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Home Features Guest Writer

Rethinking African Healthcare Through AI Integration

by Techeconomy
August 26, 2023
in Guest Writer
3
Rethinking African Healthcare Through AI Integration
Telemedicine

Rethinking African Healthcare Through AI Integration

UBA
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IFTHAKAAR SHAIK Vitruvian Medical Diagnostics
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Writer: IFTHAKAAR SHAIK, Co-founder of Vitruvian Medical Diagnostics

The African healthcare industry faces an immediate challenge: a dire shortage of skilled professionals, leading to alarmingly low doctor and nurse-to-population ratios in many countries. Training medical professionals, especially specialists like pathologists or oncologists, is a multi-year long process.

Moreover, foundational education at the primary and secondary levels is crucial to supply tertiary institutions with a stream of candidates equipped with the necessary aptitude, literacy, and numeracy skills to pursue medicine.

Recent technological leaps catalysed by the COVID-19 pandemic and expanding telecommunications infrastructure, including ventures like Starlink, have bridged some of the distance between communities in need of medical services.

Telemedicine offers those with limited physical access to healthcare professionals a chance to benefit from their expertise.

Still, the scope of what can be accomplished via a video call is limited. Accurate diagnoses are particularly challenging. Medical professionals rely heavily on information relayed by patients or, in the best-case scenarios, by lesser-skilled colleagues following instructions remotely.

Compounding these issues, Africa grapples with a healthcare brain drain. To shore up shortages in their own healthcare systems, “developed” markets actively poach African healthcare workers, further depleting the continent’s medical resources.

It’s within this landscape that artificial intelligence (AI) emerges as a revolutionary force in healthcare. Its precise deployment can literally mean the difference between life and death in underserved areas and can dramatically reduce healthcare costs in the neediest markets.

Creating an onramp for usaical Diagnoge before reaching the AI tipping point

AI’s promise in healthcare is undeniable. However, this potential can be wasted if we fail to bridge the divide between the digital realm and real-world applications. The most groundbreaking healthcare software becomes moot if not pragmatically integrated into devices used on the ground.

Our journey at VitruvianMD illustrates this challenge. Though our primary focus is healthcare, AI remains our foundational tool. One significant motivation behind our company’s inception was to address the skill shortage in pathology, an essential but understaffed field in Africa.

Our initial target was malaria. In 2021, malaria claimed around 593,000 lives in Sub-Saharan Africa, accounting for 96% of global malaria deaths.

Initially, it seemed that AI could assist in addressing this problem, however, as our company development progressed, it became evident that we needed tangible means to bridge the gap between AI’s theoretical benefits and practical implementation. Collaborating with experts, we merged AI with biomedical engineering, creating a universal-fit microscope camera. Equipped with cutting-edge software, this camera provides users with detailed analyses of their samples.

Taking this integrated approach, and by working in partnership with the medical community, we were able to develop tools addressing not only malaria but other conditions that benefit from timely pathology services.

We’re even moving towards a space where even non-pathologist medical professionals are able to accurately analyse samples. Additionally, pathologists could soon be able to remotely analyse samples.

African healthcare – AI can fill skill voids and reduce costs

This is no small gain. In transit, a lot can go wrong. A blood sample could become contaminated, be sent to the wrong place or not arrive at all.

By providing on-site testers with enough information to either make a diagnosis or communicate what they receive to skilled personnel in a different location, we mitigate the transport risk inherent in a region with such a low pathologist-patient ratio.

This doesn’t even factor in the everyday infrastructural obstacles that patients throughout the continent grapple with.

Removing these kinds of obstacles results in quicker diagnoses and decreased expenses throughout the healthcare process.

These benefits can then be directly utilised to enhance patient care at the point of service. In severe circumstances, a delay in pathological diagnosis, for whatever cause, could mean the difference between life and death for a patient.

Additionally, by enabling those who are not pathologists to perform tasks within pathology, the camera and its accompanying software assist in bridging a significant skills gap.

As it stands, there is only one pathologist for every million people in Sub-Saharan Africa. However, this statistic is somewhat skewed, with the majority of these pathologists being based in South Africa.

The forthcoming decades will witness AI’s transformative impact on healthcare. As we stand on the precipice of this revolution, it’s evident that the integration of AI into healthcare will shape its future, promising substantial benefits for Africa and other developing nations.

Over the next two to three decades, AI is poised to revolutionise healthcare in ways we can only begin to fathom now. At present, we’re merely glimpsing the tip of the iceberg in terms of AI’s potential in this sector.

The nexus between the future of healthcare and AI integration will be indomitable. Particularly, African nations and other developing regions have a golden opportunity to reap substantial benefits from these advancements.

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    Techeconomy

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  1. Pingback: Skrind’s AI Solution is Modifying Healthcare Delivery in Nigeria - Health Reporter
  2. Pingback: Skrind’s AI Solution Is Modifying Healthcare Delivery In Nigeria - News Curators
  3. Pingback: A Doctor’s Journey in the Battle Against HIV/AIDS: From Desperation to Empowerment - Tech | Business | Economy

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