Published by Jessica Weisman-Pitts
Posted on May 10, 2022
6 min readLast updated: February 7, 2026
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By Jon Payne, Manager – Sales Engineering, InterSystems
As the healthcare industry continues on its digital transformation (DT) journey – which has only accelerated since the start of the pandemic – there is a lot it can learn from other sectors that have trodden a similar path. None more so, perhaps, than financial services. Both sectors have been under pressure to digitise at a faster pace, but they are also operating in highly regulated environments that have been quite siloed historically.
Changes to the way they are regulated is now helping to grease the digital wheels of these industries. In financial services, Open Banking was introduced in 2018 and this has really helped to level the playing field for new market entrants by facilitating the secure sharing of customer data between companies. Now, a similar change is about to take place in healthcare. From July 2022, all 42 Integrated Care Systems (ICSs) across England are set to become new statutory bodies. This will represent a significant shift in how health and care services are planned and delivered – away from the model of fragmentation and competition followed in previous decades and towards one of collaboration between services.
However, for healthcare to capitalise on these organisational changes, the industry must start putting the right technology in place. Proper integration and innovation rely on the encoding, processing, and analysis of vast and complex data sets, comprising millions of datapoints that currently live in online and offline environments. The financial services sector – which is a few years ahead of healthcare in its DT journey – has already made great strides here, leveraging data through technology to drive cost-savings, create new products and services, and attract new customers. As we now approach a major development in the provision of healthcare, here are some of the learnings the industry can take from financial organisations, to facilitate a similar outcome and set itself up for success:
1. Championing interoperability
The advent of Open Banking in financial services meant that banks were mandated to open up their application programming interfaces (APIs), allowing third parties to access financial information needed to develop new apps and services and providing account holders greater financial transparency options. However, a lack of standardisation between APIs has meant this has not, to date, provided the data liquidity the industry had hoped for. By contrast, in healthcare, there are institutions like HL7 and IHE that are extremely focused on true interoperability and, by and large, they’ve got the support of healthcare organisations and suppliers too, who understand that it may solve some of their own technical problems. Although there are still limits to how far some suppliers want to go when it comes to data sharing, the NHS is asking, and they are listening.
However, the NHS is a complex web of institutions and this, rather than the technology itself, is the single biggest barrier to interoperability across all its interconnecting organisations. To facilitate data sharing, it needs to adopt a flexible attitude to technology and standards, to ensure one can support the other and that budgets can be used effectively to achieve interoperability in months not years and without then causing technical debt in connecting areas. Digitalisation of Transfer of Care stalled, for example, because the definition of standard was so complex that people found it extremely hard to implement.
2. Using AI to optimise existing workflows and make better decisions
Financial services has embraced Artificial Intelligence (AI) to drive down the cost of doing business and reduce risk by minimising the number of people processing transactions and interacting with customers. It has also allowed organisations to make predictable decisions based on data. As an industry, financial services investment in IT generally, including in AI, is much greater than in healthcare, certainly as a percentage of its overall budget. Most organisations see competitive advantage in having the best algorithms or systems and most efficient route to execute in business. To that end, every major bank has got a significant data science team and many of these teams are now putting in place AI Ops – a DevOps pipeline that’s all about deploying AI models into businesses. Having tools and platforms that can support the rollout of updated models is key to making AI an integral part of the business.
Although budgets are certainly leaner in healthcare organisations across the NHS, the premise is the same. AI can greatly improve the way in which we arrive at recommendations for clinicians and elevate care. What is needed is a loop that helps to rapidly and appropriately surface data in a useful form from operational systems into machine learning environments, and then feed the output back into the operational flows. Making that easy and practical is key to making AI useful in a common healthcare setting.
3. The security and protection of customer or patient data at all costs
Healthcare organisations are keen to ensure that their data is open and accessible but there are also ongoing concerns when it comes to data security, privacy and governance – much like in financial services. A string of recent high-profile incidents of data loss in both the public and private sectors has only exacerbated this. Getting data protection wrong can bring commercial, reputational, regulatory, and legal penalties. So understandably certain tech innovations must be approached with caution. This is one reason why cloud adoption, for example, is still run on premise or in a private cloud, rather than a public one.
Like healthcare data, financial data is sensitive and highly regulated. To avoid falling foul of the regulations it’s imperative that, like financial services firms, healthcare organisations implement robust data governance strategies and compliance frameworks well before tech innovations are deployed.
As the healthcare sector approaches its upcoming shift in how health and care services are planned and delivered, it’s crucial that individuals and organisations alike take the opportunity to look outwards. There’s a wealth of insight to be sought from other sectors that have trodden a similar path, and I certainly look forward to what DT goals could be achieved through greater, cross sector collaboration and knowledge sharing.
Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems, enabling them to perform tasks like decision-making and problem-solving.
Data security involves protecting digital information from unauthorized access, corruption, or theft throughout its entire lifecycle, ensuring confidentiality and integrity.
Digital transformation is the integration of digital technology into all areas of a business, fundamentally changing how it operates and delivers value to customers.
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