Using System-Wide Insight to Support Care Closer to Home

Executive Summary

The Challenge: Canterbury District Health Board (New Zealand) was facing rising demand, an ageing population, constrained hospital capacity and fragmented services.

The Intervention: The system used shared operational intelligence powered by our Health Insights platform to understand demand, variation and patient flow across the whole pathway, supporting more joined-up decisions between primary care, secondary care, ambulance services and community teams.

The Result: Canterbury’s wider improvement programme reported faster decision-making, more care delivered in community settings and reduced pressure on acute services. Reported outcomes included 1.5 million fewer days of patient waiting time across measured areas, almost 20,000 patients cared for in community settings in one year and significant reductions in COPD admissions, readmissions and bed days.

This case study reflects work originally delivered by Lightfoot Solutions, whose analytics capability now forms part of Kensa Health Analytics.

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Clinical Context and Objectives

Canterbury District Health Board in New Zealand had been working for more than a decade to redesign care around the needs of its population.

Like many NHS systems in the UK, Canterbury faced a difficult combination of rising demand, limited capacity and growing pressure on hospital services. The system recognised that simply adding more reports, targets or isolated improvement projects would not be enough.

It needed a clearer way to understand how the whole system was behaving, where pressure was building and which interventions were most likely to improve outcomes.

The objective was simple: support people to receive the right care, in the right place, at the right time.

As Carolyn Gullery, General Manager for Planning and Funding at Canterbury District Health Board, described it:

“The whole system needs to be working for the whole system to work.”

The Decision Problem

Canterbury did not lack data. It lacked a shared way to turn that data into decisions.

Teams were often working from proxy measures, retrospective analysis and fragmented information. This made it difficult to agree what was really happening across the system, what was driving demand and where action should be focused.

Greg Hamilton, Manager Planning and Funding at Canterbury District Health Board, explained the challenge:

“We had no joined up robust data so no insight, just proxy measures and anecdotes.”

The Approach

The work focused on creating a more connected view of the health system.

Rather than looking at individual services in isolation, Canterbury used operational intelligence to understand:

• demand across the system
• variation across pathways
• patient flow between services
• where pressure was building
• which cohorts were driving activity
• whether changes were having the intended impact

This helped teams ask better questions, test assumptions and identify the real drivers of operational pressure.

A key benefit was speed. Instead of waiting weeks for further analysis, teams could use current data in workshops to explore problems and agree next steps.

Simon Berry, Lead Analyst, Planning and Funding at Canterbury District Health Board, described the difference:

“In a single morning workshop, Health Insights can dig in and find the detail to answer any questions on the spot.”

In some cases, the evidence helped reduce four to six weeks of decision-making discussion by allowing teams to identify the real issue during a meeting and move directly to planning a response.

Supporting Care Closer to Home

The insight was used to support practical pathway redesign, not just performance reporting.

Canterbury’s wider improvement programme included:

• acute demand management to help people receive appropriate care outside hospital
• CREST community reablement, supporting people after discharge or helping them avoid admission
• COPD pathways designed to help people stay well at home
• community-based falls prevention
• stronger coordination between ambulance, general practice, acute care and community services

This helped Canterbury move beyond hospital activity as the main measure of performance. By understanding demand, flow and outcomes across the whole system, teams could focus improvement work on keeping people well at home, reducing avoidable acute demand and freeing up hospital capacity.

Outcomes and Impact

Reported outcomes from Canterbury’s wider improvement programme included:

• 1.5 million fewer days of patient waiting time across four measured areas
• almost 20,000 patients cared for in community settings in one year, avoiding a hospital stay
• 95% achievement of the six-hour discharge or admit target
• 896 fewer COPD admissions over six years compared with expected levels
• 9,937 fewer COPD bed days
• 296 fewer acute COPD readmissions
• 981 fewer people admitted to hospital with fractured neck of femur
• 66,881 fewer neck of femur bed days

A More Resilient System

The value of Canterbury’s connected model became especially clear following the 2011 earthquake, which placed extreme pressure on local health and care services.

Because new initiatives, shared ways of working and evidence-led planning were already in place, the health system was able to continue operating despite major disruption, including reduced hospital and aged residential care capacity.

The lesson was not simply about crisis response. It showed the value of a system that can understand demand, coordinate action and adapt under pressure.

Relevance for NHS Systems Today

Canterbury’s experience remains highly relevant to the NHS today.

Integrated Care Boards, Trusts and local partners are being asked to improve flow, shift more care closer to home, reduce avoidable acute demand and make better use of constrained capacity.

To do that, systems need more than retrospective reporting. They need a shared view of demand, variation, flow and outcomes, and a way to understand whether interventions are making a measurable difference.

That is the principle now carried forward through Kensa Analytics.

Kensa Analytics helps NHS leaders turn complex system data into clearer decisions, supporting earlier intervention, stronger operational grip and more confident planning across care pathways.

Conclusion

Canterbury shows why system-wide decision support matters.

When leaders can see demand, flow and variation across the whole pathway, they can act earlier, invest with greater confidence and redesign care around the needs of patients.

While the work was originally delivered by Lightfoot Solutions. Today, that analytical capability forms part of Kensa Analytics, supporting our focus on helping health systems understand what is changing, why it is changing and where action will make the greatest difference.

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_{Image: Christchurch Hospital, Christchurch, New Zealand 03, Michal Klajban, CC BY-SA 4.0}

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