What is AI in healthcare?

AI in healthcare is getting more sophisticated and efficient at supporting doctors and other medical professionals. Not only does this provide a real opportunity for growth within the profession, but it also means that tasks can be completed more quickly and at a lower cost.

The potential for AI in healthcare is huge, as it has the ability to apply problem-solving techniques that humans could not do alone. In 2019, 46% of healthcare organisations in the UK were using AI technology, which indicates how widely it is already used.

With no signs of slowing down, the growth of AI in healthcare is a trend worth recognising and familiarising yourself with. In this article, we’ll explore how AI affects healthcare, the pros and cons, and current applications. We’ll also take a look at what the future may hold for artificial intelligence in healthcare.

How does AI affect medicine and healthcare? 

The impact of AI in medicine and healthcare has been enormous and continues to grow exponentially. Put simply, AI describes computers and similar machines that replicate human cognition and are therefore able to learn, think (in a sense), and make decisions on our behalf. 

When you apply this to healthcare, some of the outcomes include:

• Machine learning is used to analyse medical data and reveal insights. These insights are then used to improve patient experiences and health outcomes. 
• AI supports medical professionals, both in conducting research and in clinical settings. For example, AI may help medical professionals make key decisions about medications and treatments by accessing research relevant to the procedure and the patient’s needs. 
• Medical imaging, where scans and X-rays are analysed in order to eliminate the risk of human error. 
• AI makes healthcare more predictive and proactive by analysing data to improve preventive care recommendations. 

For more information about current applications, you can read the applications section later in this article.

AI and healthcare: How things look currently

In many cases, the role of AI in healthcare is still at a fairly embryonic stage. Therefore, research and results from its use are still being gathered and analysed in order to make improvements and revolutionise the way healthcare is distributed in the UK and around the world.

However, at this stage, it’s clear to see the huge amount of opportunity that’s available to the profession by embracing AI. Researchers, clinicians, and patients are already reaping the benefits of its introduction, which will inevitably lead to a rapid roll-out of new technologies in the near future.

If the current growing trend of AI use in healthcare continues, it’s clear that it will become a core part of future digital health systems, helping to revolutionise medicine and healthcare to the benefit of anyone that interacts with it.

This matters because good healthcare is at the heart of a thriving society, so having the ability to analyse data in a more efficient and productive way is hugely important. 

It could easily be the difference between life and death, enhancing patient care and improving the overall quality of life for the human race. 

As seen recently with the COVID-19 pandemic, it could also be instrumental in helping to prevent and combat pandemics. 

>> Discover our collection of online healthcare degrees

Pros and cons of AI in healthcare

In order to better understand the role of AI in healthcare, it’s good practice to familiarise yourself with the pros and cons of using it in the profession. 

Advantages of AI in healthcare

1. Ability to analyse data and improve diagnosis

When it comes to medical records and other healthcare-related data, AI technology is able to analyse it much faster than humans are able to, and often more accurately. This can help medical professionals reach a diagnosis a lot more quickly and allow them to perform their duties more effectively.

2. Better patient care

If implemented correctly, AI in healthcare should improve the patient care that’s offered. 

It achieves this by cutting down on research time, facilitating the better use of resources, and reducing errors.

Integrating medical AI into clinician workflows can also give healthcare professionals valuable context while they’re making important decisions about treatments. 

3. Reduced cost of care

There are plenty of ways AI can reduce costs, both financially and time-wise. Machine learning in healthcare can ease the burden of time-consuming administrative tasks, reduce medical errors, and complete tasks a lot more quickly than a human may be able to. 

4. Real-time, accurate data

When it comes to medical issues, it’s incredibly important to offer a diagnosis as quickly as possible. To do this, it’s vital that medical professionals receive accurate data that allows them to make critical decisions more effectively. 

Real-time data reduces costs, minimises waiting times, and offers a greater chance of being able to prevent a condition from worsening. 

5. Improved workload and reduced staff stress

It’s no secret that jobs in healthcare can be incredibly stressful, and quite often departments find themselves short-staffed. Artificial intelligence in healthcare could help to address this issue, taking on some of the workloads to help ease the burden. 

Busy schedules and personal stress can also impact the standard of care provided, which is another reason why staff mental health is so important.

6. Support with administrative tasks 

Saving time on administrative tasks means medical professionals can place more focus on patient care and other important areas of their job. Tasks AI can help with include maintaining records, scan analysis and data entry.

7. Health monitoring and digital consultations

Whether it’s wearable technologies that help monitor a patient’s health or digital consultations that can be done on a smart device, AI is a great way of improving the way medical professionals record and analyse data. It also allows patients to monitor their own health and receive expert assistance online.

Disadvantages of AI in healthcare

1. Training complications

Not only do medical professionals need to receive extensive training to use a lot of AI technologies, but the AI tools themselves also need to be trained with curated data in order to perform properly. In both cases, this can lead to complications that wouldn’t exist without the introduction of AI.

2. Risk of creating unemployment

The robots are coming! In the past, it was often joked that robots would take over the world and steal our jobs, but AI and automation do actually pose a very real threat to a lot of sectors. Healthcare is no different, where the introduction of AI could mean that a lot of administrative roles are made redundant. 

3. Too much change can be difficult to manage

No matter the industry, too much change can be incredibly disruptive. That’s why it’s important to strike a balance and ensure departments are ready for AI before it’s rolled out. 

This is particularly important in healthcare, where key decisions can quite literally be the difference between life and death. The healthcare sector needs to be sure that AI can be used effectively and that all staff understand how medical technology works.

4. Still requires human input

AI has come on leaps and bounds in healthcare, but human input and surveillance are still relied upon. Humans are unique in the sense that they can notice behavioural observations and empathise with patients in a way that no machine can. 

Sometimes, these observations can be pivotal in a medical diagnosis and prevent further complications.

5. Increased security risk

AI systems can be vulnerable to security risks, which poses a massive problem to the healthcare industry, as patient data needs to be kept confidential. 

Cyber attacks are becoming more sophisticated and accurate, while also proving harder to predict and prevent. This means that healthcare institutions will need to invest an awful lot of money to ensure they keep cybercriminals at bay.

6. Social variables may not be considered 

When treating patients, it’s often not just about physical conditions. In fact, social, historical, and economic factors can also influence the specific care an individual needs. 

While AI is more than capable of allocating treatment based on the diagnosis, it isn’t yet capable of considering other social variables that may influence a medical professional’s decision.  

7. Inaccuracies could occur

Using AI in medicine would eradicate a lot of human-based errors, but it wouldn’t be able to get rid of inaccuracies completely. 

Whenever there is a huge amount of data involved, mistakes are still likely to occur, and data gaps can also be an issue. This could have potentially serious consequences in areas like medicine prescription.

Applications of AI in healthcare

There are plenty of instances where artificial intelligence is already being used in healthcare successfully, as well as countless opportunities for its involvement in the future. Here, we will take a look at some of the ways in which AI could have a positive impact on the profession.

Illness detection and diagnosis

Machine learning in healthcare could be used to detect more complex conditions that aren’t immediately apparent when someone receives a diagnosis. It could also be used to monitor patients to see when conditions worsen. The AI technology would then be able to collect vital data and alert medical professionals.

Medical imaging

AI is already being used in medical imaging, following research that suggested AI could be as effective at detecting diseases, such as cancer, as human radiologists. 

Not only is this vital for early prevention but also means that medical images can be examined a lot more quickly and thoroughly with the help of AI – eliminating the risk of human error.

Drug creation and development

AI in medicine can be used to create new drugs by analysing data and already existing medicines. Discovering and developing medicine is incredibly costly and time-consuming. With the help of AI, costs could be reduced and promising new drugs could be found much faster. 

Managing medical records

As we have already discussed, AI could be an instrumental tool in collecting and analysing data, such as medical records. Not only does this help medical professionals to work a lot more effectively, but it also means they can work faster and prioritise other important aspects of their job. 

Improving access to care

Medical professionals are always in demand and quite often there are staff shortages. In developing countries, this becomes even more of an issue. By using AI, life-saving care can be more readily available to people all over the world and be used to fill skills gaps and help with diagnosing patients.

Monitoring health using wearables and personal devices

Wearables are already being used in healthcare to monitor patients and smart devices to conduct digital consultations. 

The use of these technologies is only likely to increase, allowing medical professionals to intervene at the first sign of problems and ensure patients receive treatment and care as soon as possible.

What is the future of healthcare?

Despite there being both positives and negatives associated with artificial intelligence in healthcare, it’s clear that in the main it’s seen as a force for good and will continue to be developed and used more widely moving forward. 

In fact, it already plays a pivotal role in understanding the needs of patients through in-depth data analysis. Medical professionals are likely to rely on it even more for guidance and support, using it effectively to provide accurate and timely treatment to patients. 

Ultimately, the role of AI in medicine is to eliminate human error, make the lives of hard-working medical professionals easier, and improve the way care is delivered.

Whether you work in the medical profession or find yourself requiring treatment in the future, it’s likely that seeing AI technology used within a healthcare environment will become very normal.

AI in healthcare: additional courses

Hopefully, thanks to our guide, you now feel better informed about the role of AI in healthcare, now and in the future. While it may seem like a very complex topic on the surface, it’s undoubtedly something we should all familiarise ourselves with, as it’s likely to impact the way we receive care in the very near future (if it hasn’t already).

If you’d like to further your understanding and explore some of the key themes we have discussed in more detail, then why not take a look at some of the courses we offer here at FutureLearn? 

Whether it’s about the role of data and machine learning in healthcare or the development of MedTech, we’ve got you covered.

• MedTech: AI and Medical Robots by the University of Leeds
• AI and Big Data in Global Health Improvement by Taipei Medical University
• Artificial Intelligence for Healthcare: Opportunities and Challenges by Taipei Medical University
• AI for Healthcare: Equipping the Workforce for Digital Transformation by the University of Manchester
• eHealth: Combining Psychology, Technology, and Health by the University of Twente
• MedTech: Digital Health and Wearable Technology by the University of Leeds
• Digital Health for Cancer Management: Smart Health Technologies in Complex Diseases by Taipei Medical University
• How Artificial Intelligence Can Support Healthcare by the University of Groningen.