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It was back in the 1960s when the introduction of Electronic Health Record (EHR) systems allowed a full clinical picture of an individual’s health data to be collated into one place. With the promise of improved care coordination from doctors, we looked set for improved diagnosis and treatment regimens across the patient pathway. But here we are, more than 50 years on, still failing to facilitate the free flow of data between silos that is necessary to deliver the desired impact. In my opinion, there can be no more excuses. We have the tech, we have the standards, we simply need to find the will to work together to make it happen. The failure to grasp the opportunity for efficient healthcare data interoperability can be traced to those early years of EHR development. With a lack of mandatory interoperability standards, each provider built and maintained their silo, often with accessibility limited to hospital or even department-specific practitioners enrolled in the program. The business value lay in the data that resided and grew in those repositories, alongside powerful analytics that provided profound clinical insight for patient management. The course was set: complex and disparate EHRs all unable to communicate or use APIs to transfer data to and from each other’s platforms.
“Notable advancements in information exchange are now possible, but only if there is a willingness to embrace the interdependency of technologies such as AI, FHIR, and 5G”
Healthcare systems can no longer afford to endure the fragmentation that persists. The needs and expectations of our ageing patient population are changing faster than ever before, and honestly our healthcare systems can’t keep up with the demand for high-quality care. As a result, systems across the world are creaking at the seams and being forced to go through unprecedented change. The estimated need to add 18 million healthcare workers by 2030 to cope with growing requirements is just not sustainable. It takes approximately 10 years for a physician to train sufficiently to be truly impactful in their specialty. It is simply not possible to find, train and recruit enough surgeons, nurses, PCPs and other healthcare professionals in the next decade and this is compounded by increasingly complex therapies requiring more specialties. But done right, and empowered by cooperation, technology can allow us to support more patients with personalized treatment.
The Fast Healthcare Interoperability Resources (FHIR) standards were developed by Health Level Seven International (HL7) to facilitate interoperation and cooperation between legacy healthcare systems and ease the flow of information to providers and individuals via multiple devices. They also allowed third-party developers to create apps that can be easily integrated into existing systems. Apple’s Health Records launch incorporated FHIR, and nearly 150 hospitals have signed up. At the same time, EHR makers such as Allscripts, Athena health, Cerner, eClinical Works, Epic, and Medi tech have developer programs that use FHIR and open APIs to enable third-parties to write software that uses their platforms.
We are now at a tipping point with initiatives such as the backwards-compatible FHIR 4 standard and the finalized information blocking rule from the US Department of Health and Human Services. Notable advancements in information exchange are now possible, but only if there is a willingness to embrace the interdependency of technologies such as AI, FHIR, and 5G. The move to open platforms requires a significant cultural mind-shift by the industry, practitioners and patients. Attitudes to data transparency, sharing, and security may be partly generational. But blockchain initiatives such as Mint Health are still essential to incentivize patients to share their genomic, health and well-being data. Integrating these into the EHR will help clinicians make better-informed care decisions. Third-party contextual data feed, meanwhile, need to be analyzed alongside native information in the EHR to deliver unique insights into the individual. The approach is already working in pharmacogenomics, where clinical papers, genomic variant information, and the EHR are all analyzed by AI. It informs the correct treatment regime, exposes potential adverse drug effects, and generates a care plan tailored to the individual’s genetic makeup.
It is clear that healthcare systems are undergoing a radical change as a result of increased demand, and the sophistication of new technologies like AI, cloud-based software as a medical device, robotics and POC diagnostics. Data is the glue that links these technologies together, and through interoperability, we have both the tools and opportunity to reduce the burden on both healthcare systems and patients.