AI technology may improve efficiency in healthcare operations and help with faster diagnoses. However, a data challenge remains.
An estimated 371,000 people die yearly from misdiagnoses, and 424,000 are permanently disabled. Data suggests that CT scans are misread close to 30% of the time, while X-rays are misread 3–5% of the time. AI can help reduce these numbers drastically and save more lives.
Obi Igbokwe, CEO of WellNewMe, a healthcare and HMO company, explains that AI could play a role in imaging. “An AI can read large amounts of those images [X-rays and MRI scans] itself and churn out recommendations to the clinician that is looking at that picture,” Igbokwe tells TechCabal.
As technology continues to reshape various industries, AI stands out as a powerful tool in healthcare, offering promising solutions to address long-standing healthcare challenges and improve patient outcomes. WellNewMe offers preventative healthcare to empower individuals to take proactive steps towards healthier lives. By incorporating AI into their systems, WellNewMe can gather comprehensive health profiles of users which include medical history, lifestyle choices, and genetic predispositions. Analysing this data would enable the startup to generate personalised recommendations—which may include dietary plans, exercise routines, and wellness strategies—for the user.
Similarly, Charles Kamotho, CEO of Nairobi-based Daktari Africa recognises that AI can add value in recognising disease patterns from pre-existing data and thus come up with predictive models of best care. This is applicable in diagnostics, e.g. X-rays, as well as in therapeutics, to establish the best medicines for particular conditions.
Kamotho explains how this comes into practical use in Africa, considering that it’s still in its early stages on the continent. He tells TechCabal that “wearables are increasingly collecting plenty of data which will contribute to improved AI use”, and despite their novelty, Daktari Africa has “shown the impact of telemedicine in managing hypertension even in rural communities”.
While Daktari Africa and WellNewMe’s AI use depends on data gathering, it raises privacy concerns.
“While companies we work with can view aggregated reports of their employees on the platform, they cannot view each individual’s reports, because it’s always private data. We’ve implemented security and privacy measures on [our] platform,” WellNewMe’s Igbokwe told TechCabal.
Kamotho says that Daktari operates in “compliance with the HIPAA and with the Kenyan Data Protection Act”, and that their guiding principle in how data is handled is that “all data ultimately belongs to the patient”. Igbokwe says that WellNewMe have advisors that also advise them on [General Data Protection Regulation] GDPR as well as the HIPAA of the US “Because we are trying to make sure that our solution itself will benefit other climes as well,” he says.
However, Victor Famubode, an AI expert, says poor quality of data poses a challenge in the use of AI in healthcare. “Most of the data in the healthcare sector is largely unstructured, which makes it a bit difficult to use. Health data can be highly fragmented, and it requires extra effort and tools to ensure these data can be transformed into high-quality datasets for validation on models,” Famubode says.
Famubode says that gathering such data could help with making predictions about certain diseases. “Because the ability to store such historical data could assist with making predictions about disease outbreaks. For example, gathering high-quality data can support startups to thoroughly identify drug targets to test towards addressing specific diseases.”
While the quality of data might be an issue, another challenge for the use of AI in healthcare in Africa is the biases of medical data, says Ola Brown, a healthcare entrepreneur. AI bias occurs because human beings choose the data that algorithms use, and also decide how the results of those algorithms will be applied. Most of the current data on which AI algorithms are trained are obtained from Western countries and there is little or no input from Africa.
One way to tackle this problem is to gather more data locally and use them to train more AI models. Igbokwe confirms that WellNewMe is looking inwards into rural Nigeria by building health kiosks equipped with trained locals to help gather data and onboard more people. But Famubode believes that introducing an adequate governance framework will help AI aggregate the health data of Africans such as genetic data, thereby reducing data bias.
According to Famubode, the use of AI could improve efficiency in healthcare operations in the short term and help with faster diagnosis of diseases thereby improving the overall quality of life in the long term.
In Africa, AI has the potential to transform healthcare for the better. Daktari Africa, which claims to be the first telemedicine platform in Kenya and the region, promises to be “a step ahead to ensure quality”.
And Lagos-based WellNewMe is setting their eyes on a continental expansion, with promises of significantly improving their existing solutions before the year ends.
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