How AI Is Optimizing Patient Care in General Practice

Doctors face an ever-increasing patient load with those across the NHS seeing more than 35 patients daily. This challenge is compounded by more patients presenting with complex conditions and co-morbidities and clinicians find it increasingly difficult to make informed clinical decisions while processing vast amounts of medical information daily.

AI as a Potential Solution

When we lack the tools to access and apply the latest medical knowledge, patient outcomes suffer. The challenge of managing vast amounts of medical knowledge, time pressures and patient expectations, stretches our cognitive capacity and raises the risk of treatment oversight.

As the NHS advances towards digital reform, artificial intelligence emerges as an aid to support healthcare professionals in revolutionizing practice. Elsevier’s Insights 2024: Attitudes towards AI report reveals this, finding that 96% of clinicians believe AI will help accelerate knowledge discovery and 85% say it will free up time for higher value work.

While some doctors already incorporate search engines and conversational AI into their daily routine, this approach requires them to use their expertise to dictate when and how to use these tools effectively, consider their strengths and limitations and vet any unreliable answers or AI hallucinations. Now more than ever, clinicians need support from specialized AI technologies that deliver the right information, at the right time, to improve the quality and efficiency of care.

Related:The Transformative Power of AI for Industrial Enterprises

Streamlining Clinical Workflow

For me, generative AI is a valuable tool to support my clinical decision-making by providing evidence-based content at the point of care, ultimately enhancing patient outcomes and improving the overall efficiency of healthcare delivery.

While generative AI tools available in the public domain can surface information, they don’t work with clinical workflows in mind. Instead, they operate as “black boxes”, leaving users unaware of the underlying mechanisms and the credibility of reference materials used to generate responses.  

Healthcare professionals are in critical need of AI tools designed specifically for clinical use that function as “glass boxes”, with responses grounded in evidence-based content and clear source references.

Related:Semiconductor Technology: The Key Enabler for AI-Driven IoT Revolution

I have adopted advanced clinical decision support tools in my practice that harness generative AI, offering trusted, evidence-based content at the point of care. These tools facilitate easy access to reliable medical information and enable conversational search for deeper insights.

Importantly, their true value lies in augmenting, not replacing, clinical expertise. In my experience, they serve as invaluable allies in delivering optimal patient care while alleviating cognitive and time burdens.

The Future of Care Delivery

Supporting clinicians with specially designed AI large language models can combat cognitive burnout by providing rapid access to relevant medical information and drastically reducing the time required to perform administrative tasks. In turn, this aids the overall patient experience by allowing more meaningful interactions between them and their doctors.

Responsible integration of AI technologies presents significant opportunities for healthcare, equipping clinicians with reliable and cohesive tools that streamline workflows. By embracing this enhancement thoughtfully, we can transform the healthcare landscape and enable healthcare professionals to devote their attention to what truly matters, providing high-quality care to their patients.

This article first appeared in IoT World Today's sister publication AI Business.