Our Strategy Director Paul McGuigan was recently featured in The Journal of mHealth, sharing his thoughts on AI in the health-tech space, and how the effective positioning of a brand can make end-users have more confidence in how their health data is analysed.
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In the post-cookie, AI-driven future of personalisation, what’s the model going to look like in the health sector? The public already doesn’t like their data being gathered or the feeling that health firms might know too much about them, so how will they respond to machines learning about our health and behaviours in order to deliver recommendations, interventions, and personalised digital experiences?
AI undoubtedly presents powerful opportunities in this field, as it is currently having its moment in cross-industry adoption. We’ve seen it benefit the automotive industry, mobile arena, FMCG and many more, but when it comes to healthcare, uptake has arguably been slower. So, what’s holding us back? A key challenge is communication and brand trust. For organisations attempting to drive forward digital transformations, human-centric design and communications can play a crucial role in gaining the public (and professional) trust they need. This is, of course, easier said than done however, and requires navigating several obstacles and the right insights.
Learn from previous mistakes
The technology is new, but the challenge is as old as medicine itself. Relatively recently, just as we see with the introduction of AI-based tools, innovations such as the introduction of Electronic Health Records faced some of the same adoption challenges around security, privacy and, ultimately, trust.
Early concerns (some of which continue today) centred around effective communication about how information is shared and who with. Design and information that users (both professionals and patients) found difficult or complex compounded perceptions of an opaque practice of gathering and using medical data.
Whilst the immense benefits to patient and professional experiences have now been widely proven, further advancements continue to meet with scepticism, fear and challenge. With AI offering the next springboard to innovation in processing and interpreting healthcare data, it’s important to learn from these early mistakes in communication, brand, and design, and take a radically different, more human-centred and insight-driven approach.
AI offers the potential to make the user experience slicker and easier and to assist time-poor physicians with interpreting data and information to inform their decision-making and diagnoses. But we must recognise and deeply understand people’s reticence and fears around AI – not be dismissive of it. The next innovations need to be driven by patient needs and insights, not by what is technically feasible.
AI complements, not replaces human experts – make sure that story is told
As we continue to learn more about how different factors impact our health and risk factors, a quick Q&A with your GP about whether you smoke and drink, and what exercise you do, can no longer deliver the best possible results in terms of proactively looking after your health. When a GP can look across a huge source of data points, telling a more complete story of past health and care needs, cross-referenced with family data, information about lifestyle, exercise data, comorbidities, linked research data etc, they can give more complete, bespoke care advice to increase your quality of life. The care, advice and knowledge still come from a human practitioner, but they can be greatly assisted to make use of much wider data sets through the use of accessible, interoperable data sets and, of course, AI.
Despite demand growing exponentially, people increasingly expect more personalised and informed interactions and advice, but there’s a deficit in understanding data sharing (and opting out of it). This could potentially strangle the flow and quality of information which AI relies on. So touchpoints and interactions relating to data sharing need to be similarly insight-driven and human-centred.
Building positive messaging and brand trust around those developing AI-based tools and dealing with patient data are vital in reassuring patients, while dispelling fears that AI is a threat to their privacy. Brand consultancies can help build a positive narrative to demonstrate how AI and data science complement healthcare professionals and their ability to provide the right support while exercising more fully informed human judgement.
With ever-growing pressures on healthcare professionals and their time, celebrating the concept that patients can feed back into the system in a positive way through data sharing can help dispel myths and misunderstandings about what data in healthcare is actually used for.
Understand the lives of those you are trying to improve with AI and personalisation
Health & care systems are complex – particularly in cases where you might have a complicated mix of conditions combined with outside factors like social care needs. Individuals could end up interacting with dozens of service providers for multiple or complex, intersectional needs.
In health, personalisation is not just about the niceties of communication like addressing you by name and knowing when your birthday is. It’s about giving you the right care and tools for self-care. About understanding you, your lifestyle, your genetic risk factors, comorbidities, and the combined effects of a whole variety of data points. And about referencing those data points against the latest research.
So before offering a specific AI based tool or service to an audience, it’s imperative to get a real sense of them. Understanding their lives, mindsets, issues and concerns. By bringing together the research efforts of product developers and brand & communications consultants, you can ensure that the same insights that drive product development also drive the UX / UI design, positioning, and communication around the product. In the same way that the content or AI interface itself establishes a natural rapport with users, so must the brand and communications surrounding the product.
Be transparent about what can be done and celebrate the potential
The UK probably has more potential in terms of what we can do with AI in health and care than any other country. We have the biggest single pool of patient data in the world to draw upon and, despite its challenges, we still have arguably the most joined-up and cohesive healthcare system. It’s not unfathomable that we could be world-leading in terms of what we do with our data and what AI technologies could do with it. Could the simple act of celebrating our potential capabilities help gain public trust and permission to explore?
A clear and single-minded vision and message could make this possible. The kind of cross-industry collaboration required to build that kind of narrative should, in theory, be more possible here than anywhere else.
We must also be transparent though. This is difficult technology for the general public to understand. Openness about not just what we are confident in knowing, but also what we don’t yet understand is important to engender trust. But it’s a tricky balance to manage, to also avoid stoking fears. Skilled communications professionals and brand consultants must play a role in this.
Actively involving brand communications and design experts from the early stages of development, working alongside technologists, clinical experts and, of course, service users, will help ensure positive interactions that encourage people to trust and interact with new AI technologies.
If we put a deep understanding of people – not technology – first, we will see AI reach its full potential in helping to deliver better healthcare outcomes.
Read the full article in The Journal of mHealth here
Photo by Alexander Sinn on Unsplash
