As part of the Women's & Children's Health Innovation Portfolio, the Scottish Government Chief Scientist Office (CSO) are funding this Small Business Research Initiative. Health Innovation South East Scotland are hosting this challenge on behalf of NHS Scotland.

The challenge is now open for applications from the Public Contract Scotland website

Challenge LINK on Public Contracts Scotland

Applicants can apply for a share of £210,000, inclusive of VAT over a 2-phase competition. Phase 1 is allocated £60,000 for up to 4 projects. Phase 1 projects can range in size up to total costs of £15,000 inclusive of VAT. Phase 2 is allocated £150,000 for up to 2 contracts. Phase 2 projects can range in size up total costs of £75,000 inclusive of VAT.

A Briefing Link to provide further background and an opportunity for applicants to ask questions will take place on 1 November 2023 at 09.30 am. Register Here

All questions should be directed to the Q&A portal on PCS before 11am UK time on 6th December 2023 or at the Q&A session during the briefing event.

Challenge Objective:

The aim of this competition is to provide an opportunity for organisations working in partnership with NHS Scotland, to develop disruptive innovative solutions. These solutions will focus on the pro-active target management and prediction of asthma attacks in young people with asthma. Application must address the challenge and must address at least one of the themes below.

Challenge:

A new system that integrates with existing clinical systems to collect and process clinical data from the various sources (e.g., hospital, primary care, out of hours) and then enable a response to change the outcomes for the at-risk individuals.

Themes:

A) A way to understand more about individuals outside the conventional face to face or synchronous online consultation. We would like to utilise novel methods of communication that suit children and young people of different ages and development stages.

B) A solution that utilises existing technology (e.g., apps, home monitoring devices) in an innovative way where collected data are used to inform the risk category for an at-risk individual.

Background:

Asthma affects approximately 1 in 11 people in the UK. It is one of the few chronic health conditions that affects children and young people more than older people. Asthma is a fluctuating condition with periods of stability and periods of poor control. Overall cost to the NHS in the UK is greater than £1 billion per year.

Predicting an asthma attack, where there is loss of symptom control, is often associated with family or life changes and poor adherence. Viral infections, environmental triggers, seasonal changes etc. also upset symptom control and can lead to an attack. This attack, which will need an increase in therapy and may result in a hospital admission, is the end point of a period of loss of symptom control which may be up to a month in development. While adherence to treatment is a major factor influencing risk of attack, there are many underlying complex issues that prevent children and young people from adhering to their medication.

Asthma attacks are dangerous. They represent a failure of management and can result in loss of school, lost earnings, loss of confidence, loss of sleep, admission to hospital, requirement for intensive care or, in the worst cases, permanent neurological impairment or death due to lack of oxygen to the brain. Severe outcomes are rare but tragically are considered avoidable. Severe attacks can result in a significant aftermath of anxiety, avoidance of normal life activities and general chronic family worry. There is also a high healthcare cost due to poor asthma control.

The national review of asthma deaths, published in 2014 (Why asthma still kills, RCP London 2014), showed several areas where improvements could be made. One of the key recommendations was the introduction of personalised asthma action plans. These have been used more commonly recently but tend to be static printed documents which do not respond to changes in circumstances. In addition, current healthcare systems are poorly responsive to changes in individuals. Around 50% of those who had fatal asthma attacks were classed as having mild asthma. Those classed as severe (<10%) tend to be looked after in specialised hospital clinics with the rest looked after in primary care. In time some who were classed as severe may become more stable, and some who are considered “mild” may still have severe attacks. According the NRAD data, detecting which patients are at risk of an attack at any point in time cannot be limited to whoever is in the tertiary hospital clinic. A whole population approach is needed to reduce the risk of asthma attacks in all children and young people.

There is lack of evidence so far that the findings of the NRAD report have resulted in change. A Nuffield report into the health of young people found that the UK lagged far behind comparable countries in Europe in terms of asthma deaths (Nuffield Trust adolescent health report 2019). While the precise reasons for this are not well understood, the report highlights lack of basic access to healthcare and poor understanding of asthma risks by young people as two most likely factors.

Predicting which individuals are heading for an asthma attack and intervening to prevent this would have a significant impact on the health of this population and on the acute services that look after these cases: primary care, out of hours assessment, emergency departments, inpatient wards and critical care. A recent systematic review of studies in this area (Buelo et al, Thorax 2018) showed that the following factors (amongst others) are important in predicting asthma attacks in children and young people:

• Previous asthma attack

• Persistent symptoms

• Sub-optimal preventor inhaler use

• Increased short term reliever use.

• Associated atopy/allergy

• Poverty

• Exhaled tobacco smoke exposure

Most of these factors can be collected from existing health care data, however current systems do not generally provide risk stratification based on a pre-defined algorithm. Key to this challenge is the utilisation of existing healthcare and other relevant data for the risk stratification of individual children and young people of asthma, and the subsequent measures that will modify this risk.

Immediate Challenge

This open innovation challenge focuses on several aspects of care of children and young people with asthma (5 to 18 years).

Aspects of Care:

This list is not intended to be exhaustive, but all solutions must address the challenge and themes (Section Specific Challenges and Themes) as well as any other mandatory requirement.

Fluctuating nature of asthma and impact of attacks on the individual, family, and healthcare systems.

Current situation:

• An asthma attack is the end point of a period of poor control.

• We are currently unable to anticipate who has declining symptom control, therefore the first evidence is often presentation to emergency service or an admission to hospital with an attack. Potential Solution:

• A data driven preventative approach which utilises available data to generate an algorithm/rules-based system based on published evidence should detect those at increased risk with a view to preventing an attack.

• A digital asthma action plan that responds to signs of deterioration will help to respond to increased risk of attack.

Limitations of current healthcare system and proposed solutions

• Current reliance on routine reviews which may or may not coincide with a period of poor control. Limited time in primary and secondary care, along with a high DNA rate, results in an inefficient system. Potential Solution:

• A data driven risk stratification approach to focus attention on the people who need it at the right time will prevent attacks from occurring. Current Situation:

• Multiple electronic healthcare records use different software. No unified system that can analyse everything. Potential Solution:

• We require data retrieval across all NHS systems with analysis outcomes integrated into existing platforms.

Young person-centred approach to communication and appointments

Current Situation:

• Face to face and video calls with posted letters are currently the standard means of communication. This is an NHS service focussed delivery, rather than being patient centred. Potential Solution:

• A patient-centred delivery, gamification, digital clinics, social media etc.

Evolution of digital health towards integration of high-quality data into clinical system

Current Situation:

• Adoption of digital technology is patchy and resultant data can be overwhelming on top of the current demands on young people with asthma as well as clinicians and the traditional clinical services. Potential Solution:

• Selective and data driven approach to the adoption of existing remote sensing technology (e.g., wearables, lung function, treatment adherence, symptom scoring/recording) that recognises the limits of patient generated data and favours “passive” data collection without data input from patients or their carers.

Impact of poverty on health outcomes

Current Situation:

• Reliance on travel to hospital and devices for communication disadvantages those in deprived households. Appropriate utilisation of healthcare and knowledge of resources and help is difficult for poorer families.

• Impact on environmental pollution (indoor and outdoor) on asthma risk-traffic, poor ventilation, damp/mould, tobacco, e-cigarette vapour- disproportionately affects those in poverty. Potential Solution:

• Health care should be focussed on those with greatest need – clinician input, appointments, education, support, involvement of local authorities, housing associations and social services where appropriate.

Specific Challenges and Themes

Applications must address the challenge and must address at least one of the themes below.

Challenge:

A new system that integrates with existing clinical systems to collect and process clinical data from the various sources (e.g., hospital, primary care, out of hours) and then enable a response to change the outcome for the at-risk individual.

Themes:

A) A way to understand more about individuals outside the conventional face to face or synchronous online consultation. We would like to utilise novel methods of communication that suit children and young people of different ages and developmental stages.

B) A solution that utilises existing technology (e.g., apps, home monitoring devices) in an innovative way where collected data are used to inform the risk category for an at-risk individual.

Solution must meet the following primary workstream aspects:

a) Utilisation of machine learning in development of robust algorithms to enable prediction of asthma attack in individuals.

b) Validation of resultant algorithms through rigorous testing to provide evidence of clinical benefit.

c) Involvement of patients and families in validating and applying new approaches to asthma care.

d) Work with clinicians and healthcare systems to improve the patient pathway to effective care and to understand and resolve barriers to integration of data communication.

Secondary workstream aspects may be included:

e) Utilisation of home/remote monitoring which fully integrates with other data inputs.

f) Anticipating how wider patient supports can be involved in improving asthma risk e.g., family, school, workplace, friendship groups, social media communities.

Long term vision

In the long term we wish to see a reduction in the reliance of people with asthma on emergency care services, as signs of deterioration are met with a specific and focussed clinical response. We wish to see clinicians caring for children and young people with asthma spending the right amount of time with them to make a correct diagnosis, understand them and their condition, and to support them towards long-term effective self-management.

What might this look like?

This may involve, but is not limited to:

• A clinician dashboard of individual risk based on a data driven algorithm.

• A clinic appointment system which is patient focussed

• Clinician to clinician communication system to better share concerns

• Remote monitoring of certain patients at considerable risk e.g., wearables, symptom monitoring, lung function

• A digital personal asthma management plan that responds to increased individual risk.

• An app that allows communication between patients and clinicians

• Adherence tools to intervene for those who are at risk.

• Environmental monitoring to reduce exposure to harmful pollutants.