Behavioural science can boost cardiac survival rates

06 October 2020

By Ivo Vlaev

Out-of-hospital cardiac arrests are a significant public health challenge. A cardiac arrest, which is different from a heart attack, is where the heart abruptly stops beating leading to circulatory collapse.

Each year in the UK some 40,000 people suffer an out-of-hospital cardiac arrest (OHCA) where paramedics attempt to start or continue resuscitation, and fewer than 10 per cent survive to the point of being discharged from hospital. While globally, research suggests that the 'survive to discharge' figure is some 8.8 per cent for OHCA patients who receive cardiopulmonary resuscitation (CPR).

Consequently, there is considerable scope to improve survival rates. Indeed, improvement in any of the four steps in the chain of survival – 'early access and recognition', 'early CPR', 'early defibrillation' and 'early advanced care by paramedics' – can make a huge difference.

One innovative initiative aimed at improving the chain of survival for OHCA cases involves the use of mobile apps to alert trained volunteers that happen to be nearby. Services of this type exist in a number of countries around the world.

A good example is the GoodSAM app-based system in the UK which integrates with the emergency ambulance services. An important feature of this type of app is that it can show responders the location of public access automated external defibrillators (AEDs). These medical devices are associated with doubling OHCA survival to hospital discharge (with good neurological function) rates.

Yet, despite the difference that AEDs can make, their deployment rates are surprisingly low. Public access AEDs are used in fewer than five per cent of OHCAs. Furthermore, for each OHCA alert, evidence suggests that fewer than half of the contacted responders accept that alert.

This is where a behavioural change approach can make a difference. Behavioural change frameworks, tools and techniques, have been used to tackle issues successfully in a variety of fields, including health. They have been used to nudge behaviour in a particular direction, improving diets, reducing excess alcohol consumption, encouraging people to exercise, and getting patients to cancel medical appointments, rather than just failing to turn up without notice, for example.

The Clinical Trials Unit (CTU) at the University of Warwick's medical school runs an OHCA project, pioneering the collection of OHCA data in the UK, with a view to using it to improve outcomes. Together with a number of colleagues associated with the OHCA outcome project team and the CTU, we decided to adopt a behavioural change perspective in an attempt to improve AED use by responders (and also increase OHCA alert acceptance rates).

In doing so, we used several established behavioural change related tools, including the Behaviour Change Wheel, COM-B model (Capability, Opportunities, Motivations interact to generate Behaviour) and the heoretical Domains Framework. These provided a framework within which we were able to understand and diagnose the drivers of the behaviours we wanted to change, map those to interventions that incorporated different behavioural change techniques, and link them to specific policies and actions in practice.

Initially, the process involved interviewing 30 GoodSAM app first responders, who had recently received an alert in London, with a focus on their decisions relating to the use of a public access AED. The responses were analysed looking at enablers of and barriers to AED use through the lens of the three COM-B model dimensions: capability (physical and psychological); opportunity (social and physical); and motivation (automatic and reflective).

This gave us 10 drivers of behaviour that needed to change in order to increase the use of AEDs by voluntary first responders. Once we had identified these determinants of behaviour, we could then develop behavioural change interventions and practical ways of delivering those interventions.

For example, a number of the drivers of behaviour were related to awareness of and access to AEDs. Take the simple issue of needing to be sufficiently aware of the location of AEDs. Here, our proposed solutions to promote the desired behaviour were comparatively straightforward. Using prompts and cues - stimuli in the environment that nudge you to act in a certain way - both via email and the app, we suggest providing reminders about AED locations at regular intervals between alerts. At the same time, we also suggest in-app prompts to enable people to recognise the location of the nearest AED during an alert.

A significant number of volunteers were also concerned about the process of getting official custodians of AED devices to hand them over to the responder, particularly when responders do not have any official identification. To overcome this barrier we suggest an intervention that provides standardised information to display to custodians of public AEDs, both printed cards and a visual display in-app, coupled with a print and digital media campaign targeted at AED custodians to emphasise the importance and health benefits of using them. The aim here is to provide first responders with the confidence and reassurance necessary to overcome any behavioural barriers associated with dealing with the AED custodians, while also easing any concerns custodians may have about handing over the device.

Another significant barrier to using AEDs was the need to weigh the relative merits of getting to the patient as quickly as possible against spending time retrieving an AED. Here, we propose an intervention so that, when several people respond to an alert, some of the responders are sent to retrieve a public access AED, while others go directly to the patient.

To encourage this, guidelines can be introduced explaining why some responders are being asked to retrieve the AED, along with rules to govern the response process, as well as sharing information during an incident so that each respondent is aware of the actions of others.

In practical terms this means publishing a code of conduct on the GoodSAM website, backed up with regular email updates, coupled with visual and voice prompts delivered via the app during an alert. The aim being to persuade responders of the merits and viability of retrieving an AED if there is an alert.

The next step will be to test the suggested interventions as a single package because they are interconnected and it is their combined effect that has maximum impact. 

Having identified some of the main issues preventing greater use of publicly available AEDs by first responders using these types of app and suggested some possible solutions, it is now up to policymakers and researchers to implement and test them.

Together, we can use these interventions to save lives.

Further reading:

Smith, C. M., Griffiths, F., Fothergill, R. T., Vlaev, I. and Perkins, G. D. (2020) "Identifying and overcoming barriers to Automated External defibrillator use by GoodSAM volunteer first-responders in out-of-hospital cardiac arrest using the theoretical Domains Framework and Behavour Change Wheel. A qualitative study", BMJ Open, 10, e034908.

Murphy, J., Uttamlal, T., Schmidtke, K., Vlaev, I., Taylor, D., Ahmad, M., Alsters, S., Purkayastha, P., Scholtz, S., Ramezani, R., Ahmed, A. R., Chahal, H., Darzi, A. and Blakemore, A. I. F. (2020) "Tracking physical activity using smart phone apps : assessing the ability of a current app and systematically collecting patient recommendations for future development", BMC Medical Informatics and Decision Making, 20, 1, 17.

 

Ivo Vlaev is Professor of Behavioural Science and teaches Judgement and Decision Making on the MSc Finance.

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