Solutions are needed to reduce the costs of health and social care for the ageing population. This insight looks at existing, emerging and speculative future interventions that have the potential to help in three key areas: falls, nutrition & hydration and mental health.
The UK population is ageing, with 18% currently aged 65 or over, and this proportion is continuing to rise (Office for National Statistics, 2015). By 2036, this will have risen to nearly 24% (a 48% increase in the number of people aged 65+). For those aged 85+, this change is even more marked, increasing from 1.6 million to over 3.3 million in the same time frame. The incidence of serious health issues and the proportion needing support with daily life increases dramatically with increased age. Thus the ageing population carries with it significant challenges for health and social care.
Action needs to be taken to manage the increasing costs of health and social care. This insight looks at the opportunities presented by various serious issues such as falls and depression. Interventions can lower the incidence of such issues, as well as reduce the severity and impact of them socially and financially, when they do arise. They can also assist older people in living independently despite
reductions in capability or mobility. Many interventions are already available, but need to be applied more consistently and effectively. Others will become possible due to the rapid evolution and development of new technologies and techniques.
An earlier report examined various areas in which the ageing population faces challenges, including healthcare, home, leisure, transport and money (Sinclair and Creighton, 2015). The current report follows on from this, focusing on three key areas in more detail: slips, trips and falls; nutrition and hydration; and mental health. These areas present key issues affecting many older people and incurring significant costs in health and social care, as well as reduced quality of life and increased mortality.
Around 33% of people over 65 and 50% of those over 80 fall at least once a year (Tian et al, 2013). One in five of these falls requires medical attention (Gillespie et al, 2009) and around 7% of them result in a fracture (Stevens et al, 2006). The after-effects of even a minor fall can have serious consequences, with fear of falling again often limiting independence and reducing quality of life (Age UK,
undated). Overall, falls are the main cause of disability and the leading cause of death from injury among people aged over 75 in the UK (Age UK, undated). Half of older people who fall can no longer live independently (Mulholland, 2003) and up to 40% of nursing home admissions are related to falls and instability (Rawsky, 1998).
The full financial cost of falls are not available. However, it is known that hip fractures alone cost the NHS over £2.3 billion a year (Age UK, undated). In addition, there are healthcare costs associated with other fall injuries, as well as many indirect costs related to informal care and loss of independence.
Several relatively simple interventions can reduce the risk of falling among older people (Stevens and Olson, 2000). For example, both general exercise and balance training can improve older people’s fitness and balance and thus reduce falling. Environmental modifications can also be effective. These include measures such as removing trip hazards, improving lighting (especially at night) and providing grip bars. Simply providing improved education on the topic of balance and falls can act as a preventative method, making older people more aware of the need to take care in certain
situations. An assessment of medication also helps, since some combinations of medications cause dizziness and grogginess, contributing to falls.
Technology can alert carers to a fall, allowing medical aid to be provided more swiftly. This may reduce the severity of the fall and lead to better outcomes. Current technologies range from call alarms (also known as ‘panic buttons’) which are operated by the patient, to sensor technologies that sense a fall automatically (Kosse et al, 2013). Some sensor technologies can also be used to identify people at greater risk of falling (Ejupi et al, 2014). Interventions like those described above can then be put in place to reduce fall risk.
Some measures are also available that aim to mitigate the effect of a fall when it happens. For example, protective clothing can be used to protect hips or heads from serious damage, or floors may be carpeted with softer material to reduce the impact of a fall. Future technologies may enable flooring materials that could soften on impact to reduce consequences of falls.
Example: A falls risk assessment and management programme
One effective method for reducing the number of falls is a risk assessment and management programme. Such a programme works by assessing each individual’s risk and managing it in a personalised way, using a combination of methods. These methods include exercise interventions, changes to the environment and medication assessment. A meta-analysis by Chang et al (2004) found that such a programme had the largest impact on falling (out of the methods examined), reducing the risk of falls by 18% and the monthly fall rate by 11.8% (i.e. 11.8 fewer falls per 100
patients per month). Exercise interventions on their own were also effective (14% reduction in risk), but did not have as large an impact. Some individual studies have reported even better results, although these are preliminary and not from controlled trials. For example, Mulholland (2003) reports a 60% reduction from three pilot sites trying out a combination of better slippers, night-lights and free tai-chi classes.
Taking a 11.8% reduction in fall rate (from Chang et al, 2004), a full roll-out of a risk assessment and management programme could save the NHS around £0.3 billion a year on hip fracture costs alone, in addition to substantial savings on other healthcare costs and the cost of social care.
The implementation of such a programme could be supported using technology. For example, technology applications could help a therapist to assess a patient’s risk. A smartphone app could present people with tailored exercise programmes and remind them to do the exercises. It could also help with motivation through the use of personalised goals, e.g. using pedometers and accelerometers to measure activity. This could help to increase compliance and thus improve the effectiveness of the intervention.
Example: Automatic fall detection
Call alarms enable a patient to call for help after a fall, but the alarm has to be both within operating range, and within reach of the patient, and the patient has to be conscious and capable enough to operate it. Automatic fall detection systems avoid this issue by using technologies to sense when a fall has occurred (Igual et al, 2013). Some systems use sensors positioned in the environment that sense a fall, such as cameras, floor sensors and infrared sensors. Others use sensors worn on the body, either in the form of specialised sensors or embedded in smartphone devices.
These systems do not prevent a fall, but they do reduce its severity by enabling the provision of swift medical aid. They reduce healthcare costs, as they result in shorter medical stays and reduced medical complications.
Example: Technology-based risk assessment
Sensor technologies can also be used to identify patients at high risk of falling (Ejupi et al, 2014). Low-cost portable devices have been recently developed that use sensors to examine patients’ mobility, gait and sway as part of a clinical assessment. The use of wearable and portable app technologies from the consumer fitness market potentially could also be repurposed to identify those at risk of falling, as well as provide automatic fall detection and alert functionality (Cambridge EDC, 2016). These technologies can help to improve cost-effectiveness by targeting interventions at those at most risk of falling. For example, Close (2005) reports that interventions focusing on highrisk populations tend to reduce fall rate by around 36%. This would save the NHS around £0.8 billion a year on hip fracture costs alone.
The energy, nutrients and water in food and drink are essential to keep the mind and body working properly. Poor nutrition and hydration can lead to decline in mobility, fatigue, dependency in daily living, higher risks of falls, impaired recovery and shortened survival (Nestlé Nutrition (undated); Brotherton et al, 2012; Social Care Institute for Excellence, 2009).
Around 23% of older people are malnourished, and a further 46% are at risk of malnutrition (Kaiser et al, 2010). The figures for dehydration are less clear. Studies have found that between 0.5% and 60% of the older population are dehydrated, depending on the criteria for dehydration (Stookey et al, 2005). These figures are extremely diverse, but they do indicate that a large proportion of the older population are at risk.
There are many different reasons for poor nutrition and hydration in older people. As people age, they often experience a decreased appetite and a reduced sensation of thirst (Nestlé Nutrition, undated; Hooper et al, 2015). Their nutrient needs also change – while they need less of some nutrients, they may need the same or more of others (Nestlé Nutrition, undated). In addition, the amount of water stored in the body decreases with age. This means that a smaller drop in water intake can result in dehydration in an older person (Hydration for Health, undated).
Some older people have difficulties purchasing and preparing food, and some with chewing and swallowing. Difficulties can also be caused by underlying illness, medication side-effects, confusion, depression, social isolation and poverty (Nestlé Nutrition, undated; Hickson, 2006). In some cases, older people may consciously reduce water intake because of fears of incontinence, although this may actually be counter-productive (Queen Elizabeth
Hospital Birmingham, 2012).
In 2007, the estimated cost of malnutrition (and its consequences) in the UK was more than £13 billion (Elia et al, 2011). The costs of dehydration are difficult to estimate because much of the cost is due to secondary effects, e.g. poor hydration leading to falls or to inability to care for oneself. Nevertheless, Campbell (2011) asserts that proper hydration alone could lead to savings to the NHS of £0.95bn a year, excluding secondary costs.
It is important to raise awareness of the signs, symptoms and consequences of malnutrition and dehydration (BAPEN, 2013; British Nutrition Foundation, undated). If older people and carers are more aware of these, then they can take measures to prevent them.
Some interventions address problems with lowered appetite. Advice includes providing smaller but more frequent high energy and high protein snacks and meals. Food and drinks should be easily available throughout the day, and they should be appealing in appearance and portion size. This may mean offering favourite drinks and foods rather than just water or convenient food. Making meal times more social and attractive can also encourage eating (bpac nz, 2011; British Nutrition Foundation, undated). Some older people may also benefit from reminders to eat and drink.
Community initiatives may build on these types of advice. For example, lunch clubs can help to make meal times more social and attractive (Jones et al, 2009). Technology can also play a part, for example in raising awareness or providing reminders to eat and drink regularly.
Assistance can be provided for older people with difficulties accessing and preparing food. Initiatives such as escorted shopping services and assisted online shopping can help (Jones et al, 2009). There are also opportunities to develop snacks and meals that are easy to prepare, appetising and well-suited to the nutritional needs of older people. In developing these, inclusive design is important to ensure that the older users really can open and prepare the food easily (Inclusive design toolkit, 2016).
In addition, some older people have problems with chewing and swallowing. Good dental and mouth care, and speech and language therapy may improve this. In addition, blending foods may make them easier to eat (bpac nz, 2011). There are also various aids available, such as special cups and cutlery designed for people with Parkinson’s. Some people may require assistance to eat, and there are various ways in which this can be provided. For example, some hospitals implement a system where a red tray signals a patient in need of additional assistance with eating (Age UK London, 2011).
Example: Reminder systems
There are several apps and devices on the market that remind the user to eat or drink regularly. These tend to focus on hydration or on specific aspects of healthy eating, such as eating fruit and vegetables. Most of these are aimed at a mainstream market, although some focus on older users. Many take the form of smartphone apps that provide reminders to drink water, based on manual entry of fluid intake. However, in general, the impact of such devices on dehydration has not been evaluated.
It is also possible to infer food and drink intake more efficiently and automatically, for example by monitoring use of the kettle, fridge and other kitchen equipment through real-time analysis the data collected by smart meters (Cambridge EDC, 2016). Deviations from ‘normal’ patterns of behaviour, which might indicate nutrition, dehydration in a household could be flagged to relatives, carers etc. In addition, there are devices currently available that support some automatic tracking of fluid intake. For example, Obli is a device that monitors how much fluid is drunk from a bottle placed on it. A button can also be pushed when other drinks are taken. It then emits a visual and auditory signal when fluid intake is insufficient, to encourage the user to drink more. A trial examined its use among older people. One group used Obli and also had some education about hydration, while another group had education only. Both groups had a significant increase in fluid intake, and the group using Obli averaged above the recommended minimum fluid intake both 6 weeks and 6 months after the interventions began (an increase from 1116ml to 1763ml per day) (Konings et al, 2015).
If such a system reduced the prevalence of dehydration by just 5%, then it could save around £47 million in direct healthcare costs, plus reducing the many secondaryproblems caused by poor hydration.
Example: Early detection of risk
Technology could also monitor for early signs of malnutrition and dehydration, so that these can be treated before they have a debilitating effect on a person’s life. For example, weight sensors could be built into the floor or placed under a bed to automatically track weight gain and loss (Cambridge EDC, 2016). Another possibility is to instrument a toilet to examine urine and stools at regular intervals (Schlebush and Leonhardt, 2011). This could assess hydration and nutrition levels. It could also monitor other indicators, providing an early warning system for various disorders and diseases, as well as malnutrition and dehydration (Cambridge EDC, 2016).
Depression is one of the largest mental health issues affecting older people. Studies indicate that 3-4% of people over 65 have depression, rising to around 27% of older people in institutional care (McCrone et al, 2008; McDougall et al, 2007). However, these numbers may be underestimates as depression in older people is often misdiagnosed and under-treated. Some reports suggest that as many as “one in four older people have symptoms of depression that require treatment” (Graham et al, 2011).
Depression can lead to decreased physical, cognitive and social functioning, self-neglect and increased risk of ill health and suicide, as well as decreased quality of life (Fiske et al, 2009). The cost of treating depression rises with age, from around £2000 per year for a person aged 65-74 to around £5000 for someone aged 85 (McCrone et al, 2009). This is in addition to the cost of secondary problems such as self-neglect and loss of functioning.
There are many risk factors for depression among older people, including change of role, bereavement, difficulty adapting to illness or disability, being in care and social isolation (Rodda et al, 2011). Fiske et al, 2009 suggest that “a common pathway to depression in older adults… may be curtailment of daily activities”.
One factor that can cause depression is loneliness (Bolton, 2012). Loneliness is not the same as social isolation, but they are closely linked and both increase with age (Age UK, 2010). 17% of older people have less than weekly contact with family, friends and neighbours, and 11% have less than monthly contact (Davidson and Rossall, 2014; Bolton, 2012). “Nearly half of older people (49% of 65+ UK) say that television or pets are their main form of company” (Davidson and Rossall, 2014). Studies indicate that about 10% of those over 65 feel lonely all or most of the time (Bolton, 2012).
Isolation and loneliness increase the risk of depression, reduce quality of life, and are associated with poor sleep, poorer relationships and increased mortality (Bolton, 2012). Social isolation can mean that older people do not have the support needed for them to live in their own homes and have to move to care.
Better awareness-raising about depression, its symptoms and treatments is important to reduce misconceptions and increase rates of diagnosis and treatment. Once diagnosed, there are various effective treatments, including both medication and psychotherapy methods. There are also some relatively simple measures that can help to reduce the risk and severity of depression. These include exercise, a reassuring daily routine, improvements to the home environment (e.g. adequate heating), and support before and after adversity. Interventions to reduce loneliness and isolation also help, including befriending schemes, support groups, group activities and social skills training.
Current technology can play a part, particularly in increasing contact with others, e.g. through use of Skype and social media. Future research may enable technology to analyse voice patterns through mobile phones, and detect gradual changes in voice to enable early identification of issues such as depression and dementia (Cambridge EDC, 2016). Deep learning techniques combining sensor data from for example, mobile phones and smart meters, may enable prediction of patterns leading to mental health issues (Cambridge EDC, 2016).
Exercise classes including both strength and endurance training have been found to be effective at reducing the incidence and severity of depression in older people. Bridle et al (2012) found that around 13% of participants did better than expected, with around 20% reduction in the severity of depressive symptoms for those on the threshold of being diagnosed with depression. Technology could be helpful in rolling out exercise interventions on a wider level. For example, apps and wearable sensor devices could describe exercises, and remind and encourage people to do them (see the section on “Falls” earlier in this report). Based on these figures, exercise interventions may be able to save around £13 million in direct treatment costs, plus many savings in the cost of secondary problems. In addition to reducing depression, exercise can have several other health benefits, such as reducing the incidence of falls (see earlier in this report). It would therefore result in much greater cost savings overall.
Example: Group interventions
Support groups and group activities can be effective at reducing loneliness. For example, Pitkala et al (2009) examined groups for older people suffering from loneliness. These included therapeutic writing groups, exercise classes and art activities. They found that the groups increased ratings of subjective health and resulted in significantly lower healthcare costs (€943 less per person per year) than in a control group. Healthcare costs are different in the UK, but taking this as a ballpark figure, along with prevalence figures for loneliness, we estimate that support groups could save around £800 million in related healthcare costs.
Technology-mediated groups can also help to tackle loneliness and isolation (Findlay, 2003). Examples include group teleconferencing and specially designed websites and forums such as SeniorNet and Silversurfers. Training older people in how to use computers and the Internet in general can also help to reduce loneliness (Choi et al, 2012), enabling them to use the Internet to develop existing social networks and enhance social support. A key challenge for group interventions is persuading people to take part, particularly those who need it most. Age UK (2010) explain, “Even where schemes use considerable resources to overcome physical isolation of potentially lonely hard-to-reach groups, participation is often very low”. This presents a key challenge for education and persuasion campaigns, and may present an opportunity for technology, utilising the reach of the internet and the power of persuasive technology.
The ageing population face many challenges including the areas covered in this report; falls, nutrition, hydration and mental health. However, there are many possible interventions: Education and awareness-raising can encourage older people and carers to take action to reduce the risk of problems happening. Monitoring and screening can identify people at particular risk, so that special preventative measures can be put in place. Further monitoring can detect when a problem has occurred to enable a quick response. This often reduces the severity of the issue and can reduce
secondary problems. Interventions can also help afterwards, in rehabilitation and prevention of recurrence.
Technology can play a very important part at each stage, and drive both social (better healthcare outcomes) and financial (lower health and care costs) benefits for society. It can support many of the existing interventions, e.g. raising awareness on a wider level or reminding people to keep doing their exercises. It can also open up new possibilities. Improvements in technology and the prevalence of smartphones allow wider-scale, less obtrusive and more accurate monitoring, and fast responses. Wider technology advancement, for example in big data and deep learning, could provide the criteria for relatively simple technology assessment and alerts for older people living independently to be carried out remotely and at relatively low cost.
However, any intervention should be designed inclusively to take into account older people’s capabilities and expectations, so it can be easily learned and put into practice (Inclusive design toolkit, 2016).
This insight was written by Dr Joy Goodman-Deane, Mike Bradley and Prof P. John Clarkson, Cambridge Engineering Design Centre, University of Cambridge.