As artificial intelligence continues to shape the future of healthcare, a new AI tool being trialled in the NHS promises to enhance administrative efficiency
CREDIT: This is an edited version of an article that originally appeared on The Independent
Artificial intelligence tools have become widely popular, but questions remain about their medical safety and reliability. One AI assistant currently being trialled in the NHS is designed to improve efficiency by capturing key medical information while filtering out irrelevant details.
This AI technology is being tested in London, with leadership from Great Ormond Street Hospital for Children (GOSH) and aims to help doctors focus more on patient care by automating tasks such as writing documents and letters. The tool is expected to reduce administrative burdens, freeing up time for healthcare professionals.
What is Ambient AI?
Ambient AI refers to artificial intelligence that is seamlessly integrated into the environment, making it available in the background to enhance daily activities without requiring active engagement. It works by sensing, interpreting and responding to its surroundings, often in real-time. Smartwatches and fitness trackers like the Apple Watch or Fitbit use ambient AI to monitor users’ health metrics, such as heart rate and steps taken.
The AI used in this case employs ambient voice technology, combining speech recognition and artificial intelligence to capture relevant medical information from conversations while filtering out background noise and unrelated discussions.
What Could This Mean for Practices?
The tool is designed to reduce the time doctors spend on administrative tasks by automatically drafting notes, follow-up letters and suggesting clinical codes, which are then reviewed by the physician. Doctors at GOSH report that the AI improves clinic efficiency, minimises administrative workloads and enhances the overall experience for both healthcare professionals and patients.
Is it Accurate?
In an earlier phase of the trial, actors posed as patients and attempted to deceive the AI by discussing fictional characters, providing false information, speaking with different accents and introducing loud background noise. Despite these challenges, the AI successfully identified the relevant medical information and generated clear clinical letters.
While the trial appears to demonstrate positive benefits in terms of efficiency and accuracy, concerns regarding data protection have been raised. Ensuring that patient data is securely handled and protected remains a key issue as AI tools become more integrated into healthcare settings. As the technology evolves, it will be crucial to address these concerns to maintain trust and ensure that patient confidentiality is upheld.
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