Jon Payne, manager – sales engineering at InterSystems, discusses how implementing a long-term data strategy from the outset, centred around achieving interoperability and compliance with industry standards, can allow start-ups to scale at ease, and prepare for future uptake and widespread adoption.
The UK has become a hub for innovation in health technology and life sciences. Now the second largest subset of the thriving tech sector, healthtech is worth £36 billion and employs 132,000 people. Investment in UK healthtech has long been the highest in Europe, yet the industry’s key role in developing practical solutions to help the NHS with innovative digital tools during the COVID-19 pandemic has propelled this venture capital to new heights. 2021 saw a record £2.87 billion pumped into UK start-ups and scale-ups, a ninefold increase on 2016 figures.
For any ambitious healthtech start-up, the time is ripe to scale up and achieve real growth. However, critical challenges lie ahead: even the most innovative and entrepreneurial companies often find themselves incapable of allowing data to flow quickly and reliably between their devices and external health systems. Start-ups that fail to launch from a more effective data platform can stumble before they even begin to walk.
James Pike James Pike
Intersystems, tech Summit, the Belfry, 2017
Companies offering advances in diagnosis and treatment must integrate their own data with the abundance of clinical data that already exists and learn how to share with other systems and organisations. This is why interoperability must form the backbone of any robust healthcare strategy.
Start-ups must prioritise the seamless movement of data to support patient outcomes
Interoperability is often overlooked in the excitement of getting a business started, yet it is key to getting healthtech start-ups off the ground. Without the necessary interoperability, they are unlikely to move out of the pilot stage, especially in the NHS. In England and Wales, the NHS has been highly effective in introducing mandatory data standards HL7 V2 and FHIR governing interoperability, to which any applications must adhere. Although start-up owners and creators have compelling ideas and strong business plans, they often fail to fully consider the challenges of scaling and interoperability that such standards present.
Scaling is much easier when a company starts with a well thought-through data strategy early on, preparing for the requirement for data to be secure, available, and compliant. The ability to easily share data between healthcare organisations and clinical systems ensures a greater level of co-ordinated care and improved patient outcomes.
The contemporary world of healthcare is increasingly driven by data, and any solution incapable of full interoperability is likely to fail. Healthcare providers are relying on healthtech companies to resolve the data challenges themselves. What they want are improved outcomes and reduced costs, and solutions that optimise the work of healthcare professionals.
While many start-ups possess the energy and vision of entrepreneurial talent, they often lack the experience of healthcare culture, data, and standards. To deliver on expectations, start-ups need to set off with healthcare organisations’ requirements at the forefront of their strategy. This requires developers to have an intimate understanding of healthcare systems, interoperability, and regulatory compliance.
Getting to grips with the complex health data standards landscape
Anyone entering the healthcare domain must understand the standards landscape. The very active standards bodies, including HL7, ASTM, DICOM, and IHE, know the importance of both data models and associated message patterns. Start-ups need to become familiar with these requirements and build compliance into their solutions.
One mistake that new healthtech businesses commonly make is to dismiss current configurations as legacy, inefficient, or part of a failed project. This way of thinking is fundamentally flawed given that most applications depend to some extent on data being collected from other applications. For a solution to be successful, it is necessary for data to be pulled from multiple data sources, some of which will use legacy standards and others which will be operating to the new requirements.
The latest HL7 standard, Fast Healthcare Interoperability Resources (FHIR), is specifically designed to be RESTful and provide a simple framework for both system-to-system implementations and application developers. All future interoperability projects will need to support FHIR: Apple Health for example, uses FHIR data to power integration with healthcare providers. New product offerings that include the capability to support older standards, other APIs, and non-standard interfaces, would increase the ability to fit into any architecture.
The power of a single platform strategy
Resource and time constraints mean that achieving this level of interoperability swiftly and cost-effectively is beyond most start-ups. However, a solution does exist. Building applications on a third-party data platform which encompasses interoperability, the ability to orchestrate multiple interfaces, high-speed data storage, and “in-flight” data transformation, offers a wealth of benefits.
Firstly, this approach relieves data scientists of the burdens of cleaning and preparing data. Moreover, a data strategy built on an established, specialised health integration platform allows start-ups to address a far greater number of interoperability use cases. Such capabilities can be enhanced further when combined with the ability to provide real-time analytics, such as insight into usage patterns and performance.
A unified platform also eliminates the need to integrate multiple technologies and toolsets. This not only reduces the amount of code that needs to be developed and tested but can also significantly reduce the time-to-market. In-house developers are free to focus solely on evolving their product or service offering. Evidence suggests data scientists at start-ups currently spend as little as a fifth of their time on analysis, so shifting to a single platform strategy will allow for more efficient working.
Wireless technology, miniaturisation and computing power are evolving at pace, leading to the increasing acceptance of digital health solutions by clinicians and patients alike. For ambitious start-ups at the beginning of their journey, a commitment to solving the basic, fundamental requirement for data interoperability will pay dividends in the long run.
Deloitte has identified interoperability as “arguably the biggest challenge” in the medical technology sphere. Whatever their achievements in diagnosis and treatment, start-ups must set out with a robust and astute data strategy that does not leave them incapable of working in full harmony with existing and future healthcare systems.
As healthtech start-ups develop new applications and seek to stand out from the crowd in a booming market, interoperability is sure to be key to their longevity and success. From the very outset, companies must ensure that their solutions can neatly fit within existing infrastructure. This can be realised through a single data platform designed to achieve interoperability and full integration with health systems and standards.
