Healthcare creates more data than any other industry in the USA, but most of the data remains locked inside the systems where it was produced. It means hospitals, clinics, and even labs cannot share patient information conveniently.
The USA loses $265 billion every year due to manual and inefficient ways of data sharing. Compared to other industries, banks can transfer money promptly everywhere in the world, and delivery companies can track their packages in real time.
But in the healthcare industry, a lab report often cannot be sent smoothly from one hospital to another. The issue is not that technology doesn’t exist, but the reason is a combination of outdated software, business decisions by software vendors, and weak coordination between organizations.
The Structural Reasons Healthcare Data Stays Stuck
Healthcare data is often trapped inside separate systems that were never designed to communicate with each other. Even with modern standards and APIs, structural, business, and organizational barriers still prevent seamless data sharing across the ecosystem.
Fragmented systems with no interoperability in mind
The issues begin with how healthcare software was originally built. Most of the healthcare systems were designed not to share data easily. Some of the biggest EHR software companies, like Epic, used in many hospitals in the USA, control a major share of the market.
Reports and lawsuits have raised concerns that some vendors make it quite difficult for outside platforms to access patient data.
Vendors treat health data as a kind of business advantage. The more data they keep inside their system, the more valuable their platform becomes. This is one of the key reasons EHR interoperability challenges continue to persist.
Compliance and interoperability are serious
There are already existing rules for sharing healthcare data. The 21st Century Cures Act (2016) made it illegal for organizations to block access to electronic health records without a valid reason.
This act also pushed the healthcare systems to use a standard way of sharing data called HL7 FHIR (Fast Healthcare Interoperability Resources). This is a modern system designed to help systems exchange health information.
In practice, many organizations implement FHIR APIs in a limited way to meet regulatory requirements instead of enabling full data sharing access between systems.
In this way, healthcare systems may be technically compliant, but still struggle to exchange patient data. Incomplete patient records can lead to medical errors and inefficiency in care delivery.
The trust problem that technology cannot solve
Despite FHIR APIs in place and the availability of data, healthcare data still does not move smoothly due to trust issues among organizations. KLAS EHR interoperability report shows that trust is a bigger hurdle in sharing data than technology between payer and healthcare organizations. So, the real concern is how organizations work together, not technology.
Hospitals and insurance companies need clear agreements to share patient data. They must decide on who is responsible in case something goes wrong, who will protect the data, and how it will be protected.
These decisions are handled through legal contracts and a proper approval process due to the differentiation in insurer and hospital goals.
Fragmented data is blocking AI before it starts
Many companies that try to build AI tools for healthcare face the same issues: a lack of data or data that is not ready to use. AI requires clean and complete information to perform well. According to CHIME Digital Health Insights, many healthcare organizations are still not fully prepared to use their data for AI.
This is a serious concern because if an AI tool has partial access to a patient’s medical history, it can make wrong or incomplete predictions. Similarly, if different hospitals use different ways to record the same information, the AI can be refused and produce unreliable results.
The problem is not the AI itself; it is the poor quality and incomplete nature of the data. Cloud platforms like AWS, Azure, and Google Cloud can store healthcare data safely, but they cannot fix messy or missing data. If the original data is broken, it will stay broken even in the cloud.
What Meaningful Progress Actually Requires
Rules regarding healthcare data sharing are getting stricter. In 2025, the U.S. Department of Health and Human Services (HHS) increased enforcement against information blocking, which is when systems make it hard to access or share health data.
EHR developers can face a fine of $1 million per violation. Healthcare providers can also risk losing Medicare-related payments if they block access to information. In 2026, regulators have also started issuing warnings about API performance issues and possible violations.
No single company can solve interoperability on its own. Hospitals, insurers, and software vendors all need to work together. This requires shared rules, clearer responsibilities, and better incentives for companies to actually share data.
For companies building healthcare technology, this is important. The pressure to improve data sharing is increasing, old barriers are weakening, and the system is slowly becoming more open than it has been in years.
The Bottom Line
The healthcare data problem is not a technology problem; there are already cloud systems, and software exists. The real issue is that data has stayed locked inside the separate systems because of business incentives, legacy software, and a lack of trust among organizations.
This is now slowly changing as regulations become stricter and the cost of poor data sharing becomes harder to ignore. Billions are wasted every year due to inefficiency and duplicate work, showing the system is not sustainable.
At the same time, AI and digital health tools depend on connected data. As pressure increases to fix these issues, the industry is moving toward better data sharing, but progress is still gradual.
