronics & Information Technology (MeitY)
Digital Personal Data Protection Rules, 2025
Primary regulatory source for India’s evolving personal-data protection framework.
Major Industry & Professional Research
- KPMG India
Can India’s Healthcare System Keep Pace with AI Ambitions?
Useful for healthcare data readiness, fragmentation, data quality and AI/cloud infrastructure challenges. - EY-Parthenon India
India Healthcare Sector Records Strong FY26 Growth
Supports the broader healthcare growth and capacity-expansion narrative. - EY-Parthenon India
How Hospital Expansions Are Reshaping India’s Healthcare Sector
Useful for the FY27 outlook and increasing technology/infrastructure requirements.
Supporting Industry Research
EY-Parthenon – CII HealthTech Survey
Supports discussion around increasing healthcare IT investment, digital innovation and technology adoption challenges.
