Artificial intelligence (AI) simulates human intelligence by being programmed to think like us and mimic our actions, allowing them to engage in problem-solving and learn from their mistakes. Taking this definition directly into medicine, it is clear these skills that AI possesses are transferable to healthcare roles, such as virtual nurses, but also gives them the upperhand to humans in analysing lab results to assist in medical diagnosis. As AI technology evolves and scientists adapt the algorithms to develop AI for specific and niche roles, there is also the question of how far we can take these advancements into the NHS, and, ultimately, how realistic that would be (The Medic Portal, 2021).
How is AI already used in medicine?
One example of virtual nursing is by a company called ‘current health’, who have used AI in a wearable device that monitors a patient’s vitals (temperature, respiration and oxygen saturation, pulse, etc) in an accessible way for the patient’s doctor to read and assess. The benefit to the NHS has already been analysed, as the use of ‘current’ devices has seen an 87% reduction in emergency department visits, reducing a strain on healthcare services through prevention (Current Health, 2021).
Robotic surgery swept medicine when in the 2000s the da Vinci Surgery System was FDA approved for general laparoscopic surgery (Robotic Oncology, 2021), and since then the use of robotic surgery increased from 1.8% in 2012 to 15.1% in 2018 (Sheetz et al., 2020). This is due to advancements in robotic surgery that made systems more capable of replicating the sensation and tactile feel for a surgeon in less and more invasive procedures. For medicine, this has reduced surgical complications by five-fold, decreased the number of staff required, and saved time in surgery.
How can AI benefit the NHS in the future?
Household names like Amazon’s Alexa is already a technology that is supported by AI infrastructures and the general population is increasingly becoming familiar with how to use it. The Department of Health have announced a partnership between the NHS and Amazon’s own Alexa, to utilise this technological shift in society to the healthcare systems advantage: Alexa can now search on the NHS website automatically when people ask medical questions. In the UK specifically, there is an ageing population where, in 2019, approximately 22.9% of the population is 65 years or older, meaning the most clinically vulnerable group, where the rate of comorbidities and polypharmacy is the highest, are also the group that struggle with accessing the internet to find NHS medical advice the most (Office for National Statistics, 2020). By integrating the NHS website into Alexa’s database, health advice will be far more accessible, although there are concerns of how far this will go in relation to confidentiality, despite Amazon’s confirmation that all data will be kept confidential and encrypted.
With regards to virtual nursing, there is now the possibility of AI being on the other end of the NHS 111 service, this would increase the amount of people able to call and reach a 111 operator at one time and be triaged quickly and accurately to save lives. However, the public's hesitancy of having a ‘talking robot’ giving them medical advice may prevent this from becoming a reality of the NHS.
More immediately, after the pandemic has shown the NHS the usefulness of virtual medicine, there should be a pursuit to fully digitise its data, so all data is generated in machine-readable format. Furthermore, there should be a review conducted to evaluate how data from devices outside of the healthcare system, like Current Health wearable devices or even FitBits, could be integrated and used in the NHS (Reform, n.d.).
How likely will AI become the NHS’s future?
Even though there are large sums of money to consider behind AI, it is an investment that the government has acknowledged as important for the future of healthcare. These costs would be returned in the long run as AI has the potential to cut down emergency department visits, predict patterns in diseases to lead to earlier diagnoses, and reduce waiting times, so it seems AI has come at the perfect time to combat these problems.
Overall, there is a split in ideas for the future applications of AI whether they be more practical, concerning the NHS databases and IT systems, or more innovative and dystopian, like robot arms that conduct surgery in a separate room to the surgeon. However, it is universal in opinion that AI will become part of the NHS even more so than it is already, we just don’t know in which application it will be the most revolutionary.
Bibliography
Current Health. (2021, July 31). The mission control for healthcare delivery outside the hospital. Current Health. https://currenthealth.com/
The Medic Portal. (2021, July 31). AI in medicine. The Medic Portal. https://www.themedicportal.com/application-guide/medical-school-interview/nhs-hot-topics/ai-in-medicine/
Office for National Statistics. (2020, June 24). Population estimates for the UK, England and Wales, Scotland and Northern Ireland: mid-2019. Office for National Statistics. Retrieved July 31, 2021, from https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/bulletins/annualmidyearpopulationestimates/mid2019estimates
Reform. (n.d.). Thinking on its own: AI in the NHS. Reform. Retrieved July 31, 2021, from https://reform.uk/research/thinking-its-own-ai-nhs
Samadi, D. (2021, July 31). History and the future of robotic surgery. Robotic Oncology. https://www.roboticoncology.com/history-of-robotic-surgery/
Sheetz, K. H., Clafin, J., & Dimick, J. B. (2020, January 10). Trends in the Adoption of Robotic Surgery for Common Surgical Procedures. Jamane Network. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2758472
