The Future of Health Data in the UK: What HCPs need to know

The National Health Service (NHS) in England will shortly begin an open procurement process for a “Federated Data Platform,” a new data system designed to enable transformational healthcare change in a range of areas, including population health, waiting lists, care coordination, vaccines, and supply chain.

The Federated Data Platform will solve several items, including; population health, care coordination, and supply chain among them – through the promise of data liquidity, machine learning (ML), and Artificial Intelligence (AI). These new technological capabilities have shown promise but have led to questionable insights and even moral and ethical concerns– compounded by staffing shortages and data transparency concerns.

In our continuously evolving technical world, too often, we focus on IT efforts and forget about the people who really need the IT (and data) to work for them, like caregivers, coordinators, and schedulers. New data insights need to drive renewed confidence in data-driven decisions and actions– by those who need data most. They need a seat at the table from the beginning.

Healthcare data produced by individuals and their caregivers should be owned and used for the benefit of individuals and caregivers. While there have been incredible advancements in vaccines and other care delivery equipment through the use of data and AI, it should be the individual or caregiver who benefits from that sale in the form of improved access, reduced care costs (taxes, insurance premiums, etc.), and more innovative services. For healthcare to transform, we must include those most impacted in decision-making and outcomes.

A preliminary solution: A single source of truth

Today, critical data about patients, providers, facilities, and supplies are often maintained in different systems with different backend databases that support specific business functions. Business functions such as maintaining clinic locations, hiring providers, scheduling patient visits, conducting assessments, and administering medications (the list goes on) each have their own highly specific and complex workflows and business users. The applications were developed over time by different companies, using different technologies, and often don’t easily integrate.

To bridge these gaps, most organizations developed some version of an Enterprise Data Warehouse (EDW) to pull together data from these systems for the purposes of reporting and analytics. EDW deployments certainly helped address the basic needs for consolidated reporting but have been slow to build and hard to maintain. They don’t readily scale to modern data types and use cases requiring additional tools to be implemented, such as data lakes, interoperability tools, and more. All of these different applications and data analytics toolsets offer individual value today, but they often want to be the new “digital front door” or controller of the whole experience, thus creating and persisting the data silos.

To be successful in the new world of AI, ML, and analytics, organizations need to get all of the data aggregated into a single location to allow that data to work together to tell a story. New advancements in technology need to be utilized in such a way that they complement human decision-making while inviting collaboration. Breaking down the silos is a critical first step but not the only element to remember.

Surfacing the data will generate easy use cases such as shortening elective wait times (which NHS England has started to use recently) and managing outpatient services across many specialties with benefits for patients and staff. These successes will motivate teams to tackle broader-based population health areas such as diabetes and acute heart failure management, and this is exactly why looking at early use cases is vital for overall success.