By Bernard Place
Health Minister Tom Binet is facing a busy autumn. The Budget debate last month saw him asking for significantly more resources for baseline funding, preventative healthcare and digital development. He is also taking forward new governance arrangements with the creation of a partnership board to guide future system-wide planning, while continuing with the current Health and Care Jersey Advisory Board. Finally, he must oversee a new health and social care strategy, underpinning developments including the New Healthcare Facilities Project.
Each challenge is substantial in its own right. But they also hang together: failure in one will weaken the others. Predictive analytics – the use of health data to spot risks, target resources and reduce waste – offers a way to align these priorities, making them more coherent and achievable.
The Jersey Care Model
Health’s previous strategy, the Jersey Care Model (JCM), launched in 2020, aimed to shift more care into the community and prepare for the needs of an ageing population. Its intention was sound. But the official review in 2022 made clear that ambition alone was not enough.
Projects were rolled out piecemeal, without a clear story Islanders could follow. Patients and professionals were often confused. Some feared responsibility for complex care was being shifted to charities and volunteers.
The model also lacked robust evaluation. Ministers and the public were told community services would reduce hospital pressure and save money, but the review could not confirm whether savings were real. Services such as Physiotherapy First or Telecare showed promise, but there was no systematic way of measuring impact or ensuring lessons were learned.
In short, the JCM faltered not because its direction was wrong, but because Jersey lacked the tools to measure outcomes, track costs, and demonstrate value for money. That gap was fatal.
Predictive analytics
Elsewhere, health systems have addressed this challenge by adopting predictive analytics. Kaiser Permanente, one of the largest integrated care providers in the US, has for more than two decades used data to anticipate risks and guide its work.
In plain terms, predictive analytics means using data to see what might happen before it does. At Kaiser, algorithms monitoring patients’ records can warn doctors up to 24 hours before deterioration, reducing deaths and intensive care stays. Predictive tools cut hospital readmissions by 20% and halved antibiotic use in newborns. They also expose waste – unnecessary treatments, duplication and inefficiencies.
The scale is far larger than Jersey. But the principle is transferable: use the data you have to prevent crises, target resources and identify waste. That is exactly what Jersey needs now.
- Challenge one: Budget and resources
This autumn, the Health Minister will ask the States Assembly for significantly more funding. Islanders will expect that extra money to buy not just more services, but better value. Predictive analytics can help meet that test.
Our health data is currently fragmented by the use of three different patient administration systems. GPs use EMIS, the hospital uses IMS MAXIMS, and adult social care uses Care Partner. Patients often repeat their story to multiple professionals. By combining these datasets into a shared system, Jersey could start to model demand and cost across the whole system, showing clearly where resources are wasted and where they make the most difference.
Predictive analytics would allow us to discipline spending: to identify duplication, target investment in prevention and reduce expensive hospital admissions that could have been avoided. Crucially, it could also show which preventative measures genuinely deliver savings. For example, smoking cessation or falls prevention may reduce costly admissions – but only robust data can prove this. In a tight budget settlement, such insight is vital: it allows us to back the interventions that work and quietly drop those that do not.
This is not just about efficiency – it is about maintaining public trust that increased budgets are being spent wisely. And once that investment is secured, it must be governed carefully.
- Challenge two: Governance and the partnership board
The creation of a new partnership board is an important step. Predictive analytics should be a standing item on its agenda, providing a transparent, evidence-based view of system performance.
If Islanders are to believe that governance reforms are more than a reshuffle of committees, they need to see that decisions are guided by real evidence. Predictive analytics can provide that evidence: which services are delivering outcomes, which are not, and where improvement is most urgent.
In this way, the Budget challenge and the governance challenge are linked: the former secures resources, the latter ensures those resources are deployed with discipline. Yet both will fail unless they are anchored in a clear long-term plan for services and facilities.
- Challenge three: New strategy and facilities
The forthcoming health and social care strategy, together with the New Healthcare Facilities Project, represents Jersey’s biggest investment in a generation. But new buildings alone will not solve our challenges. Without a clear focus on prevention and efficiency, we risk simply expanding costly hospital-based care.
Predictive analytics can help avoid that trap. By modelling demand and outcomes, we can design services that reduce avoidable admissions, speed safe discharge and strengthen community care. In turn, the new facilities can be planned and used in ways that deliver value across the system, not just in bricks and mortar.
Artificial intelligence may also help, building on predictive analytics to spot patterns invisible to the human eye. Used carefully, AI could support earlier interventions, more personalised treatment and better planning. But it will only succeed if coupled with clear communication and trust-building. Islanders must see these tools as aids to care, not distant algorithms.
Cautiously optimistic
Looking back, the Jersey Care Model was right to aim high, but it failed to prove its value or carry the public with it. Looking forward, predictive analytics offers a way to tie together the minister’s three major challenges: disciplining spending in the Budget, supporting evidence-based oversight in governance and ensuring new strategies and facilities focus on prevention and efficiency.
I have seen first-hand how difficult it is to make health strategies succeed. Islanders are sceptical after the pause of the JCM, and rightly so. But if we learn from others, integrate our data and use predictive analytics wisely, Jersey can move from ambition to accountability – and give Islanders a system that is not just bigger, but smarter.
A registered nurse for nearly 40 years, Bernard Place has been a clinician, teacher and researcher in intensive care units. From 2012 he managed departments in Jersey’s healthcare system and from 2015 to 201
