How can we empower health and social care workers to embrace AI technology?

Sam Kyffin, NHS Navigator at DigitalHealth.London, shares his reflections from a recent discussion at Intelligent Health UK about the challenges in adopting artificial intelligence (AI) in healthcare.

It’s becoming all too familiar to hear concerning and sombre statistics about the challenges facing the NHS and social care. We’re frequently reminded of the deteriorating and often depressing state of the precious systems that exist to protect us from ill health and save us when harm strikes. It feels inevitable that artificial intelligence is going to be a vital component in supporting NHS and social care staff in the future as digital innovation strives to tackle the challenges that already exist as well as those that lie ahead. New AI platforms and applications are continually being introduced to healthcare, so it is vital that health and social care workers are given the knowledge and skills they need to deal with this new technology in everyday practice. While AI is becoming more pervasive in all walks of life, there still exists an underlying mistrust and fear of AI which extends to patients and staff who are being asked to put their trust in evolving and novel AI technologies. How then do we build trust in new AI-based tech and empower the health and care workforce to utilise AI innovations?

Some of the challenges in adopting AI reflect the challenges we see with the wider introduction of digital health technology. I recently hosted a Challenge Session on this topic at Intelligent Health UK, and through the discussion it became obvious that the same complaints around system inoperability, lack of integration with existing workflows and insufficient time for training, exist when thinking about AI. However, there does seem to be a uniquely expressed symptom, a sense of fear and distrust that exists when the enigma of artificial intelligence enters the room. There is a danger that the availability, rising popularity and ensuing risks of AI in general and that of open AI sources such as ChatGPT blur the focus on specific AI technologies introduced for healthcare. Conversations on AI can often end up down a ChatGPT wormhole. That said, this may not be such a bad thing. AI innovators seem to acknowledge that the public discourse on open AI is helping to stoke awareness and interest that then extends to include the implementation and use of medical-grade AI technologies. 

So where do we start? It strikes me that to empower and cajole staff will require the introduction and education of AI technologies to adhere to and extol some key messages.

• Firstly, there must be reassurances that AI technology is not there as a replacement to staff and that AI can be a tool that builds on staff’s existing practice. The focus should be on harnessing technology to release time that can then be spent on human related tasks. This mirrors the more general discussions that society is having on the tightening grip of AI.
   
• Innovators will need to clearly demonstrate the clinical benefits of introducing AI. Clinicians care deeply about improving patient care and this must be demonstrated when promoting the adoption of AI.
   
• Wherever possible AI must not interrupt the existing workflows of staff. It is imperative that companies build the application and interface with these existing processes in mind. It certainly must not make life harder for the workforce. Notwithstanding that there will ultimately be opportunities to change the way that staff work once AI is more widely accepted and embraced within the system.
   
• Training and education on AI must be digestible. Emma Taylor is a former Digital Pioneer Fellow and is now Clinical Lead at Accelerator alumnus company WYSA as well as a Nurse Educator. Emma points out that “if you can’t give clinicians information in the same time it takes to make a cup of tea, then they won’t listen. Bite sized educational chunks are the key”. This starts with AI companies who must ensure their technology and the skills needed to use it are accessible to a busy workforce who are already working beyond capacity.

• Finally, the upskilling in AI must encompass a broad spectrum of roles that includes clinical and non-clinical staff and Allied Health Professsionals (AHPs), as well as just nurses and doctors. Very often the discourse is all too focused on the latter groups but the adoption of AI in healthcare must bring everyone along with it. The versatility of the AHP community and evident willingness to embrace innovation should be recognised (transparency disclaimer: I’m a physiotherapist by background).    

Manish Patel of Jiva.AI thinks “if step one is analogue and step 100 is a robot delivering a baby, we are somewhere between steps two and four right now”. If this is true, we have an opportunity from the beginning to get staff on board and be not just accepting of AI but embracing it. The points above are only scratching the surface of how we might think to go about this. There must be consideration and collaboration that banishes the fear and mistrust brought about by frustrating battles with automated phone lines that haunt our memories of automated and ‘intelligent’ technologies. Progress will not be made by working in isolation and innovators must remember what matters to staff, but also acknowledge the position that the workforce finds itself up against trying to get through each day. In this challenging climate it’s no wonder that health and social care staff may be blind to the advances of AI innovators and digital health companies. As it appears the progress of AI shows no signs of stopping, we will need to work together to make sure it becomes the answer we are all looking for.

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