Pathology consolidation and innovation to drive efficient patient care
David Wells, Head of Pathology Services Consolidation at NHS Improvement has produced a blog on Pathology consolidation and innovation to drive efficient patient care exclusively for the UK Diagnostics Summit. Within the blog David outlines how NHS Improvement are driving the networking of pathology services in England and developing shared learning.
By 2030 outcomes for patients with chronic diseases will be transformed with their earlier diagnosis. That was the announcement by the Prime Minister on 20 May 2018. To achieve this – earlier diagnosis of 50,000 cancer patients each year and as a result a predicted 22,000 fewer cancer deaths each year – the NHS will need to lead the world in the use of diagnostics, health data, artificial intelligence and innovation in pathology. Patients potentially requiring intervention will be targeted in a proactive risk-based approach to diagnosis.
A personalised approach to healthcare is the minimum we should expect from the digital revolution to drive earlier and faster diagnosis – and it should be the standard across all aspects of diagnostic healthcare, not confined to the high-profile arenas of genomics and cancer.
NHS Improvement is driving the networking of pathology services in England to create the essential infrastructure to make this a reality. In September, we published an operational productivity report on consolidating the country’s pathology service into 29 pathology networks and have since been supporting providers to make the necessary changes for a sustainable, high quality, clinically focused pathology service in England. These larger networks will mean all patients, irrespective of where they live, have access to specialist expertise. Network working ensures consistency across multiple centres (in protocols, equipment and workforce) and boosts service resilience: if one laboratory is out of action for whatever reason, others will maintain the service. This scale also means laboratories can provide a wider repertoire of tests using best methods as the optimum equipment can be purchased. The latest sequencing technology or point of care technology (POCT) equipment becomes affordable when it serves a larger population.
Figure 1 – 29 Pathology Networks
We have issued toolkits to share learning and provide best practice advice and guidance, and continue to work with providers, arm’s length bodies, professional bodies and industry experts to help all parts of the system together achieve this change. This includes work in genomics, antimicrobial resistance, screening, workforce, digital/AI innovations and other innovative technologies. We want one change to a truly interoperable system that will deliver on the national challenge to diagnose disease earlier and improve patient outcomes.
Every acute and specialist acute trust in England is engaged in the networking programme. Several networks are already working at the scale we proposed and by the end of this financial year we expect a third of the 29 networks to be formed.
We will also need to consider the benefits to the workforce. Training opportunities are more consistently available when services cover larger populations. The medical workforce in certain disciplines within pathology is in short supply and biomedical and clinical scientists are well placed to adopt new and innovative roles to deliver a high quality timely diagnostic service to patients. This is an opportunity to put into place the advanced roles envisioned by the modernisation of scientific careers programme and ensure that all staff work to the top of their capability.
The future advances in diagnostics will be in using data science as much as innovative technology. This will need to be supported by clinical experts to provide clinical advice and support tools to shorten pathways to diagnosis, referral and treatment. To deliver this, healthcare systems need to have a high degree of connectivity, messages must be standardised and be platform agnostic. The data needs to be accessible for immediate patient care and allow for long term monitoring that can provide insight to clinicians that truly personalises care.
Some of this benefit will come from being able to work with industry, developing the integration tools and the diagnostic algorithms. The UK has the almost unique benefit of being able to collate population and outcome data that other healthcare systems cannot, providing for powerful statistical models to robustly test and validate these new clinical tools and approaches. This approach is slowly being evidenced by teams demonstrating the value of using data (demographics, biomarker, clinical information) to identify unique patients from both diagnostically ‘sick’ and diagnostically ‘well’ patients. Developing the IT and digital infrastructure within pathology will enable academic healthcare science networks, exemplar centres, pathology and genomics networks working with industry partnerships to provide a springboard that will position the UK as a leader in diagnostic healthcare. NHS Improvement will continue to support and drive this networked reconfiguration and digitisation for improved patient outcomes.
This change is fundamental, and it is challenging, but when you think of the benefits to patients and the broader population we can see the moral imperative of challenging the status quo. If 100% of cancer patients had their diagnostic result reviewed by the most appropriate clinician within 28 days, it would improve the speed of diagnosis of more than 5,800 patients. Use of big data and AI will enable clinicians based in the most suitable setting to refer patients into the correct clinical pathways. The clinical time saved by working smarter could support additional life-saving screening programmes such as screening for lung cancer. Detecting the disease earlier could bring the five-year survival rates from 5 in 100 to 1 in 3. All patients would receive the required diagnostic tests to support a personalised response to their care which can include identifying appropriate chemotherapy – for example, we are now able to target some children’s brain tumours to ensure we use the most effective treatment and minimising unwanted and toxic side effects. This digital and AI capability will give the life science sector access to considerable data, so far unavailable at the scale proposed, to further develop and advance machine learning and AI at a world beating pace. The future of diagnostics is being enabled now, it is our task to deliver it, by developing networks at pace to provide the core infrastructure and also striving for innovative solutions within diagnostics.