The rapid sophistication of artificial intelligence-powered services in recent years has helped to increase AI technology adoption by more than 51% compared to previous estimates, and these advancements are helping revolutionise provider and patient relations in healthcare services across the world.
With a current market value of $15.4 billion USD in 2022 and a predicted revenue forecast of $208.2 billion USD by 2030, the potential of artificial intelligence and machine learning technologies spans all aspects of healthcare from out-of-clinic services to in-patient care; as well as data security, fraud detection, and error reduction across common procedures.
A 2019 survey of over 900 healthcare professionals from the United States and United Kingdom (conducted by MIT Technology Review Insights, in association with GE Healthcare), found that the introduction of AI not only automated repetitive, time-consuming processes but allowed healthcare professionals to spend one-third less time doing administrative tasks and two-thirds less time writing up reports – giving patients more, valuable contact time and reducing waiting lists. Furthermore, AI technology was found to be able to provide a better analysis of gathered data which led to enhanced diagnoses and more suitable treatment plans with improved success rates and recovery time.
However, the possibilities of AI don’t stop at carrying out assistive duties. Advancements in data mining, speech recognition, image scanning and machine learning now make it possible for both healthcare staff and patients to benefit from accelerated treatment processes that use new and historical medical data to form a diagnosis.
In 2018, a team of MIT researchers created an algorithm capable of analysing brain scans and other 3D imagery 1,000 times faster than before – making it possible to study the changes in a patient’s condition in under one second; and 2021 a team at the University of Cambridge and The Alan Turing Institute collaborated on the creation of a machine learning tool that was able to identify early stages of dementia. These key examples show us a glimpse into the future potential of AI in today’s healthcare system and create further opportunities for innovation as we build on existing research and combine the expertise of top professors and experts from across the world. By adopting these technologies, patients will further benefit from up-to-date information about their condition, and reduce pressure on doctors to memorise conditions and their symptoms – enabling them to focus on treatment plans and reducing the chance of misdiagnosis.
Throughout the COVID-19 pandemic, AI also played a major role in increasing accessibility to healthcare by offloading the lengthy task of conducting pre-consultation screening and risk assessments to virtual assistants (similar to the COVID-19 Self-Check web app Zudu donated to NHS Tayside at the beginning of the pandemic which is still used today, having helped hundreds of thousands of patients since April 2020). This approach not only lessened staff workload, but also made the services more user-friendly for people with disabilities and provided clear guidance to users that could be updated across all touchpoints simultaneously as regulations changed from region to region. It also enabled staff to focus on more urgent tasks, including helping patients who do not have access to the internet or are otherwise unable to use online services to get the help they need.
Towards the end of 2020, a survey by KLAS revealed that 83% of respondents cited “poor communication” as the most challenging part of their patient experience, with many of those surveyed also indicating clear ideas of the types of tools that would be helpful to them – both for improving the communication with their care provider, as well as services following their visiting, e.g. requesting repeat prescriptions, or tracking appointments, and getting quick answers to questions without requiring an appointment.
As pre-appointment and post-appointment interactions are key to improving patient relations alongside the methods of treatment themselves, these stages shouldn’t be ignored as they create opportunities for both public and private healthcare clinics to make the most of their resources and reduce unnecessary expenditure.