It’s been difficult to escape the far-reaching buzz around artificial intelligence (AI) in recent months.
Every industry has the potential to be transformed by it. However, nowhere is its productivity promise more needed than in healthcare.
With junior doctors announcing further strike action in August and consultant doctors in September, the plight of our overworked and under resourced medical professionals is once again being highlighted.
Add this to the well-publicised appointments backlog and the fact that the population is aging and it’s clear that an AI-driven revolution cannot come soon enough.
The recent explosive growth of foundation and large language models, such as GPT-4, points to a future in which clinicians and patients are empowered with personalised medicine, clinical decision support, increased patient access, and workforce optimisation.
But while the overarching promise for the future of generative AI in healthcare is clear, there are also ways in which this technology is already shaping healthcare delivery today.
Solving healthcare’s biggest challenge
The healthcare industry is laden with administrative processes; many of which are manual, paper-based, time-consuming and error-prone.
Inefficient healthcare workflows can occur in outpatient management, appointment management, consultations, diagnostic investigations or any other part of the healthcare journey.
In every instance, they have a negative impact on clinicians, patients, and healthcare organisations.
Inefficient workflows can mean that patients experience long wait times for appointments.
When they do eventually access treatment, their care could be severely impacted by inaccurate or missing information in electronic patient records (EPRs).
Meanwhile, clinicians often become frustrated, burned out, and overworked, due to these inefficient workflows.
This is unsurprising when you consider previous research by Nuance found that the average clinician is spending 13.5 hours per week on clinical documentation, up more than 25% from 7 years ago.
To make matters worse, 3.2 of these hours are taking place outside of working hours, with healthcare professionals having to give up their personal time.
But it doesn’t have to be this way.
AI technologies have the power to transform healthcare, particularly when it comes to medical documentation and common clinical tasks.
An AI revolution is underway
Modern technologies, such as AI–powered speech recognition, can be used to help relieve some of the administrative pressure on clinicians, enabling them to work more efficiently and intelligently.
These technologies are designed to recognise and record passages of speech, converting them into detailed clinical notes, regardless of how quickly they’re delivered.
By reducing repetition and supporting standardisation across departments, they can also enhance the accuracy as well as the quality of patient records.
For example, voice activated clinical note templates can provide a standardised structure to a document or letter, thus meeting the requirements set out by the PRSB (Professional Record Standards Body).
Frimley Health NHS Trust is a prime example of an organisation that has benefited from this technology.
In the past, the Trust has relied on transcription services and handwritten reports for document and letter creation.
This process worked, but it was slow and inefficient. Paper records had to be scanned, then entered into electronic systems.
Letters had to be typed up and sent out to patients and GPs.
With the move to an Epic EPR, the Trust wanted to keep its staff using their voices—but it also wanted to ensure they could create documents and letters in a much more efficient, real-time way.
Frimley chose Nuance’s cloud-based speech recognition solution, Dragon Medical One, which accurately translates the voices of doctors, nurses and allied health professionals into detailed clinical narratives that feed directly into a Trust’s EPR.
In the future, the most advanced solutions will combine conversational, ambient and generative AI to make the documentation process even more efficient.
These tools can automatically and securely create draft clinical notes in seconds for immediate clinical review and completion after each patient visit.
They work for both in-person examinations or remote (e.g. telehealth) appointments, meaning that patients get the best experience, regardless of how they access treatment.
With so much increasingly complex clinical documentation to get through, the ability to create detailed, accurate documents using voice alone can give clinicians back hours in their working day.
Those hours quickly stack up over weeks and months, to help them to see more patients and achieve a better work/life balance.
As AI’s use in healthcare continues to evolve, there’s no doubt that investment in the technology is only going to increase.
In fact, NHS England is already investing in various pilots which use the technology, with £123 million earmarked for AI projects over the next four years under the AI in Health and Care Award.
This investment could be the key to relieving some of the administrative burden faced by our clinicians and helping to reduce burnout levels throughout the sector.
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