The COVID-19 pandemic has only made matters worse by forcing healthcare institutions to transform the way they deliver care. Healthcare IT and digital solutions have been at forefront of this fight as the industry navigates through these unprecedented circumstances. Within these solutions, artificial intelligence (AI) has shown immense promise for the future of the healthcare industry. Recent rapid advances and ongoing developments in the field are likely to propel it from being a technical novelty into a powerful and indispensable aid.

The evolution of AI

As a technology, AI has actually been in existence since the 1960s. As interest waxed and waned, investment in the sector went through a number of cycles. However, during each cycle, the technology failed to live up to expectations and attention was diverted elsewhere.

Fast forward to 2020, and AI is in a very different place. With our modern processing capabilities, the time is ripe for AI to bring positive changes across industries. AI’s progress is further aided by the dramatic rise in volumes of data across the world. AI tools work best when they can learn from massive amounts of data, and this has never been more possible than today.

In the healthcare sector, too, data volumes are rising at rates never seen before. Electronic monitors, scans, health sensors, and treatment equipment generate terabytes of data that can provide detailed insights into what care is required and how successful it has been for a patient.

AI is also benefitting from the accelerated adoption of cloud services. These have led to significant reductions in the cost of data storage and compute resources, which puts AI usage into the hands of organisations and groups that could not have afforded it previously.

Putting AI to work

There are numerous ways in which AI can be used in the medical sector and new opportunities for applications are being constantly identified. From disease diagnosis and treatment applications to patient engagement and administrative processes, AI-based solutions can streamline and augment multiple areas within healthcare environments.

Many countries around the world are plagued with poor doctor-to-patient ratios. AI solutions can bridge this gap by making healthcare more accessible for the masses. For example, AI tools are being applied in many areas of radiology, from MRIs and X-rays to CT scans. These solutions can expedite MRI scan processes with the help of smarter image processing and image reconstruction techniques and can even flag those scans that may require follow-up examination by a human operator.

These tools can also be used to analyse blood cultures and other samples for signs of disease and to check the effects of prescribed medications. In addition to physical health, AI can be used to identify if a patient is suffering from a mental health problem via facial expression analysis and changes in speech patterns.

AI solutions can also enhance the administrative functions within a medical facility. From optimising front office management, appointment bookings, and shift schedules to streamlining document processing workflows insurance claims, AI can aid multiple administrative operations in the healthcare sector.

As for its role in dealing with COVID-19, AI tools are helping doctors and radiologists in identifying ground glass opacity via lung CT scans and X-rays. AI solutions were also used for contact tracing and containing the spread of the virus. Once a vaccine has been developed, AI will also be able to assist in determining which groups should receive it first to bring the pandemic under control as quickly as possible. Various AI-based simulation models can thus be designed to chart out an effective vaccine deployment plan.

Deployment challenges

While it’s clear that AI can deliver significant benefits for the medical community, there remain some challenges that could hinder its widespread adoption.

One of the biggest concerns in AI implementation is maintaining patient privacy and keeping personal health information (PHI) secure at all times. There are also many regulations, such as the HIPAA, that healthcare institutions need to comply with in order to demonstrate the adequate protection of sensitive patient records. These requirements could potentially prevent important data from being analysed by AI tools and reduce their effectiveness.

Another challenge occurs because the results offered by the tools are not 100 percent accurate at all times. Results may still need human supervision to ensure conclusions are accurate. For this reason, it's important to remember that AI can aid but can never replace healthcare workers.

A third challenge stems from the fact that many medical systems and data stores are not interlinked, which reduces the interoperability of the data. This can make the collection of data for analysis difficult if not impossible, further reducing what can be achieved. These things can be overcome, however this is likely to take time and require a financial investment.

Despite these challenges, it’s clear that AI has much to offer in the medical sector. By analysing vast quantities of information available and providing insights that humans may miss, the technology can significantly improve the quality of patient care and outcomes.