Valued at US$10.4bn in 2021, the global artificial intelligence (AI) in healthcare market is expected to continue to grow at a compound annual growth rate (CAGR) of 38.4% from 2022 to 2030.
Lending itself to this growth is the growing datasets of patient health-related digital information, increasing demand for personalised medicine, and the rising demand for reducing care expenses.
Additionally, AI was key in the fight against COVID-19. Soon after the pandemic was declared, the World Health Organisation (WHO) signalled that AI could be an important technology to manage the crisis caused by the virus.
As it was able to help with detection and diagnosis during the pandemic, many technologists and healthcare professionals were keen to get this technology applied throughout healthcare organisations as it had well and truly proved its worth.
Already automating processes in a number of healthcare organisations, we take a look at more ways AI could revolutionise healthcare in the future.
1 - How AI can improve the patient and employee experience
Patient satisfaction is a top priority for many hospitals and healthcare organisations. With machine learning and (AI) patient data can become invaluable, providing insights into where improvement in the patient journey is needed. Machine learning systems provide an opportunity for hospitals to improve overall health outcomes, as patient satisfaction is strongly associated with greater compliance and increased treatment adherence, according to researchers.
AI can also provide more personalised and convenient healthcare experiences. Chatbots used by healthcare organisations can also boost patient satisfaction. It seems that many people are happy for AI to be applied as back in 2019, a Pegasystems survey of 2,000 healthcare consumers found that almost half (42%) of patients said they are comfortable with their doctors using AI to make healthcare decisions.
For healthcare workers, AI can also play an invaluable role as it can complete a number of manual tasks, freeing up workers' time and reducing burnout. AI can help remove or minimise time spent on routine, administrative tasks, which can take up to 70% of a healthcare practitioner’s time.
2 - Delivering care in new ways through AI
By refining the use of AI for clinical surveillance, hospitals can proactively identify a range of health conditions with greater speed and accuracy. AI-powered clinical surveillance can save lives and reduce costs for conditions that have previously proven resistant to prevention.
AI can analyse millions of data points to predict patients at-risk for healthcare-associated infections, enabling clinicians to respond more quickly to treat patients before their infection progresses, as well as prevent spread among hospitalised patients.
According to the World Health Organisation, by 2030 healthcare systems could anticipate when a person is at risk of developing a chronic disease, for example, and suggest preventative measures before they get worse. This development has been so successful that rates of diabetes, congestive heart failure and COPD (chronic obstructive heart disease).
3 - AI-driven drug discovery
When it comes to drug discovery, AI has the potential to make processes faster and more cost-effective, with the hope of reducing the time a new drug needs to reach the patient. AI can sort through masses of information and data from tissue or blood samples from patients who have the disease and others who don't. This could help researchers look into new compounds likely to target those proteins. During the coronavirus pandemic, AI was successfully used to identify potential drugs that could be used to treat Covid-19.
Last year, Google’s Deepmind AI system AlphaFold has found a solution to how proteins fold into their 3D structure, which may create new opportunities in structure-based drug design.
4 - Harnessing AI for patient risk identification
In healthcare, predictive analytics can process and evaluate enormous amounts of historic and real-time data to create valuable forecasts, predictions and recommendations on anything from individual patient care to wider public health. By assessing tens of thousands of data points, predictive analytics can predict a number of things from an individual's risk of developing illnesses to their likelihood of coming back into a hospital with an infection.
In doing so, predictive analytics can help healthcare professionals become more proactive with their treatment plans and potentially reduce the need for expensive and time-consuming surgeries or treatments.
5 - Transforming radiology with AI
AI-powered systems are already being used in computer-aided cancer detection, they can classify brain tumours and reduces the tumour classification time to about three minutes. The technology can also be applied to detect hidden fractures, recognise breast cancer and detect neurological abnormalities.
On top of this, AI can reduce the workload of radiologists by completing more monotonous tasks and free up clinicians' time to complete tasks that require human interpretation.