Extra £20 billion NHS funding to focus on prevention and early detection

Date: 08th Jan 2019

Yesterday, the Prime Minister and Simon Stevens, Chief Executive of NHS England, announced the eagerly awaited long-term 10 year NHS plan, described by NHS England as a ‘blueprint to make the NHS fit for the future’. But despite being little or no mention of social care, the key priority is to save 500,000 lives by following a more strategic line on prevention and early detection.

Many commentators have struggled to see how a ten-year plan for the NHS could make no mention of adult social care, or the promised social care green paper, which was postponed several times towards the end of last year and is now due to be released in January.

George McNamara, director of policy and influencing at Independent Age, said:

“One of the biggest health challenges we face today is how best to care for an ageing population. The NHS long-term plan must clearly set out the necessary funding and reforms to ensure older people can live healthier lives for longer. It is absolutely right to focus on prevention, but until the government addresses the crisis in social care the success of the NHS plan will be severely limited. Health and social care go hand-in-hand. Failure to do both will put the sustainability of one of our national treasures at risk and push more older people into crisis, putting avoidable pressures on an already stretched NHS.”

Brian Brown, Director of ARMED (Early Intervention & Prevention Solutions) comments:

“Although social care wasn’t highlighted in yesterday’s announcement, we welcome the prevention and early intervention approach. Our Advanced Risk Modelling for Early Detection (ARMED) solution combines pioneering predictive analytics modelling with innovative wearable technology, and health and social care data, to provide a powerful tool to identify risks earlier in the care cycle, including the risk of falling. The wearable device detects early indicators of frailty, such as low grip strength, muscle mass, hydration levels, low heart rate and heart rate variability.

Predictive analytics modelling - developed in partnership with Edinburgh Napier University - then uses data to predict the risk of a potential fall and allow intervention.  Examples of this are now demonstrating escalations of risk being identified up to 32 days in advance of previously identified falls.”

Download further information on ARMED here.

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