An ageing population, lifestyle-related diseases and global prosperity are driving a demand for the latest healthcare technology, investment professionals suggest.
Specifically, Artificial Intelligence (AI) has the potential to play a transformative role in healthcare. The software is capable of integrating large data sets and combining clinical experiences across specialities. This advances groundbreaking research, saves doctor’s valuable time and ultimately helps patients get the help they need quicker.
To celebrate World Health Day, PA Future spoke to fund managers who invest in the sector to understand how AI can be used to benefit the healthcare system around the world.
How AI is advancing healthcare
Servaas Michielssens, head of healthcare and senior fund manager at Candriam, said the role of AI is changing in the healthcare landscape. The firm directly invests in the technology and service providers, such as hospitals, that deploy AI technology within their operations.
Commenting on the traditional use of AI, he suggested the software’s greatest potential lies beyond its current purpose. “Historically, AI is prominent in accelerating drug development and enhancing medical image processing. Recently, there have been evolutions in large language models, such as ChatGPT, an AI system capable of understanding and generating human language by processing vast amounts of text data and generative AI. Although this presents novel opportunities for innovation, the greatest potential for transformative impact lies beyond these traditional realms,” Michielssens said.
One of these potentials lies in healthcare administration. Figures reveal that approximately 25-30% of expenditure is allocated to administration in the US healthcare system. This exceeds the expenditure on drugs, which stands at around 10%.
He added: “According to McKinsey, leveraging AI could potentially save a quarter of these administrative costs, equating to the substantial sum of a quarter of a billion dollars in the US alone. This proves the value of investing in AI solutions that streamline administrative processes within healthcare systems.”
Further, Sarah Nottle, investment analyst in the Liontrust Sustainable Investment team, said it “invests through the thematic lens of enabling innovation in healthcare and providing affordable healthcare”.
Interestingly, she noted the team is “not looking to invest in AI for AI’s sake in the hope that it may be used for positive outcomes such as improved outcomes in healthcare”. Instead, they are interested in how specialist companies can use AI and machine learning to augment what their positive products and services can achieve.
Nottle insisted the pressure for medical professionals to work smarter and harder while not compromising quality is “not expected to dissipate anytime soon” and, as a result, investors should keep an eye out for the “limitless capabilities” AI will have on the healthcare system.
The opportunities of investing in AI to improve health
The key to advancing healthcare systems, particularly within hospitals, is “leveraging AI to streamline administrative processes, optimise patient care pathways and enhance the efficiency of healthcare delivery systems”, Michielssens said.
For example, hospitals may use AI algorithms to improve their intake processes and reduce the administrative burden so workers can spend more time with their patients. By investing in these solutions, stakeholders can contribute to improving both the quality and accessibility of healthcare services on a broader scale.
Lionstrust’s Nottle adopts a similar approach. “The team views AI as a tool; as a means to the ends of diagnosing sooner, treating better and working more efficiently. While AI has been utilised in healthcare for some time, we are in the early innings of large machine learning models using huge compute power to analyse enormous data sets.
“One consideration of AI models is ‘garbage in, garbage out’ – that is, if your algorithm is trained on poor quality data, your output will reflect this. Health data has been difficult to analyse at scale – with large data sets, unique data points and discordant technology, it has been challenging to aggregate in a meaningful way. This is where the new generation of AI models comes in,” Nottle said.
The challenges of investing in AI to improve health
Investing in AI to improve healthcare presents unique challenges due to the highly regulated nature of the industry, especially when these decisions directly impact patient health outcomes.
This is because, as Michielssens continued: “AI tools in healthcare must adhere to rigorous standards. For instance, while large language models have shown remarkable capabilities, any potential inaccuracies in medical contexts are unacceptable. Significant advancements in AI reliability and robustness are necessary before widespread integration into healthcare decision-making processes. Regulatory frameworks governing AI in healthcare must evolve to assess and ensure the safety and efficacy of these technologies.
“Furthermore, while AI has made significant strides in expediting drug discovery processes, a major challenge persists in the lack of disease models that accurately correlate with human physiology and pathophysiology. This hinders the translation of AI-driven insights into clinically viable solutions.”
Addressing these hurdles requires joint efforts from stakeholders across the healthcare ecosystem to ensure the safe, effective and equitable integration of AI technologies into healthcare delivery.
Patient trust is also a significant hurdle, Nottle mentioned. “Patient trust is integral in the healthcare system, and data protection must protect sensitive patient information. Given learning models are only as accurate as the data they are trained on, problems have arisen on poor diversity metrics of training data. This could intensify social inequality and widen existing gaps in patient care, a problem that can lead to biased or subpar recommendations for underserved populations.”
Further, Jasveet Brar, fund manager of M&G Better Health Solutions fund, suggested the differing pace at which the healthcare system and technology operates will be a significant challenge. “We must accept that healthcare systems tend to move at a gradual pace when it comes to adopting new technologies. Understandably so, given the precious and fragile nature of health. This does mean such advancements can be over-estimated in the short-run. Hopefully we under-estimate the advantages it brings in the long-run.”
Examples of AI use in healthcare
Real-life applications of AI technologies in healthcare are plentiful. Examples include enhancing electronic health records, accelerating drug discovery and vaccine research, and even using robots to help surgeons during surgical decision making.
Nottle provided examples of the ways in which the Liontrust Sustainable team is investing in AI. The team invests in IQVIA, a $45bn (£36bn) US-based company which runs clinical trials on behalf of its pharmaceutical customers, while collecting medical data points. The company has one of the largest collections of healthcare information – including 1.2 billion unidentifiable patient records, 56 petabytes of data and covering 85% of the world’s pharmaceuticals.
With the help of AI, the model can form insights using IQVIA’s high-quality data, which would have previously been impossible due to lack of computing power. In many cases, IQVIA’s AI capabilities can contribute to real world outcomes.
For example, the company partnered with the NHS to identify the risk of stroke in patients with atrial fibrillation (AFib). Research revealed that patients with AFib are five times more likely to have a stroke and IQVIA used AI within its electronic medical record (EMR) data to identify clinical risk factors and predict stroke risk.
“This enabled a focused and selective engagement on prevention in these higher risk patients, leading to a 22% reduction in stroke during the implementation phase, estimated to save the NHS $2m (£1.6m) annually,” Nottle concluded.
Alongside this, AI-driven augmented reality is another sector that is gaining traction. Another of Liontrust’s holdings is Intuitive Surgical. The company is a pioneer in robotic surgery – launching its first Da Vinci robot over 20 years ago – and is working on a new robotic generation – Da Vinci 5.
“AI invites vast opportunities in robotic surgery and the potential for machine learning data analysis to provide real-time insights to the surgeon to assist in surgical decision making. This could improve patient outcomes and surgical efficiency,” Nottle said.
Further, Michielssens provided insightful ways that AI can speed up admin-based tasks within healthcare. The first is the enhancement of electronic health records (EHR). “Picture an AI tool that transcribes and completes medical records during physician-patient interactions, while also managing prescriptions and scheduling follow-up appointments. These innovations have the potential to save workers approximately seven minutes per consultation in documentation time alone,” he said.
Second, AI can alleviate the burden of prior authorisations for doctors. “In the US, it is predicted that doctors spend on average 13 hours a week getting medication approved for reimbursement with health insurance, with an estimated annual cost of $25bn (£19.8bn). AI could greatly save time that could be directed to patient care.
“For example, AI algorithms can be used to improve the intake of cancer patients. This results in shorter waiting times to receive their treatment. This technology can also increase the length of time that physicians spend with their patients as well as improve patient retention, a significant win for all parties involved,” he concluded.
Further, Brar said drug discovery is a large part of M&G’s investment strategy. The fund invests in Thermo Fisher Scientific, a company that uses AI to develop research and development tools within the healthcare sector. For example, its atomic resolution images use AI to enable researchers to better understand druggable targets and potentially accelerate drug discovery.
In addition, AI can be used to support healthcare professionals make decisions. The World Health Organisation (WHO) estimates there will be a global shortage of 10 million healthcare workers by 2030.
“Masimo, a leading medical technology company, launched a remote patient monitoring system. Capturing over 60 parameters, the system uses machine learning to establish a personalised baseline for a patient to more accurately escalate patient distress with fewer false alarms, enabling greater healthcare worker productivity,” Brar concluded.
Evidently, the healthcare industry is already being transformed with the help of AI, and as echoed by these fund managers, is an investment opportunity not to miss given the ever-present and growing demand of healthcare.
