5 Things We Know About Digital Change and Implementing New Technologies in Health
No matter your industry, conversations around digital, technological change, and AI abound. Health is no different. Historically, the health industry, especially the UK, has not been known as an early adopter of new technologies the same way other industries have been.
However, the pandemic changed that significantly. Now, we are firmly in the era where 'digital transformation' isn't restricted to change management and IT teams but is rather a common lexicon across the NHS and other health bodies.
But what do we actually know about "making digital health happen" in health?
Here are 5 ideas/themes/concepts you should know about.
Digital Health is not one thing.
Using the term' Digital Health' is about as descriptive as using the word 'food'. Digital health is an umbrella term that represents very different tools and applications. Talking about digital change can be misleading because it covers different technologies, applications, and use cases.
The number and type of digital health tools have proliferated, particularly in the past five years. Digital Health is used to represent tools as diverse as remote patient monitoring platforms, robotic surgery systems, EHRs, smart scheduling software, patient education and triaging chatbots, staff communication platforms, admin automation software, genomic decision support tools, and more.
Acknowledging this diversity is essential if we want to understand these technologies, figure out how to implement them, and determine what works and doesn't. We need to accept this complexity to avoid making simplistic assumptions about implementation and what needs to change.
These new technologies are about more than their technical capabilities; context and how we use them matter just as much.
Google DeepMind’s team, a pioneer in AI model development, has emphasised the importance of looking beyond the technical capabilities of these new technologies. When looking at many of the technologies, context matters, including who is using the tools, for what, and in what situation. They set out a framework that incorporates the need to understand human interaction and health system-wide impacts, too. This means looking at more than model performance to what implementing some of these tools could mean for socio-technical outcomes. How will these people, economies and social systems interact with these tools to shape health outcomes and experiences?
Digital tools and technologies have impressive capabilities but can’t magic away real-world constraints – for now.
Health systems worldwide face challenges around staff shortages, well-being and skills, and disease burden. Our health services are still primarily delivered by humans, who need facilities, buildings, and machines to diagnose and treat patients. Even with new technologies, we still have to invest in humans, capital, and especially IT systems.
The UK performs worse than most comparable countries in terms of health workforce shortages, staff satisfaction, and investment in capital (facilities, buildings, equipment, and IT).
Even if digital is to help alleviate workforce challenges, we will need engaged staff to train and implement technologies, as well as buildings and up-to-date IT systems that can integrate new technologies.
Perhaps one day, we will see intelligent robots providing treatments, autonomous drones collecting pathology samples and 3D printers printing much-needed medical devices. However, we’re not there yet; in some use cases, we may not want to be.
We live in a world where lack of hospital beds, theatres in disrepair and staff burnout are serious issues. Some of the new technologies have the potential to alleviate these challenges but won’t eliminate them.
Digital Inequalities are real, and we must address them as we implement new tech.
With a growing emphasis on patient-facing health technology worldwide, if we don’t address the issue of digital disadvantage, certain groups could be left behind or, even worse, become ‘invisible’.
People differ in their ability to engage with digital tools. Typically, risk factors include those who are older, from more deprived groups, and have lower levels of literacy. Yet, some of the people who need the most health support often fall into this group. In a world where health access and engagement increasingly require higher levels of digital skills, this could exacerbate existing health inequalities.
Alongside digital implementation, we must address the wide variation of digital capabilities in our population.
Understanding ‘what works’ in this new wave of technologies, from digital health apps to AI models, is not straightforward.
In some respects, it is easier to focus on evaluating the technical capabilities of these new technologies than to understand their real-world impacts as a whole.
We are in the early days when it comes to evaluating “ what works and what harms exist” when we implement these technologies. Part of the issue goes back to point 1: they are so different. There are challenges, too.
One issue is that there is still a paradox when it comes to digital health technology. Which is to show that digital health has benefits, we have to implement and, in some cases, scale them. Yet, when it comes to the NHS, we are not used to procuring or scaling products that don’t already have extensive evidence of benefit. This is reasonable given in health, we deal with people’s lives and quality of life, so we want to make sure tools are safe. However, it does mean some significant real-world benefits and harms won’t be known until we implement them.
Understanding “ what works” is also complex for other reasons. Traditional methods of evaluation don’t lend themselves well to these new technologies. This is due to factors ranging from the dynamic nature of product lifecycles to the role of context, implementation, and human interaction in driving outcomes.
We need to do more to evaluate the socio-technical aspects of new technologies and explore new implementation and evaluation approaches which can limit harm. Some health bodies, such as NICE, NHS England, and academic institutions, have already proposed frameworks and are testing new methods. To find out more, here's my article on evaluating new technologies.
