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How artificial intelligence can reshape the healthcare experience

2023 was a big year for artificial intelligence (AI). The launch of Chat-GPT-4, Microsoft Copilot, Google Bard and Amazon Q has raised awareness of the potential of AI solutions across the board.

In the healthcare sector, the potential is huge. And 2024 is shaping up to be an equally exciting year. In this blog, we take a look at the different ways in which artificial intelligence will reshape the healthcare experience.


Using AI tools to streamline administrative effort

One of the areas in which AI tools are already delivering value is in streamlining administrative effort. The use of robotic process automation (RPA) to streamline routine tasks helps hospitals and other healthcare providers to operate more efficiently. This means that a larger proportion of funds can be directed into delivering frontline services.

Microsoft Copilot for Microsoft 365 is an exciting new development which has a lot of potential to streamline back-office and administrative services, especially in automating patient communications and searching for information from multiple documents and sources.


Improving facilities management with AI 

There is huge potential for AI-powered solutions working in conjunction with Internet of Things (IoT) devices, such as meters, sensors and monitoring solutions, to help minimise the overheads of running a hospital campus and all the associated HVAC services. As well as helping to reduce energy costs, it can help to optimise space utilisation and help healthcare providers achieve their net zero goals.

Additionally, predictive analytics can be applied to monitor services use, facilities use, patient footfall traffic, staff workflows, rotas and shifts, and other metrics. This way, healthcare providers can predict and optimise all aspects of facilities management.


Summarising patient records using AI

Many healthcare providers have invested in electronic patient records (EPR) to help integrate patient data. However, it can still be a challenge for physicians to navigate through the information held in these systems. AI offers the possibility to search multiple systems and information sources quickly, to present pertinent patient information quickly and in summarised fashion, thereby aiding physicians and enabling more appropriate responses.

Of course, there are some data privacy and governance concerns around this. Healthcare providers must be confident that any localised and personal patient information used by the AI solution is not used to train the underlying AI models so that data security is maintained.


Aiding diagnoses with AI

AI is already being used and tested in a variety of diagnosis scenarios. Models are being developed that are more effective in interpreting scan data than their human counterparts. For example, in the area of cancer diagnoses from recorded images. It is hoped that these breakthroughs will help to speed up diagnosis, make diagnosis more accurate and even help to identify disease earlier.


Robotic assistance during surgery

Another way in which the application of AI is being explored in a healthcare context, is in the use of robotics during surgical procedures. One advantage of using the computerised control of robotic surgical apparatus is that the surgeon does not have to be present on campus to perform the procedure. This opens the door to remote surgery and even AI-assisted or automated procedures.


Using AI in drug development 

Another important area in which the potential for AI to drive improvement is highly significant is in the development of new medicines. Given that it typically takes around 12 years to get a drug to market, using AI to speed up the process could have major impact.

Global pharmaceutical firms are already exploring how AI solutions can help to suggest new combinations and determine the effectiveness of potential drugs. AI can recognise hit and lead compounds, provide a quicker validation of the drug target and facilitate the optimisation of the drug structure design.

When it comes to speeding up testing, AI models could be used to predict how potential drugs might behave in the body so unworkable drugs are discarded before they make it to trial. AI-based techniques could assist in selecting potential patients for pre-clinical trials by identifying relevant human-disease biomarkers.


Remote monitoring of healthcare devices and wearables 

Using IoT connected devices, AI can be used to monitor the use of healthcare devices to ensure optimal operation and maintenance. The same metrics can be used to ensure the patient is using the device correctly and prompt them if there are issues.

Predictive AI models could be applied to optimise operation and patient health. This potential isn’t restricted to physician-issued connected devices, such as insulin pumps or oxygen masks. The wearables and fitness trackers in everyday use record a great deal of health-related information. Using AI models to spot trends in this data and make healthcare recommendations would be of huge benefit in the area of preventative medicine.


Personalised treatment plans 

The holy grail of healthcare AI is the creation of personalised treatment plans designed on the individual needs, history and genetic makeup of each individual patient. We may be some years away from the routine use of AI modelling to determine and design personalised treatment plans across every healthcare discipline – so that the patient is treated holistically and personally – but work is already underway to help us get to this end state.

It’s an exciting time for both technologists and healthcare professionals. As the two worlds continue to merge, the results will be exciting for clinicians and patients alike.

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