Can AI rescue health and social care from burnout?
With 2024 drawing to a close, Dr Jonathan Shaw, former surgeon and emergency physician, reflects on issues that have poisoned the sector and suggests smart technology could be the systems only successful antidote.
Lord Darzi’s independent review of the NHS paints a sobering picture of an overburdened system straining under the weight of escalating demands. He highlighted how the service is in a ‘critical condition’ with issues around efficiency and access to services. The report made numerous recommendations for improving the NHS which included driving productivity in hospitals through more capital investment and making more use of technology. Similarly, the NHS England Long Term Workforce Plan, published last year, explicitly called for productivity gains in exchange for expanding staff numbers.
The issues currently faced
A recurring concern voiced by health and social care staff is the substantial amount of time taken up by administrative duties. Health and care professionals find themselves bogged down with clerical work that could be handled by support staff and intelligent systems, diverting precious hours away from their core responsibility – providing exceptional care to individuals. A significant amount of time is spent on tasks such as taking patient notes, reviewing results, care planning, capturing structured information so that coded data can be used elsewhere, or corresponding with colleagues and other care providers. Phone calls or notes in unstructured format need to be typed up and many organisations still collect data manually. The latest LGA survey found that social workers are increasingly weighed down by administrative work and were managing more complex caseloads.
The potential of AI
This is where AI can make a significant impact. Clinical and social care notes are information-rich sources, with complex workflows, making them ideally suited for AI applications. It can not only reduce the amount of manual entry of documentation, but it also allows health and social care providers to streamline processes, optimise resource and provide more proactive care. AI’s capabilities extend beyond just summarisation; it can assist users with the next steps of performing actions and tasks within an individual’s record. This empowers health and social care professionals to focus on what truly matters. The true potential of AI is how it can boost efficiency for both the people using services and the organisations providing them. By putting AI to work on those tedious, time-draining tasks, we can streamline operations like never before.
But it’s about more than just saving time and effort. Bringing AI into the mix creates an opportunity to raise quality standards and consistency across the board. By automating all the monotonous admin work, we free up human experts to focus on the high-level, person-centred aspects that really matter. This allows social workers and clinicians to be present in a conversation with people rather than busy taking notes. Blending human expertise with the power of AI will ultimately improve quality of care. And thanks to AI’s ability to standardise processes based on data-driven best practices, we can ensure the same experience no matter where services are delivered.
The importance of maintaining human oversight and accountability
A crucial principle in the use of AI is maintaining human oversight and validation throughout the process. Ultimately, the final decision-making authority should remain with the human experts, such as social workers or clinicians. They must be the ones to validate and confirm the outputs and recommendations generated by AI systems. For instance, when an AI tool helps to summarise a care plan or handover summary, the social worker or healthcare professional should review and approve it, ensuring its accuracy and appropriateness. There are various use cases and examples where this human-in-the-loop approach is essential across different social care scenarios. While AI can be a helpful tool, we need the expertise and judgment of human care professionals to lead the way. This is especially true in social care – for example, if an older person says they want to see the moon, AI might take that literally, but a human caregiver would understand the deeper meaning behind that wish and find a more meaningful way to address it in their care plan. Social care is all about complex human emotions and needs that AI alone can’t fully grasp. By combining human understanding with AI’s analytical abilities, we can provide truly personalised, empathetic care.
Safety and ethical practice are paramount
Ensuring the safe and ethical integration of AI is critical. There are many temptations to cut corners and approach it in a more cost-effective but potentially exploitative way, especially when it comes to health and social care data, but we must have robust safeguards and oversight so that we don’t misuse personal data. Prioritising privacy, transparency and responsible data stewardship is key here. This balanced approach, which places the wellbeing of individuals and communities at the forefront, is critical to upholding high ethical standards when it comes to AI. If we start using ChatGPT or Google translate for writing patient letters, for example, there is no assurance of patient confidentiality.
But doing all this properly isn’t easy – the process of implementing and maintaining specialised health and care technologies can be costly and complex. There’s a significant amount of governance and overhead involved in setting up these systems appropriately. What’s more, the social care sector tends to have less regulation compared to the healthcare industry, meaning that these technologies are not always treated as medical devices in the same way. This creates additional risks and challenges when deploying these types of solutions. At System C this is something we’re very passionate about. We’ve partnered with Microsoft to ensure we’re creating a properly governed system which complies with NHS guidance around data processing. We’re making sure that the data we put into our AI system is secure, compliant and safe.
Ultimately leveraging AI efficiencies is not just about doing things quicker or cutting costs. It’s a chance to totally transform operations and set new benchmarks for quality. Timely and informed actions at the outset can significantly reduce the length of hospital stays and provide the best possible care outcomes, therefore unlocking other benefits as a result but it must be pursued with robust safeguards and a commitment to ethical AI principles to harness its full power.
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