Having a good grasp of NHS Hot Topics is incredibly important for your UK Medical School Interviews, in particular, the idea of the modernisation of medicine through Artificial Intelligence (AI).
The NHS may currently, be known for its overstretched services, but the UK government hopes that Artificial Intelligence (AI), could be its saviour.
AI is a growing field in healthcare, and knowledge of its current use and future potential could set you apart from other candidates at your UK Medical School Interviews.
This comprehensive guide will teach you everything you need to know about Artificial Intelligence, how it can benefit the healthcare sector and the ethical considerations associated with this.
Artificial Intelligence in Healthcare Summary - What Do I Need To Know
Artificial Intelligence (AI) is transforming healthcare by automating tasks, improving diagnostics, and streamlining operations.
The UK government is investing in AI integration into the NHS, adding to its existing, but limited use in 2023 - making AI an upcoming NHS Hot Topic.
In 2023, AI is already aiding radiologists, powering virtual wards, and identifying patients at risk of chronic illnesses.
AI offers faster data analysis, streamlined hospital operations, and earlier disease identification, but it raises concerns about bias, data privacy, and patient trust.
The use of AI in healthcare raises ethical issues, including data privacy, bias, accountability, and the balance between AI and clinical judgment.
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What is AI?
Artificial Intelligence, or AI, is a self-learning technology that allows computers to do tasks previously required to be done by humans. It describes computers having the ability to “think like humans”, and execute tasks such as pattern recognition, decision making and judgement.
Artificial intelligence, or AI, is when a computer or machine can perform actions that would be thought to require human intelligence.
As of 2023, the UK government is pushing for AI tools to be integrated into the NHS, and have launched a £21 million fund to support this.
What is the current role of AI in Medicine?
The relation AI has to medicine is becoming increasingly important as technology is implemented to reduce waiting times, give more personalised care and much more.
One of the main goals of the NHS Long Term Plan is prevention and more accurate diagnosis by 2030, and AI is the gateway to making this change.
Below are some of how AI is changing the medical field, and how this impacts the doctor-patient relationship!
AI in medicine is a developing field, with limited current use deployed within the NHS but vastly invested in by private healthcare fields.
The scope for AI application in the medical profession includes:
Diagnosis - AI systems can be trained in pattern recognition to process large numbers of scans and correctly identify pathology.
Treatment - AI can be used in the development of personalised treatment plans for patients, taking into account their comorbidities and past medical history.
Surgery - Engineers are working on AI Robots capable of performing surgeries, such as routine, non-complex operations. Through reduced human error, these may improve patient’s surgical recovery outcomes.
Drug Discovery - AI can be used in identifying new drug targets and screening drug candidates.
Admin - Operational efficiency within a healthcare system can be used by automating administrative tasks using AI.
Recently, Prime Minister Rishi Sunak announced that there would be £100m of funding for the uses of AI in science and healthcare. This would be a great fact to bring up at your medicine MMI interview this year.
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Examples of AI in the NHS
As mentioned AI has limited use in the NHS as it currently stands. However, the following areas have implemented AI tools to:
Support radiologists through screening X-ray images for red flags or concerning features. This helps focus the radiologist's time on more complex cases or ambiguous scans.
Virtual Wards - Provide hospital-level care and treatment from healthcare staff, whilst patients are still at home. AI facilitates this through its smart monitoring of patient’s health parameters.
AI algorithms are being used to screen mass amounts of patient data to highlight patients at risk of developing heart disease and other chronic illnesses.
AI Supporting clinical decision making.
AI can access a breadth of information about treatment plans, as well as patient history rapidly - for this reason, it gives doctors context to make well-informed decisions about their patients.
For example, organisations like DrDoctor have products that assist with streamlining information (patient details, family history, ensuring all information is on one database) - freeing up time to see more severe patients in clinics. This aids doctors and nurses with the triage of different patients, as AI can flag up concerns automatically.
Radiology & AI
Recently, NICE (National Institute for Health and Care Excellence) approved several AI organisations, one of which is called AI-Rad Companion Organs RT - to produce ‘contours’ of radiograph images, a process normally done manually, with only minor edits needed from healthcare professionals.
This speeds up diagnosis and allows doctors to spend more time with their patients.
Analysing mammograms - supporting radiologists in their assessments as well as increasing the time spent with their patients - directly benefiting the doctor-patient relationship.
Virtual wards & AI
The MDT (multidisciplinary team) can remotely monitor a patient’s health while being cared for from home. For example, a remote monitoring Hub was set up in the North West region to support patients with COPD, heart failure, type 2 diabetes and COVID-19.
It is available 365 days of a year and supports around 5500 people daily. The results have shown an increase in capacity and a reduction in hospital admissions for chronic patients.
Prostate Cancer Screening & AI
Addenbrookes Hospital in Cambridge uses Microsoft InnerEye to analyse scans for patients with prostate cancer. The software outlines the image, highlighting the tumour location and then reports back based on its findings. A consultant can then analyse the report, cutting down on the time spent preparing for scans, as well as reducing the wait between referral and treatment.
HeartFlow & AI
A system of scanning a patient’s heart, and creating a personalised 3D model to observe blood flow, immediately identifying blockages. This process would normally be carried out with a coronary angiogram, a type of X-ray used to examine blood vessels (a dye is injected into the specific area, illuminating the vessels). Using HeartFlow is, therefore, less invasive, and faster and makes visualising the blood vessels easier.
👉🏻 Read more: Common NHS Hot Topics
AI in the NHS: Government Initiatives
The UK government has announced its commitment to the integration of AI into the NHS.
In hopes of modernising healthcare, the government has allocated a substantial investment of £21 million to support the incorporation of AI tools and technologies within the NHS.
This finance aims to fund the development of new and upcoming AI systems which can benefit patient care in the NHS, as well as integrate existing AI tools into the current NHS infrastructure.
These steps aim to bring the NHS into the modern technological age, an area which has long been neglected within the NHS budget.
AI in healthcare: Benefits and Risks
For your medical school interview, you may be asked to weigh up the use of artificial intelligence in healthcare.
This will require a background level of knowledge of the advantages and disadvantages of this technology.
Advantages of Artificial Intelligence in Healthcare
Faster data analysis - AI allows the processing and analysis of vast amounts of medical data, providing improved diagnostic times.
Streamlining of hospital operations - AI can be used to automate administrative tasks. This reduces the administrative burden on healthcare workers, allowing them to focus on patient care.
Earlier identification of at-risk patients - AI can be used to rapidly analyse patient databases and compare their characteristics to scoring systems, like Q-RISK, to identify patients at risk of disease earlier.
Telemedicine - AI can be used within online platforms to allow patients to access medical advice, as well as allowing remote consultations.
Drug Discovery & Personalisation of Treatment - AI can be used to identify potential medications for a patient’s condition and predict their efficacy, saving time and resources based on the patient’s characteristics.
Disadvantages of Artificial Intelligence in Healthcare
Bias - Given that AI systems are trained using data, it means that AI systems are very liable to bias. Given that there is historical medical negligence in some communities, this may mean that the medical suggestions or treatment provided by AI are discriminatory.
Security and data privacy - AI systems require data from patients to learn and complete their required tasks. If these systems are storing and processing large amounts of personal data, there is a risk of cyberattacks or data breaches. Data protection is an integral concept - the safeguarding of sensitive and personal data that is collected, processed and stored by AI systems. This can be patient details, their history and any other confidential information.
Patient Trust - Many patients struggle with the use of technology and prefer to see doctors face-to-face. This is a common theme with many patients feeling that Artificial Intelligence is not trustworthy enough for it to be used in their healthcare.
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AI in the NHS: Ethical Concerns
Many of the ethical concerns around artificial intelligence in the NHS and healthcare relate to the above disadvantages.
Data Privacy - if large AI companies are obtaining patients’ healthcare data, there are ethical concerns that data could be misused, breached or sold without patient consent.
Bias - As mentioned above, due to the data AI uses, it could lead to discriminatory results from the AI. These may lead to perpetuation or exacerbation of existing healthcare biases and discrepancies.
Accountability - If an AI misdiagnoses a patient, who is held accountable, and how can lessons be learned?
Complexity - AI algorithms are highly complex, and so understanding the decision-making made by an AI is incredibly difficult. As their ethical duty, doctors and healthcare professionals must be able to understand and challenge decisions made by an AI.
Clinical Oversight- Should AI override a doctor’s clinical judgement of a situation?
👉🏻 Read more: Answering Medical Ethics Questions
Medical AI: How To Prepare for AI-related Medical School Interview Questions
The best way to prepare for any medical school interview question is to practise, after getting a good grasp of the content they could ask you about.
For artificial intelligence, it’s important that you explain to your examiner:
What artificial Intelligence is
How it is used currently, and how could it be used?
The benefits and drawbacks of AI in the healthcare field
The ethical concerns regarding AI use in the NHS
To impress your examiner, consider how you can link the use of AI to the 6 core values of the NHS. Contemplate whether AI in healthcare helps the NHS embody these values, or whether it contradicts them.
👉🏻Need more help? Consider 1:1 Medicine Interview Preparation
Artificial Intelligence Medical Interview Question and Model Answer
Do you think AI should be allowed to make clinical decisions without supervision from senior medical professionals?
The potential of AI in healthcare is certainly exciting, offering the possibility of faster and more accurate diagnosis and treatment recommendations. However, fully autonomous clinical decision-making by AI systems raises important concerns that need to be carefully considered.
On the one hand, AI has the ability to analyse huge amounts of patient data and detect patterns that humans may miss. Recent advances in deep learning have enabled algorithms to match or even surpass human performance in specialised tasks like reading radiology scans. Allowing AI greater autonomy could improve efficiency and reduce human errors.
However, AI lacks human judgement, empathy and the ability to deal with nuanced or unexpected situations. Take the example of IBM's Watson for Oncology - while it has ingested vast amounts of cancer data and guidelines, doctors found that its treatment recommendations were often not tailored to individual patients' needs or took important quality-of-life factors into account. Its suggestions needed to be heavily supplemented by experienced oncologists.
In my opinion, AI should not fully replace doctors' skills and experience but complement them - forming an effective doctor-AI partnership that enhances healthcare while ensuring patient wellbeing remains the priority. AI is able to learn through data, which can certainly provide valuable insights and recommendations, but the expertise, empathy, and ethical considerations that human medical professionals bring to the table are irreplaceable.
With continued research and transparency from technology companies, AI in medicine can greatly improve care, but the human touch must not be lost. Humans understand patient anxieties and preferences in a more holistic manner.
👉🏻 Read more: Ultimate Medicine Interview Preparation Guide
AI Medicine Interview Questions To Practice:
How does AI impact the process of diagnosing medical conditions, and what are the potential advantages and disadvantages for healthcare professionals and patients?
Can you provide an example of a specific AI application in healthcare that has improved patient outcomes?
In what ways can AI help optimise the allocation of healthcare resources, and what ethical considerations must be taken into account when using AI in resource management?
Discuss the role of healthcare professionals in ensuring the ethical use of AI in medicine. How can they strike a balance between AI assistance and clinical judgment?
What measures can be taken to address bias and fairness in AI algorithms used for healthcare, especially when considering historical biases in medical data?
Explain the concept of data privacy in AI-driven healthcare. What safeguards should be in place to protect patients' sensitive medical information?
How do you envision the future integration of AI in medical education, and what benefits can it bring to medical students and practising physicians?
Describe a scenario where an AI system's decision conflicts with a healthcare professional's clinical judgment. How would you address this situation ethically?
Discuss the potential challenges and ethical concerns associated with using AI in drug discovery and personalised medicine. How can these concerns be mitigated?
Given the potential for AI to automate administrative tasks, how do you see this affecting the roles of healthcare workers in the future, and what ethical considerations are involved in this transformation?
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Artificial Intelligence in Healthcare FAQs
What is Artificial Intelligence (AI) in healthcare, and why is it important?
AI in healthcare involves the use of self-learning technology to perform tasks traditionally carried out by humans, such as diagnostics, treatment planning, and administrative work. Medical students should be aware of AI's significance because it's revolutionising healthcare, making it more efficient and effective.
How is AI currently being used in the NHS in 2024?
As of 2024, the NHS is gradually integrating AI into healthcare. Current applications include supporting radiologists in screening X-ray images, virtual nursing through smart monitoring, and using AI algorithms for the early identification of at-risk patients.
Can you provide an example of how AI can assist in diagnosis and treatment?
AI can analyse extensive datasets to identify patterns and anomalies in medical images, helping with early diagnosis. It can also assist in the development of personalised treatment plans based on a patient's medical history and comorbidities. Examples include DrDoctor, Healthflow and in Prostate Cancer.
What are the advantages of AI in healthcare?
AI offers faster data analysis, streamlining of hospital operations, earlier identification of at-risk patients, telemedicine capabilities, drug discovery support, and personalised treatment options. These benefits improve patient care and healthcare efficiency.
What are the potential drawbacks or disadvantages of AI in healthcare?
Disadvantages include the possibility of bias in AI algorithms, concerns about data security and privacy, and patient trust issues, as some patients may prefer face-to-face interactions with healthcare providers.
How does AI in healthcare align with the core values of the NHS?
AI can support the NHS core values by improving efficiency, ensuring patient-centred care, and enhancing patient safety. However, ethical concerns, such as bias, need to be addressed to ensure alignment with these values.
What ethical issues are associated with the use of AI in healthcare?
Ethical concerns include data privacy, potential bias in AI algorithms, accountability for AI-related errors, the complexity of AI decision-making, and questions regarding whether AI should override a doctor's clinical judgment.
How can medical students contribute to the responsible use of AI in healthcare?
Medical students can play a role in advocating for ethical AI practices, staying informed about AI advancements, and participating in ongoing education related to AI in healthcare. They can also engage in discussions on patient-centred AI applications.
What is the role of the UK government in promoting AI integration in the NHS?
The UK government has allocated a £21 million fund to support the integration of AI tools into the NHS, emphasising the importance of modernisation in healthcare and the potential benefits of AI technologies.
How can doctors ensure that AI benefits patients and addresses ethical concerns?
Healthcare professionals should actively engage in the development, integration, and oversight of AI systems in healthcare. They can participate in the design of ethical frameworks, stay informed about AI developments, and prioritise patient trust and well-being.
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