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What is happening in AI in the healthcare sector? What’s next?

Healthcare is one of the most exciting sectors for AI innovation. Its potential is being explored throughout the whole healthcare lifecycle – from drug discovery and diagnostics to streamlining administrative processes and enhancing the patient experience.

 

While AI and generative AI solutions offer myriad opportunities for healthcare professionals and patients alike, there are a number of challenges facing the sector which must be resolved if AI is to reach its full potential.

Integrating multiple data sources

For AI-powered data analytics that can be applied to discovery, predictive analytics, scheduling optimisation or a whole host of other applications, healthcare organisations need to ensure a cohesive and secure data platform.

Like many other industries, healthcare organisations struggle with the issue of siloed data and disparate systems with little integration. Generative AI solutions offer some opportunity to interrogate disparate data sources but, even then, the architecting of a suitable, integrated underlying data platform is the first step.

Cybersecurity

Healthcare organisations are a key target for malicious cyber activity. Important national infrastructure and services offer huge potential for disruption and are, therefore, an attractive target for terrorist and state-sponsored actors. 

At the same time as an increasingly destabilised global situation, advances in AI are putting new tools in the hands of the cyber-attackers. AI powered solutions for detection and response offer healthcare providers some protections in this increasingly high-tech game of cat and mouse. But it means that in their adoption of AI and other IT solutions, cybersecurity must play an increasingly important role.

Ensuring the safety of patient data

Data privacy, information governance and the protection of highly personal patient data are key considerations for all healthcare providers. The integration of new AI solutions adds another layer of complexity to this already complex picture.

Most importantly, healthcare providers must be alert to the problems of “shadow AI” which may undermine the data privacy and information governance systems they have in place. Organisations must ensure all staff are aware of the potential of unauthorised AI solutions to leak sensitive and private patient data or information if used.

Disabling shadow AI solutions, setting alerts around AI and data use and investing in education and monitoring solutions will be key to ensure the safe use of AI moving forwards.

Ensuring ethical and responsible use

While some AI trials have shown AI’s efficacy in diagnostic services – meeting and even exceeding the performance of clinicians – the need to maintain patient and clinician confidence mean that, for now, AI will need to play a supporting role rather than a leading role in healthcare delivery. 

Ensuring a “human in the loop” checks AI-generated decisions and insights is a key plank in current ethical use frameworks. Transparency about models and applications as well as proactive reviews and assessments to ensure fair, unbiased and appropriate use are not only essential but must be demonstrable.

Navigating an increasingly complex regulatory landscape

The evolving regulatory landscape for AI solutions will need to be navigated carefully to ensure trust and transparency, as well as compliance. Transparency over the use of AI and its algorithms, as well as work to ensure its ethical and unbiased operation, will be critical for maintaining public trust.

As the EU and the UK seek to introduce tougher guidance on the use of AI solutions, the regulatory easing expected in the USA may cause increasing friction across borders. At the same time, healthcare organisations must comply with evolving data privacy and information governance requirements. This complex regulatory picture means that healthcare organisations need to develop additional, specific competencies in AI regulatory compliance.

Accessing the skills required

When grappling with this multi-faceted set of challenges, healthcare organisations need to invest in a wide range of AI expertise if they are going to realise the full potential of AI to transform healthcare.

We know there is a well-documented skills gap for IT and AI specialists, raising the difficulty and cost of accessing the necessary skills. For healthcare organisations who are well-versed in managing skills gaps, the route may well be to partner with expert organisations who can provide the skills and expertise required.

What next?

Healthcare organisations must begin the work to address these challenges as early as possible. Only in this way will they be able to lay the groundwork for successfully adopting the AI-powered solutions that promise to transform patient care and healthcare delivery now and to come.

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