How we’re using technology to aid healthcare processing
I am Lead Cloud Architect for all digital, insight and technology solutions here at the NHSBSA. I joined in February last year and since then I have been engulfed in the world where artificial intelligence (AI) is moving from a back-end tool to the forefront of patient and clinicians day to day working life.
As an Arm’s Length Body of the Department of Health and Social Care, we provide a range of critical services to NHS organisations, NHS contractors, patients and the public, such as NHS Dental Services, Prescription Services and now, NHS Jobs.
Using AI and Machine Learning to aid healthcare processing
We’re currently undergoing a large number of initiatives to make improvements and efficiencies to the services we deliver, from the front end digitisation of services, to using AI, Robotics and Machine Learning to provide efficiencies within processing.
Our aim is to support patients and healthcare professionals in the daily management of their healthcare and become a ‘catalyst for better health’. To do this we have to provide the best experiences possible for our customers, reduce cost overheads and make best use of the data held to benefit the NHS and wider healthcare sector.
By taking advantage of these technologies within healthcare, we can use the data we’re responsible for to add value in more ways than we have before. Increased accuracy of data insights can help with fraud detection, medical errors and future analysis to better prepare for changes in healthcare in the future.
Cloud is the accelerator in the use of AI and Machine Learning
With the introduction of cloud computing, the adoption of AI and Machine Learning has accelerated. Technology has become more accessible for public consumption and no longer requires major investments. Two of the main cloud providers, Amazon and Microsoft, also have AI and Machine Learning services dedicated to the healthcare sector.
- Amazon recently introduced ‘Comprehend Medical’: a natural language processing service that makes it easy to use machine learning to extract relevant medical information from unstructured text. When using the service, you can quickly and accurately gather information such as: medical condition, medication, dosage, strength, and frequency. These are pulled from a variety of sources like: doctors’ notes, clinical trial reports, and patient health records. The Machine Learning service by Amazon Web Services allows the extraction of medical information to build applications for use in cases like clinical decision support, drug spend management and drug information processing. These can then be factored into other systems such as: fraud detection, forecasting of drug spending and mapping of patient data for insights.
- Microsoft’s project ‘EmpowerMD’: aims to create an AI powered system that can capture and integrate medical expertise at scale by listening and observing doctors doing their work as they meet their patients. It (cleverly) captures and synthesizes patient-to-doctor conversations whilst maintaining privacy and data compliance. Its goal is to allow healthcare professionals to spend more face-to-face time with patients, by bringing together many services from Microsoft’s Intelligent Cloud including Custom Speech Services and Language Understanding Intelligent Services, customised for healthcare.
But with new technology comes more responsibility, and the initial Code of Conduct provided by the Department of Health and Social Care for data-driven health and care technology gives assurance that the technologies that we’re using are aligned to the Government’s objectives. It also shows how we’re meeting the needs of our partners in: academia, healthcare professionals, patients, clinicians and the wider public.
Where the NHSBSA is taking advantage of these technologies
We are running a number of concept projects to understand how using AI and Machine Learning can benefit the services we provide to our customers, UK citizens and NHSBSA employees. One of these concepts we are looking into is using machine learning on our prescription processing.
We scan and process approximately 50 million prescriptions per month generated by pharmacists, general practitioners, nurses and other sources nationwide. The current process involves manual checks at certain points of the process, where prescriptions can’t be read correctly by the automated scanners. Watch our short video to see this process in action.
Introducing AI and Machine Learning into prescription processing will improve the services that we offer to our customers and our partners within the NHS in a number of areas, such as:
- Accuracy in processing of prescription payments to pharmacies, meaning a reduction in payment errors made due to misreading of the paper based prescription forms
- Detection of fraud, leading to a reduction in fraudulent use of prescription forms, which can cause financial loss to the NHS as well as harm to people who use drugs obtained illegally
- Detection of medical irregularities (the mis-prescribing and misuse of drugs) within the NHS, to reduce any endangerment to human life
- Increased job satisfaction for processing. By removing the repetitive nature of data entry, our staff can focus on customer interactions and the training of Machine Learning models, which results in a better experience for customers
- Enabling near real-time data insights with thanks to cloud technologies, meaning we can gain more knowledge in the medication that is being prescribed within the UK, and the how, where, when and to whom it’s being prescribed, to help medical research and academics with their studies and recommendations for improvement
- Delivering more effective treatment due to the ability of building ‘medical maps’, to understand what and where patient treatments are being used by GP’s and pharmacies, and the effectiveness of these treatments, whilst also enabling GP’s and pharmacies to forecast medical conditions such as diabetic treatments, planning winter medical care, and monitoring drug stocks
Technologies such as AI and Machine Learning are evolving at a rapid pace and improving the way in which we live, so it is absolutely key that healthcare takes advantage of these technologies. This could be anything from medical data processing, to a form of robots in operating theatres, all with the aim of providing the best outcomes for healthcare professionals and patients.
At the NHSBSA we see the use of this technology as being one of the contributions towards our goal of ‘catalyst for better health’ and improving efficiencies within the NHS.
Contact firstname.lastname@example.org if you have any questions or would like to learn more.
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