AI tools have seen an explosion in interest since the generative or ‘GenAI’ chatbot ChatGPT made headlines when it launched in 2022. Understanding and taking advantage of emerging technologies without getting caught up in the hype cycle can be challenging — anyone remember NFTs? At PwC, part of our role is helping businesses cut through the noise to identify genuine opportunities and value.
The hype is justified this time, AI will change the way we work and live. It presents real opportunities and challenges for individuals and businesses alike. PwC has so much confidence in the transformative power of Generative AI that we’ve partnered with Microsoft to establish the GenAI Business Centre at our Spencer Dock offices in Dublin. Enabled by Microsoft Technology, the Centre leverages PwC’s extensive experience and expertise in AI, as well as our human-led, tech-powered approach, to deliver value for our clients and society.
In the case of community pharmacy, AI presents opportunities to improve the working lives of pharmacists and the experience and outcomes for patients. This comes at a time when the healthcare providers are pushing more treatment options from acute to community settings to enable better outcomes for patients. This shift will involve more integrated care across different kinds of health providers, and community pharmacy will likely play an increasingly important role in improving patient health across the country.
Contributors to the IPU Review have provided an overview of the general use cases for GenAI. So, let’s explore some of the more speculative, targeted use cases for AI in community pharmacy. These examples come from our PwC HealthTech team whose members include clinicians, public health professionals, technologists, and delivery specialists who provide expert advice and deliver technology enabled change to clients in the Irish health sector.
The World Health Organisation recognises antimicrobial resistance (AMR) as one of the top public health threats, one that was directly responsible for 1.27 million deaths in 2019. The negative consequences of AMR can’t be measured in deaths alone, many more people are left with long-term disability, and the World Bank estimates that AMR could result in $1 trillion in additional healthcare costs globally by 2030. GenAI deployed smartly in community pharmacy might be able to play some part in solving this problem.
By monitoring prescribing activity, AI could spot instances where a patient is prescribed multiple courses of different antibiotics, signalling that an initial course of antibiotics has been ineffective, and that the prescribing physician is looking at other options. If this happens multiple times in a community, it might suggest that an antibiotic resistant strain of a pathogen is in circulation. AI can monitor and detect these kinds of trends in real time and share that analysis with public health officials to support more rapid public health decision making and action.
Tools like Titan PMR are already leveraging AI to automate clinical checks at the point of dispensation. In a study, the company’s Titan.X Machine Learning (ML) technology was able to automate clinical checks of 45 per cent of prescription items. When pharmacists reviewed the decisions made by the automation, they chose to override just 0.12 per cent of them and none of those overrides were categorised as clinically significant. In a pharmacy setting, this kind of capability can assist with tools like pre-emptive search and match on medical history, allergies and adverse reactions, and act as a true digital assistant to pharmacists to improve quality of care.
Patients are demanding better access to their own health data, and better tools to enable them to manage their own health and healthcare. Health providers are responding with patient facing mobile applications to enable people manage their digital health identity, personal health information, and access to health services. GenAI powered healthcare chatbots will play a significant role in empowering patients by enabling self-care and improving access to high quality healthcare information.
A challenge to date with GenAI and chatbots in healthcare has been the lack of control on sources of information. By building GenAI chatbots on top of proprietary libraries, organisations can mitigate the risk. For better or worse, patients already use search engines to self-diagnose and self-medicate; an approved healthcare chatbot with built in safeguards, trained on high quality, verified data is a safer alternative. The anonymity offered by GenAI chatbots has advantages; patients may ask AI questions they perceive to be embarrassing or sensitive, like how prescription medications interact with over-the-counter medication, supplements, or other substances. This offers GenAI chatbots the opportunity to encourage better conversations with pharmacists and healthcare providers, or at least offer better information than they’re likely to get from an internet search.
Eagle eyed observers might have noticed these potential uses have something in common; a dependency on quality data sources, some of which don’t exist yet. High quality medicines data like summaries of product characteristics (SPC) and patient information leaflets (PIL) documents are widely available, but electronic health records and central databases of prescribing activity are not, but they are on the horizon. The trend internationally is towards more integrated care, enabled by the proliferation of shared electronic health records, medicines catalogues, ePrescribing and eDispensing systems. The availability of high-quality data combined with the proliferation of AI tools should help inform faster, better decision-making in the healthcare system of the future.
It’s worth remembering that the health service, regulatory environment, and pharmaceutical industry around the pharmacy will be evolving with it. In the regulatory space, PwC is already building advanced AI tools for the auto classification of adverse reaction reports. In the pharmaceutical industry, we have trained AI Models to accelerate the process of writing clinical trial protocols.
In Europe, the European Medicines Agency (EMA) has published a reflection piece on the use cases and considerations for AI across the medicinal product lifecycle, both in Industry and in regulatory activity. More recently, it published a five-year workplan for AI which includes the roll out of GenAI powered chatbots, a policy on the use of AI tools in the regulatory network, and guidance on the use of large language models (LLMs). AI will play an increasingly important role at every stage of the medicinal product lifecycle and will have an increasing impact on the way medicines are designed, produced, tested, regulated, prescribed, and dispensed.
This comes as the European Union prepares to bring its EU AI Act into effect in quarter one, 2024. Following in the footsteps of GDPR, it is a piece of European legislation that is likely to set the global standard. The AI Act defines risk categories for AI, ranging from low to unacceptable, and establishes rules for each. Transparency will be key, with an onus on companies to inform customers when they are interacting with AI or AI generated content. The Act has implications for the regulation of AI powered medical devices, which will be categorised as high-risk and subject to additional levels of scrutiny.
AI has the potential to significantly improve the working lives of pharmacists and outcomes for patients, but it comes with challenges and responsibilities, like ensuring ethical, transparent, traceable, and trustworthy use of the technology, an imperative to keep humans in the loop, protect data privacy, intellectual property rights, ensure quality standards, and ultimately, protect patient health.
That’s why we are committed to applying AI in a responsible and sustainable way, and to helping our clients and stakeholders to do the same. We are also continuously investing in our people, skills, and capabilities, to ensure that we are ready for the future of AI.
If you’d like to share some of your own experiences with AI, or thoughts on opportunities and challenges it creates in your life, feel free to reach out to me at Mark.x.kelly@pwc.com or on LinkedIn to discuss more about our HealthTech and GenAI service offerings.
Mark Kelly is a Senior Manager in PwC’s HealthTech practice specialising in delivering technology enabled, business driven change projects to organisations in the health sector.
Mark Kelly
Senior Manager, PwC’s HealthTech practice
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