How medical SMBs can benefit from AI for healthcare

The World Economic Forum estimates that by 2035, there will be a global deficit of 12,9 million skilled health professionals. This will put a heavy burden on healthcare systems around the world; from hospitals to clinics, all will feel the effects. Patients will no doubt bear the brunt, but so will the doctors and nurses who have to share the load. Plus, more people will be accessing healthcare: in MENA, the total population is predicted to increase to 581 million (up from 484 million in 2018). The deficit will not only have an impact on hospitals and healthcare systems at large, but it will filter down to clinics and smaller practices, too.

There is another scenario, however.

By 2035, clinics, doctors' rooms, same-day surgery centers, and even patients’ homes are connected to a single command center, on the same digital infrastructure. There’s still a 12,9-million deficit in healthcare workers, but hospitals just focus on emergencies and complex surgeries, while smaller practices deal with day-to-day medical needs. All the patient data is linked to a central network on the cloud and is monitored in real-time for backlogs, medicine supply, and more.

It may sound like a pipedream, but this scenario is possible with AI.

I am under no illusion that reaching this point will not be straightforward. Using AI to make healthcare more efficient, less costly, and patient-centric is not a simple task, especially for smaller players who can’t afford huge investments in technology and who lack digital skills. But this doesn’t mean that AI is only for large enterprises like hospitals. 

Medical SMBs stand to benefit from AI, thanks to scalable cloud platforms that allow for more affordable functionalities, including AI and data insights, while AI-powered health bots can free up time usually spent on admin.

An AI shift is starting, but the basics must be in place to take advantage

AI in healthcare remains relatively untapped and small in scale around the world, but changes are certainly happening. In the GCC alone, Saudi Arabia has approved an AI strategy which is expected to contribute $133 billion to the GDP by 2030, while in 2019 Oman’s Ministry of Health and Information Technology Authority piloted AI in five hospitals for early diagnosis of breast cancer. Abu Dhabi’s Department of Health has also launched an AI laboratory in partnership with American Hospital Dubai and Cerner; the multi-phase AI transformation programme includes a data lab built within American Hospital Dubai's datacenter, as well as the use of intelligence predictive models.

While these examples of innovation are impressive, according to McKinsey’s Transforming healthcare with AI report, the initial, more widespread use of AI is likely to relate to routine and repetitive administrative tasks, as well as imaging and pathology. AI systems can automate writing out scripts and detect tumors through radiological pattern recognition, and the time that could be made available for life-saving surgeries or longer doctors’ consults could be significant. 

Digital skills will of course play a major role in any AI transformation, whether in a large hospital or a doctors’ practice. Most healthcare practitioners in 2021 are not equipped with digital skills, but this needs to change.

McKinsey states in their report that the future of healthcare will require an understanding of medicine and data science – and I completely agree. Basic skills such as digital literacy, genomics fundamentals, AI, and machine learning will need to form part of the primary training for everyone who studies medicine – as well as continued learning.

For smaller players, there are challenges – and opportunities

Smaller players in the healthcare sector may struggle to get access to enough quality data for AI to have an impact, and they may not have the resources for digital reskilling. But, by working together in “innovation clusters” that merge AI, digital health, biomedical research, or translational research, they can potentially benefit immensely. For less developed areas, simple AI systems based on SMS technology can be utilized, too.

AI doesn’t have to be an expensive and inaccessible undertaking – I believe that if the basics are covered, AI can be successfully deployed to completely transform healthcare at every level. And it’s becoming clear that while the deployment of AI in healthcare remains on a small scale worldwide, it’s increasingly being adopted in everything from apps to imagery.