AI in healthcare, five years after lockdown – a different system, and a better one | usagoldmines.com

It’s hard to believe it’s been five years since the COVID-19 pandemic first hit. While life has gradually moved forward, its impact is still being felt in countless ways. COVID accelerated the development of many kinds of technology including artificial intelligence (AI). Once seen as novel and full of promise, AI has seen a meteoric shift – from something promising and experimental into something that is a critical driver of innovation.

One sector that has reaped the benefits of this accelerated development is healthcare, where it is being used to support clinical decision-making, monitor patient outcomes, and accelerate drug discovery.

So, what would a pandemic response look like today, in a world where AI tools play such a central role?

Enhanced detection and forecasting

There are straightforward ways that more advanced AI models could support the healthcare system. Data analysis, for instance, could help track the spread of a virus in real time and pinpoint the most effective treatments more quickly than ever before.

But the real potential of AI goes far beyond the basics. Today, we’re able to use its capabilities in far more impactful ways, particularly when it comes to tackling the challenges we faced five years ago.

Take detection, for example. AI has the incredible ability to analyze large sets of data from multiple sources in the blink of an eye. Through this analysis, it can then predict any unusual patterns that might occur, allowing governments the opportunity to be one step ahead. Not only that, with machine learning, AI can be trained on the historical data from previous outbreaks and forecast any red flags that may be on the horizon. Governments could then use this intelligence to plan their response and take steps to slow the spread.

A secondary and major benefit of a powerful forecasting system is that it can markedly improve efficiency – in many areas. There has been a swell of conversation around the financial viability of our NHS as the world becomes more expensive and life expectancy rises. The government has already acted, with plans to scrap NHS England after a £6.6 billion budget deficit was predicted for the coming year. Step forward AI. By accurately forecasting and predicting future health trends, governments can allocate resources in a much more efficient manner, reducing government waste.

Further, today’s AI models could play a vital role in the more technical healthcare challenges a major health crisis presents. Looking back, one of the most challenging features of COVID-19 was the development and rollout of the vaccine. The overall cost of the vaccine was estimated to cost the government £376 billion.

Development and discovery

Today, however, AI is doing powerful work in vaccine development and discovery. In America, AI is being harnessed to help create vaccines tailored to vulnerable groups. Additionally, through data analysis, it could predict which individuals are in the most immediate need of the vaccine and predict how candidates may react to it. Going even further, AI has the capacity to test millions of vaccine variations before a human trial has even begun, therefore optimizing clinical trial design.

A more efficient system for vaccine discovery, development, and distribution would allow the government to not only respond more quickly, but also better allocate resources to other areas of the healthcare system that are under great strain.

It can improve outcomes, but it can also help shape how information around those outcomes is shared. Which brings us on to another area where AI could make a meaningful difference: misinformation.

When the virus struck, little information was available about it and how it would affect the public, and the information that was relayed was possibly less robust than it needed to be. The government at the time had to set up specialist units to combat false narratives – costing valuable resources. With AI’s ability to decipher information in real time, any information or data getting passed around can be easily fact-checked, mitigating the spread of false and dangerous guidance.

AI has transformed how we would handle a global pandemic, but it’s also important to understand how the COVID-19 virus accelerated this progress. While the role of AI in healthcare was already being established at the time of the pandemic, COVID compressed the timeline – accomplishing in five years what might have taken a decade.

From experimentation to implementation

In truth, when the pandemic hit, AI in healthcare was largely experimental and often used solely for research and diagnostics, with little real-world deployment. COVID acted as a catalyst for investment in AI – and technology in general. Prior to the pandemic, investment in tech was dwindling, but fast-forward to 2021, and there was a marked difference in the attitude towards technology.

As we moved into lockdowns and a period with strict social restrictions, the focus turned to developing and implementing AI and tech that could improve mental health and wellness, with the use of mental health and well-being apps increasing 200% during the pandemic.

COVID also exposed gaps in the healthcare system; overburdened staff, slower diagnostics, and delayed responses. However, one of the most significant gaps was the bias in the data collected. The pandemic highlighted the lack of trust in healthcare in certain populations. The black community in the UK were much less likely to get the vaccine compared with other ethnic groups, for example.

Building trust in healthcare among minority communities is, therefore, vital to ensuring healthcare systems can support everyone. If provided with the right data, AI can significantly build trust and challenge misinformation that spreads so easily in today’s tech-centric society.

AI and the future of crisis response

Looking ahead, AI has the power to transform the management of global health crises. Governments are investing in AI infrastructure, building large language models (LLMs), and considering creating data-sharing platforms to support this innovation.

This is where we need collaboration. The NHS has the most extensive set of healthcare data but doesn’t share it. If that data is made available, we can train our AI platforms to analyze areas where improvements can be made. There also needs to be a commitment to train staff and make them aware of the benefits that AI can provide in terms of their productivity and workflow.

In conclusion, the pandemic and the following five years have highlighted how AI and healthcare institutions can be better prepared for any potential health crisis in the future. With a commitment to collaboration, the power of artificial intelligence can foster transparency, gather equitable data, and build trust among the population. By working hand in hand, we can build a healthcare ecosystem that is proactive and resilient.

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