How AI could alleviate systemic healthcare issues

I can’t think of a digital technology innovation that excites clinicians as much as artificial intelligence (AI). We are only just at the beginning of the process of discovering how the latest generative AI technology can benefit healthcare professionals. Yet there’s enormous confidence that AI can and will change how we approach patient care and clinical documentation for the better.

This wave of optimism for the potential of new digital technology starkly contrasts with the high burnout and frustration healthcare professionals face. This global phenomenon worsened after the COVID-19 pandemic, with high rates of professionals leaving their roles. In the US, despite high pay rates, over 50% of physicians would not recommend their occupation to their children.

It is an alarming trend that points to deeper systemic issues that must be addressed to ensure the sustainability of healthcare delivery. AI may offer a solution to alleviate some of these pressures. By automating routine tasks and providing advanced decision support, AI can reduce the cognitive load on clinicians, allowing them to focus on patient care and complex medical decisions. Given that medical resources are limited, an enhancement in job satisfaction and patient outcomes due to the effective use of AI will create a win-win scenario for healthcare providers and patients.

Generative AI set to revolutionise the care experience

Generative AI is a transformative form of AI that is set to revolutionise the healthcare experience for patients and clinicians. This is because GenAI can help derive value from unstructured documentation that describes the patient’s conditions, treatment, relevant clinical protocols and more. The possibilities include virtual health assistants providing round-the-clock support to AI-powered apps offering tailored health recommendations.

For clinicians, AI can enhance the usability of electronic medical record (EMR) systems, making them more intuitive and less cumbersome. Pilot studies demonstrate AI’s potential to streamline documentation processes and provide intelligent prompts when providing care. This will give clinicians more time to engage meaningfully with their patients.

Healthcare data is a gold mine waiting to be tapped

The wealth of data generated within the healthcare system is a gold mine waiting to be tapped. And AI is the virtual ‘tap’, as it can analyse large datasets to help track and manage chronic diseases like diabetes and HIV or spot the onset of epidemics and pandemics. In some countries, number-crunching AI-powered dashboards provide real-time patient population updates, enabling proactive interventions and better resource allocation.

One of AI’s most promising emerging applications in health care is clinical decision-augmented support. AI has proven its ability to interpret complex medical images and lab results to help clinicians make more informed, faster decisions. AI algorithms are now being tested to help detect early signs of sepsis, facilitating timely interventions that will save lives. Predictive analytics will enhance centralised monitoring, improving alert visibility and prompt resolution for community care.

More patient-centred, effective care at a lower cost

AI can empower patients by providing them with personalised health information and provide insight into their condition by reducing technical or medical language from clinical documentation. Using historical and relevant data, chatbots and AI-driven apps can offer timely advice and support, enhance patient engagement and help people take a more active role in managing their health. Furthermore, generative AI can safely be used by clinicians to help with the time-consuming task of ‘translating’ medical records into patient-facing language and be delivered in a written format to the patient or relatives. This more patient-centred approach can lead to better health outcomes, and I imagine a world where clinical records are routinely converted into patient messaging by AI, approved by the clinician and provided to the patient and family to fully engage them in their care.

Another area of concern to healthcare organisations is operational efficiency, where, for example, AI might help streamline scheduling and reporting. Patient flow analysis — the tracking of a patient’s physical or logical position in the care process — might also identify inefficiencies and suggest workflow improvements that help optimise operations for more effective care and better patient experiences at a lower cost.

There is also a bigger picture: AI is a powerful catalyst for research and innovation in health care. By analysing high volumes of medical data, AI can uncover new insights and trends that drive the development of new treatments and therapies. AI can also model and simulate clinical trials to accelerate research, bring new solutions to market faster, and help continuously improve the science of medicine.

Why interoperability and data management are critical

As healthcare organisations explore the AI frontier, they must establish governance systems for data collection and leverage AI to achieve meaningful, sustainable care improvements. One example of this is using generative AI to identify structured data from unstructured clinical notes to enhance the quality of clinical records.

Data-driven care improvements also rely on the seamless flow of information between various stakeholders. However, this requires regulatory frameworks that encourage systems interoperability and data standards. It is also why national networks and local health information exchanges (HIEs) are pivotal in facilitating interoperability to ensure the correct data is accessible and actionable when and where needed.

AI thrives on data. The ability to integrate and analyse data from disparate sources is fundamental to its success. High-quality, trustworthy data should enable AI to provide valuable insights to drive better clinical and operational decisions. Proper infrastructure and data management are crucial for developing and maintaining AI applications with appropriate oversight.

This presents challenges and opportunities for the cost-constrained healthcare industry, which must invest in technology to leverage AI successfully. Given the optimism surrounding AI and its potential to address systemic healthcare challenges, these are investments we need to make, and make wisely.

Dr Nick Tayler is the global lead of the safe use of clinical AI and a Clinical Safety Specialist at InterSystems, a creative data technology provider which delivers a unified foundation for next-generation applications for health care, finance, manufacturing and supply chain customers in more than 80 countries. Based in Melbourne, Australia, Dr Tayler provides clinical expertise to assist systems architects in the development of integrated, user-focused implementations of the InterSystems TrakCare unified electronic medical record (EMR) system across the Asia Pacific region.

Image credit: iStock.com/Akarapong Chairean