The insidious burden of chronic disease has been growing for decades draining resources, expanding health inequalities and multiplying costs. Paul McGinness, chief executive, Lenus Health, explains how proactive pathway automation builds system resilience.
It bears repeating that the NHS is in the middle of its worst winter in the last decade. Accident and emergency waits and ambulance delays are the longest on record, and waiting lists are running north of 7 million people.
We know that staffing shortages and lack of community care are exacerbating the problem in the UK, but many other European countries are facing similar healthcare provision challenges despite their investments in pandemic recovery.
A chronic problem
For decades, more people have been living longer with one or more long-term condition. The economic cost and clinical burden of this on healthcare providers is significant.
Around 15 million people in England have a LTC. Heart failure, chronic obstructive pulmonary disease, asthma, diabetes and kidney disease are the most common, with each of these conditions accounting for five of the top 10 reasons for an emergency admission and 70 per cent of total inpatient bed days.
Going for broke
Caring for patients with LTCs is estimated to account for £7 out of every £10 of UK health and care expenditure, and the average cost of treating a single patient with two conditions is more than treating two patients with a single condition. The maths doesn’t add up.
If delivering greater value is not possible in the current system, the only alternative is to increase spending. In 1990, healthcare accounted for 5 per cent of the UK’s gross domestic product. Today, it is around 12 per cent of GDP and almost half of UK government spending.
Furthermore, multimorbidity (having more than one condition) is a growing issue with a projected two-thirds of adults aged over 65 expected to be living with multiple health conditions by 2035. In line with the ageing population, healthcare spending would need to increase exponentially to even maintain today’s precarious standards.
Intelligent models of care
With the over 65 population in the UK set to grow by 30 per cent in next the 20 years and more who will be able to benefit from technology, new models of care are vital to manage patients with LTCs and to build system resiliency moving forward.
These models exploit technology, integrate patient generated data, support improved automation, as well as joining up care and data across primary, community and hospital settings and between medical specialities to address the growing number of multimorbid patients.
Patients at the most severe end of their illness need an intelligent, “always-on” healthcare system which anticipates when they might deteriorate, compares them to other patients who look like them, and monitors their health on a continuous basis.
Proactive pathway automation
The solution to reform in the NHS lies with technology, better data structuring and application of artificial intelligence to drive more automation and give clinicians the tools they need to help patients with chronic disease.
As with many other industries, technology can transform expensive services into affordable goods. Think of the cost of a custom-made shoe versus a factory-made one or a farmer hand ploughing a field versus running a fully computerised operation.
Perhaps in 50 years we might look back at how care teams work today and be shocked at how few digital biomarkers were available to them compared to their more modern contemporaries and how much of the information gathering work of clinicians can be achieved using machines and automation.
A more equal solution
The crisis we face today is ultimately one of capacity, and the delivery plan put forward must take into account that LTCs are the primary driver of unplanned care. They have led emergency admissions to reach breaking point, and this is particularly true in deprived communities where they are more prevalent and severe.
Current approaches to managing these patients remain suboptimal, dispersed across medical specialties and healthcare settings. Health data is often fragmented resulting in uncoordinated pathways, repeat tests, delayed diagnoses, and reactive interventions. The result is increased costs and backlogs for the health service and poor outcomes for patients.
We must shift the balance of resources from one that is aimed at specialised, episodic care for acute conditions, even those provided by digital means, to one that matches the needs of the population for proactive, integrated, and preventive care pathways for chronic conditions.
Through addressing LTCs we also address health inequalities. Therefore, it is vital that significant strategic investment is made to help find, diagnose and manage major LTCs more effectively across care settings by integrating devices, data and applied AI to automate decisions across the complete patient pathway.
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