Why siloed data is stalling the future of smarter healthcare
Healthcare innovation is brandished around as if it permeates the system at every corner. But what is the use of innovation if our foundational systems are stuck between the old and the new?
This is the reality at most hospitals and clinics. Behind every digital promise lies a patchwork of isolated and fragmented systems that cannot communicate with one another.
The cost of disconnected data
Siloed data is one of the most significant, yet overlooked, barriers to healthcare growth today; limiting doctors’ capacity to care for patients, diminishing hospital efficiency, and capping the speed at which breakthroughs like AI may be adopted at scale.
The true cost of fragmented data is felt by the patients themselves. Decades of inconsistent and incoherent digital records force patients to move between hospitals, bringing an assortment of physical and digitised notes with them from one visit to the next. Missing patient data forces medical professionals to repeat costly scans and diagnoses, further clogging waiting rooms.
These inefficiencies don’t just cause treatment delays and confusion, they create additional work, intensify administrative dissatisfaction, and leave behind them a wake of burnt out healthcare workers.
Disconnected data, too, stifles research and innovation. Healthtech businesses developing AI tools or predictive analytics must manage standalone datasets with varying standards and permissions, resulting in breakthroughs that seem promising in trials, but which fail to scale throughout the system.
A structural problem, not just a technical one
Many view interoperability as merely a technical hurdle, but it is much more complex. The absence of interconnected data is a fundamental issue that modifies the operation of healthcare systems. When information cannot be shared securely and easily, it hinders collaboration among professionals and confines critical insights within individual institutions.
Throughout my experience in the NHS and in healthcare consulting, I have observed the strong spirit of collaboration that exists within hospitals. On a busy Saturday night shift in London’s A&E halls, I might see a dislocated shoulder, someone with a suspected heart attack, and a stabbing within the first two hours. There is no way I’d have been able to provide the best care without leaning on my colleagues: the orthopaedic, cardiac, and trauma specialists.
But that knowledge and data sharing is a luxury only afforded to clinicians working in frontline care, in hospitals largely located in large urban centres and cities. At the primary care level, this support network becomes less robust.
GPs often find themselves working alone, lacking a seamless method to lean on specialist colleagues for support, just like I did. It increases referrals to hospitals or specialists and only further perpetuates the strain on healthcare systems.
Establishing comprehensive connectivity would not only enhance efficiency, but also ensure that expertise and insight are distributed more evenly across the system. What if that GP who’s unsure about a patient's ailment could message a specialist for advice in real-time? Referrals would fall massively, treatments could be administered locally, and the strain on frontline care would be lifted.
How AI can connect the dots
AI cannot fix fragmented healthcare alone, however it can work as a link to facilitate the flow of data across boundaries. As healthcare makes the transition from legacy to modernised systems, AI-driven platforms can link different datasets and provide clinicians with a real-time, holistic view of a patient’s health. For example, by integrating primary care records with hospital data and results, an AI system can flag potential risks before symptoms escalate.
While the technology already exists, the infrastructure that lets it operate seamlessly is currently missing. However, with the advent and subsequent rollout of AI transcription and diagnosis technologies, I believe we are close to finding the glue that’ll marry our mishmashed systems together.
Building trust through connection
While there is, of course, concern that sharing data more widely must come at the expense of privacy, in reality, the opposite is true. When systems are designed to talk to one another properly and efficiently, information can be shared securely. A clinician who has access to all the relevant health data is a clinician more adequately prepared to carry out effective treatment.
Better connection also strengthens trust. Patients are more comfortable engaging with digital tools when they understand how their data is being protected and how it’s helping their care. While a digital data transition may seem daunting, patient confidence in the systems is critical if AI-driven systems are to be used safely, responsibly, and to their full potential.
A vision for the future
Imagine a healthcare system where every clinician has secure, instant access to the information they need – whether that be through real-time clinician support networks or joined-up historical and modern data. A system where AI supports early intervention, where patients no longer repeat the same tests, and where care pathways are connected from start to finish.
That vision is within reach and the appetite for change is growing. What’s needed now is collective commitment to connect the dots, between hospitals and GPs, between public and private systems, and between data and decision-making.
Healthcare has always been built on collaboration. It’s time our data caught up.
About the author
Dr Sonia Szamocki is founder and CEO at 32Co, a leading UK healthtech company connecting clinicians to perform specialist care at high street practices. Dr Szamocki is a former NHS doctor, trained at Oxford University and practicing at some of the world’s leading teaching hospitals in Emergency Medicine. Dr Szamocki's experiences in healthcare inspired her to create 32Co, realising that access to novel or specialised treatments is restricted by the small population of clinicians qualified to offer the treatment.
