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4 min read
AI and Healthcare: The Future of Medicine
By
Dr. David Garley (MRCGP)
Artificial intelligence (AI) is reaching all parts of our lives, from managing factories to personalising adverts to even controlling the temperature within our homes. But how has healthcare been changed by AI and how will it be managed in the future?
AI refers to technology that can mimic human intelligence. It can learn and to an extent, think. Mostly when we consider AI, we imagine software and machinery that is far more advanced than the present reality. However, the majority of AI healthcare applications are perhaps more humble than you might think.
How is AI used in healthcare today?
AI is already established throughout the medical field. However, before exploring these present applications, it is worth reflecting on what healthcare actually is and what its component pieces are.
The key point here is that AI in healthcare is not just about clinicians - it’s not just the doctors, nurses and pharmacists delivering care at the patient interface. It includes the administration of huge numbers of patients and the management of even bigger volumes of associated data. From AI medical diagnosis tools to generative AI in healthcare, AI applications are relevant across all these domains.
Furthermore, healthcare itself does not live in a vacuum. Healthcare needs to understand the drivers of health:
• Why do people get ill?
• Why don’t they get better?
AI can work across the full range of these sectors to help answer these questions.
Improving administrative efficiency
A core role of AI in medicine and healthcare is the automated processing of admin and data.
From assisting with basic office tasks to streamlining outpatient management, including appointment scheduling, patient billing and communications, AI is revolutionising these tasks. AI can even assist with bed allocation within hospitals—a role as complex as an air traffic controller managing a small airport. A reported 55% of healthcare professionals believe medical AI boosts efficiency in outpatient clinics1 . AI can use voice recognition to automatically produce summarised notes of a medical consultation, which saves vital clinician time.
During my training, most of my undergraduate education was focused on clinical medicine, but in reality, over half of my time during the first two years of practice was consumed by administrative tasks:
• Writing notes
• Ordering tests
• Producing discharge summaries
In this context, the benefits of AI in healthcare become clear: every hour it saves a doctor in admin means an extra hour available for clinical work, directly impacting patient care.
AI medical diagnosis
One of the most progressive uses of AI is in diagnostics. Many diagnoses, whether they involve blood results, X-rays, CT scans, or laboratory slides, require the analysis of similar data sets.
AI in medical diagnosis collaborates with clinicians to speed up the diagnostic process, stratifying samples into high- and low-risk sets and flagging areas of concern to improve both speed and accuracy. 68% of healthcare professionals believe AI in healthcare is helpful1 , reflecting its growing importance in medical settings.
Personalised medicine with AI
Modern medicine is producing massive volumes of data, particularly as we delve deeper into the human genome. AI in healthcare provides the ability to process this large-scale data in a timely manner. Generative AI in healthcare and similar tools enable the effective use of data for targeted therapies, particularly in fields like oncology. With AI in medicine, subsets of cancer can be identified, allowing for the application of more effective treatments.
Where is AI in healthcare heading?
The future of AI will continue to address key challenges in healthcare delivery, particularly cost and workforce efficiency.
Reducing workplace costs
AI in medicine has the potential to significantly reduce workforce costs through streamlined processes. AI healthcare applications will allow clinical staff to focus more on patient care, increasing the clinical hours of staff like nurses and doctors and dramatically reducing overall costs. 62% of healthcare professionals think AI can reduce healthcare costs1 .
Autonomy in diagnostics
One of the most exciting future possibilities is the potential for AI autonomy in diagnostics. While AI currently works alongside clinicians, the eventual goal may be for AI to take full responsibility for certain diagnostic decisions. This will be a step by step process requiring rigorous validation. However, concerns about the empathy of AI systems may mean that they will never fully replace human-led consultations.
As we look ahead, questions arise, such as how AI will be very useful in medicine when it reaches this point. How will it interact with the existing medical workforce? How will AI in medicine and healthcare handle issues like responsibility for clinical accuracy?
Governance and ethics
As AI continues to integrate more deeply into healthcare, ensuring robust governance and ethics will be crucial. How can AI be used in healthcare responsibly? This question is key as we consider the ethical and technical oversight needed to safeguard patient data and privacy.
Healthcare providers and AI tech companies must collaborate to manage information governance, patient safety and privacy in this high-stakes field.
What does all of this mean for AI’s future in healthcare?
AI is undeniably a part of healthcare’s future.
As technology evolves, the role of healthcare providers will be to ensure its development is safe, efficient and effective. By embracing AI and integrating it responsibly, we will see the benefits of AI in healthcare transform patient outcomes. But with this transformation comes the need to stay informed about the advancements AI brings and ensure its integration benefits everyone.
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References
1 SERMO (2024) AI In Healthcare. Online Poll. January 2024.
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