AI and competitiveness angle from a patient view point (Guest blog)
23.03.22
Optimization and system efficiency, enhanced diagnostics, drug discovery pipeline acceleration, deep learning algorithms, interoperability and digital transformation, integrated care, interoperability and bias, artificial neural networks, natural language processing and machine learning, these are just some of the “buzz” words one associates with. But how do patients perceive these terms, how do they see the immediate benefit of AI enabled care and what does it actually mean for them? We must cut through the hype and develop mechanisms to promote understanding, engagement and acceptability.
Patients and citizens are becoming increasingly more aware of their rights when it comes to digital health, but there is a need for enhanced transparency which the adoption of the European Ethical Principles for Digital Health is set to achieve. We must ensure that ethics are integrated as early as possible with fair and unbiased data although figuring out the practical nitty gritty as to “how” we achieve this with regards to both implementation challenges and regulation is constantly evolving. The EU needs a comprehensive hybrid strategy that can achieve a balance between proportionate risk assessment and innovation that is patient centric. The UK has commenced this by making several changes to make it easier for innovators and SMEs to produce and meet evidence standards with the NICE MetaTool. In a recent exploratory study commissioned by the UK NHS England and the Accelerated Access Collaborative looking at public perceptions and attitudes to Artificial Intelligence (AI) in healthcare, the results were striking in demonstrating positive and negative views. Patients see AI as positive in “contexts in which there is faster diagnosis and subsequent treatment, improved care outcomes and improved experiences” with differences between usages in e.g. critical care such as heart attacks and life-limiting illnesses and ‘emotive’ conditions such as cancer and in the general ability to remove human bias that creates health inequality. However there were still concerns around “security and ethical considerations around the collection and sharing of data, health inequalities, algorithm bias, and risk of harm to clinician–patient relationships”, as well as healthcare professionals’ understanding of AI itself and how best to use it and communicate the value of it to patients. More work needed to happen around ensuring patients had “a clear understanding of exactly what AI means, or the breadth of technologies it covers”, with “explanations needed to be tailored to patients, explaining the risks and benefits and how the use of AI will impact them”.
Patients and citizens are becoming increasingly more aware of their rights when it comes to digital health, but there is a need for enhanced transparency which the adoption of the European Ethical Principles for Digital Health is set to achieve. We must ensure that ethics are integrated as early as possible with fair and unbiased data although figuring out the practical nitty gritty as to “how” we achieve this with regards to both implementation challenges and regulation is constantly evolving. The EU needs a comprehensive hybrid strategy that can achieve a balance between proportionate risk assessment and innovation that is patient centric. The UK has commenced this by making several changes to make it easier for innovators and SMEs to produce and meet evidence standards with the NICE MetaTool. In a recent exploratory study commissioned by the UK NHS England and the Accelerated Access Collaborative looking at public perceptions and attitudes to Artificial Intelligence (AI) in healthcare, the results were striking in demonstrating positive and negative views. Patients see AI as positive in “contexts in which there is faster diagnosis and subsequent treatment, improved care outcomes and improved experiences” with differences between usages in e.g. critical care such as heart attacks and life-limiting illnesses and ‘emotive’ conditions such as cancer and in the general ability to remove human bias that creates health inequality. However there were still concerns around “security and ethical considerations around the collection and sharing of data, health inequalities, algorithm bias, and risk of harm to clinician–patient relationships”, as well as healthcare professionals’ understanding of AI itself and how best to use it and communicate the value of it to patients. More work needed to happen around ensuring patients had “a clear understanding of exactly what AI means, or the breadth of technologies it covers”, with “explanations needed to be tailored to patients, explaining the risks and benefits and how the use of AI will impact them”.
The “magic” of AI comes with the myriad of applications it can do, from optimising the messiness of real-world data into workable models for analysis at scale, creating enhanced drug safety through better and faster target profile validation and diagnosis of genetic conditions and/or applications in translational and precision medicine with enhanced stratification that aligns CROs with PROs more. This has the potential to transform care at all levels towards a more sustainable and value based model, but we still have a little way to go towards engaging citizens in the development and application of such AI technologies. To do this right, the EU must work alongside patients, patient organisations and industry as equal stakeholders to ensure representativeness and accountability with further initiatives like #AIEUWeek. As a EUPATI trained patient expert with some technical product management and regulation familiarity, this is a complex and ever changing area, but for the public to be more involved in decisions about the deployment and regulation of these AI systems, perceptions do matter; people must be at the heart of everything that is done and it is through appropriate investments in education, training and co-creation of innovation working with industry that this can best be facilitated and expedited so that the EU can remain competitive. Afterall innovation can come in many guises, sometimes it’s just about utilising what you have to develop and generate additional value that can be implemented.
NHS England AAC report “Public perceptions and attitudes to AI in healthcare” is available on NHS Futures website
