Healthcare professionals are using AI to improve a range of services, from cancer detection to the provision of care for long-term conditions.
AI is streamlining administrative tasks, improving patient outcomes and supplementing the work of doctors and care providers. What’s more, the role of AI in health and social care is only set to grow.
It’s incumbent on leaders to start implementing this transformative technology in a meaningful way, irrespective of whether they’re working in the private or public sectors.
In this article, we’ll provide a roadmap for integrating AI into your organisation. We’ll also alert you to common pitfalls and offer some guidance for navigating the often thorny issue of AI ethics.
Contrary to common understanding, the use of AI in health and social care is not new. AI fully entered public awareness in the last several years, catalysed by the release of ChatGPT. However, research into the medical applications of AI dates back well over fifty years.
Because of its ability to monitor and analyse complex inputs, individuals at risk of common health concerns can use AI for preventative purposes.
Wellbeing tracking apps are one example. The NHS is also trialling AI for the analysis of patient data to preemptively find and assist patients with complex needs when they are most vulnerable in the winter months.
Because of its ability to monitor and analyse complex inputs, individuals at risk of common health concerns can use AI for preventative purposes.
Wellbeing tracking apps are one example. The NHS is also trialling AI for the analysis of patient data to preemptively find and assist patients with complex needs when they are most vulnerable in the winter months.
AI is increasing the accuracy and speed with which professionals can make diagnoses. For example, researchers at Imperial College London have used AI to detect the causes of stroke and dementia, surpassing the accuracy of current methods. The NHS is also using AI to help with disease screening, particularly cancer.
Because AI can analyse vast amounts of patient data in ways not previously possible with rule-based automation, professionals are using it to provide greater levels of tailored care. Researchers at the University of Leeds have led a project aiming to improve end-of-life care for the terminally ill. Another example is Woubot, a phase one winner of the NHS Ai in Health and Care award, which generates personal care recommendations for chronic lower limb wounds.
NHS mental health services have historically suffered from underfunding. AI is helping to meet the growing demand for psychological treatment through automated symptom assessment, virtual treatment in addition to in-person services, and preventative tools like Biobeats, an innovative application developed by the private sector.
AI is helping to streamline healthcare operations in a multitude of specific cases.
AI is helping the NHS and social care providers streamline administrative tasks in a number of areas, easing the burden of entering, managing and retrieving disparate and complex data.
While much of the commentary and excitement centres on the application of AI to specific healthcare settings, social care is also experiencing a significant AI-oriented shift. There are many ways that AI is helping to positively shape the social care space.
In addition to the automation of time-consuming manual and data-related tasks, AI is also being used to help train members of staff. One interesting application is the use of avatars developed by health innovator Cera to impart new skills, like how to spot the signs of a stroke.
Enhancing community engagement with AI
AI gives social care leaders new ways of identifying, understanding and responding to community needs. For example, automated analysis tools can be used to track changing customer sentiments and feelings about social care services collected through surveys. AI-driven chatbots can also be leveraged to reach out to community members to provide updates and important information.
Predictive analytics for preventative care
Predictive analytics help care providers identify areas of risk and respond accordingly. This has the effect of reducing the burden on GPs and limits the progression of illnesses with the potential to detrimentally affect the quality of life of those under care. For example, predictive analytics and remote monitoring has been used by the NHS to help elderly people avoid intensive care settings.
Data-driven and collaborative improvements across multiple organisations
AI can process and interpret vast amounts of data. Data collaborations, such as the one driven by a group of social care and NHS organisations in the Midlands, provide access to large datasets which provide insights into broad, holistic opportunities to improve operational efficiency and patient care. They also allow staff to predict where future pressure points are likely to arise.
Ethical considerations and challenges
While the presence of AI in health and social care has been overwhelmingly positive, leaders are nonetheless faced with a multitude of ethical challenges. Because in most cases these issues elude easy solutions, they will likely continue to evolve and be discussed as AI’s presence continues to grow.
AI integration in health and social care settings will inevitably vary between organisations. However, there are several general steps for successfully integrating this cutting-edge technology.
A handful of important trends are shaping the future of AI in health and social care. They are laying the foundation for an integrated, ethical and collaborative global healthcare system that incorporates AI.
The powerful combination of AI and traditional health and social care is cause for optimism. While there is much talk about the dangers and pitfalls of AI, including the opportunities it gives to bad actors, in most cases it is genuinely changing lives for the better, and this trend looks set to continue.
The potential of AI is undeniable. But there is a risk of falling behind. Now is the time for leaders to start embracing AI in a meaningful way and powering the digital evolution that can free up resources, improve patient outcomes and change lives for the better.
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