Will AI make healthcare more inclusive and affordable?
Welcome to Fast Company Middle East Pulse, our daily newsletter on LinkedIn, featuring an article selected each day by our editors on topics around innovation in technology, business, leadership, and design.
Sign up here to get Fast Company Middle East's newsletter in your inbox!
------------------------------------------------------------------------------------------
The saying “prevention is better than cure” could not be more true than in the diagnosis of cancer. Cancer, a leading cause of death worldwide, currently contributes to more than one in every six deaths globally. And breast cancer accounts for 30% of new female cancer cases each year.
Recently, AI achieved a remarkable milestone by accurately detecting early signs of breast cancer years before it develops. This breakthrough shows how far we’ve already achieved with AI, paving the way to enhance early detection and intervention in healthcare.
Yet, amidst all the advancements, the ultimate measure of success remains its direct impact on patients.
REIMAGINING PATIENT CARE
Hospitals are increasingly integrating AI technologies to revolutionize operations and patient care.
AI redefines the hospital management and treatment industry by enhancing diagnostic accuracy and streamlining administrative tasks.
“By harnessing advanced algorithms, machine learning, and data analytics, hospitals are not only boosting efficiency and reducing costs but also delivering more personalized and effective care,” says Alice Yammine Boueiz , Chief Executive Officer at Arab Hospitals Federation.
But even though AI is the most common buzzword for this era, considerable skepticism is being spread about overpackaging technological development under the AI umbrella.
Vijay Sagar , Chief Operations Officer at Al-Dawaa Medical Services Co. , highlights technological advancements such as automation and digitalization.
“AI is another and different level of evolution, but the other two remain core, too. Calling it right helps engage and manage expectations.”
The healthcare industry continues to use automation to improve financial and productivity efficiencies. Over the years, automation has helped to better plan for future growing demands, manage rising workforce challenges, and support a more robust regulation framework. This supports the longevity of organizations and, in turn, supports the availability of quality healthcare services.
On the other hand, digitalization has introduced a modern, convenient era for organizations’ operations and patient journey.
“Be it medical records, prescriptions, or receipts, moving from paper to mobile applications has changed how we interact today,” he adds.
However, as AI-driven healthcare solutions become more prevalent, it’s crucial to consider the potential ethical implications, such as data privacy and equity.
THE HEALTHCARE DISPARITY
According to Veneeth Purushotaman CHCIO , Group Chief Information Officer at Aster DM Healthcare , the biggest disparity in healthcare is its affordability and accessibility, and adopting technology reduces this disparity.
AI-powered telemedicine and remote care solutions make quality healthcare accessible to patients in remote areas with limited facilities. These solutions also help reduce care costs by optimizing resources, making it more affordable for underserved populations.
AI personalizes treatments and, through proactive health monitoring with wearables and AI-driven apps, empowers individuals to manage their health effectively. This approach eases the burden on healthcare systems and enables early intervention.
Boueiz points out that AI enhances medical research by including diverse populations, ensuring that new treatments are effective across all demographic groups. By integrating these innovative approaches, AI not only advances technology in healthcare but also significantly contributes to reducing inequalities and promoting a more inclusive healthcare system.
However, the ethical considerations of AI-driven healthcare—such as bias, privacy, transparency, and equitable access—are critical to ensuring that these technologies benefit all patients.
Automation and digitalization are already working well, but basic human interaction, empathy, and trust matter in the patient care process.
Sagar says it is as simple as this: walk into a pharmacy, laboratory, or clinic, and when you see someone physically in front of you with a white coat on, you have a default assurance that you are being looked after.
Data protection is crucial.
Recommended by LinkedIn
No matter how many papers we sign or tick boxes, data remains open. Sagar adds that much work must be done to build confidence.
He adds that more work must be done to educate AI governance within organizations, and it should be a constant drumbeat. That’s why cybersecurity and AI governance are the top topics on every executive strategic goal list.
THE ETHICAL CONSIDERATION
AI has immense potential to enhance patient outcomes through its ability to personalize treatments, enable early disease detection, providing predictive analytics, and streamlining healthcare processes.
However, Boueiz adds that realizing all these benefits while addressing data privacy and ethical concerns requires a wide-ranging tactic.
Robust data protection in AI involves strict encryption, secure storage, and access controls to protect patient information. Equally important is transparency in AI models, which promotes trust by providing clear explanations of how decisions are made.
By integrating these practices, AI can be harnessed to revolutionize healthcare, delivering improved patient outcomes while upholding the highest standards of data privacy and ethical responsibility.
Purushotaman suggests that creating a robust regulatory framework for health data involves integrating established standards, such as GDPR and HIPAA, with new ethical guidelines from organizations like the WHO. This approach aims to ensure both innovation and protection in the evolving landscape of healthcare technology.
Also, interdisciplinary committees combining AI experts and practitioners are established to ensure meaningful and safe AI applications. Data anonymization and encryption protect patient information, while pilot programs and sandbox environments help identify and address issues like false positives.
“Ensuring the explainability and transparency of AI systems is crucial as long as clinicians find the AI’s logic and transparency convincing, the technology is more likely to gain acceptance,” Purushotaman adds.
MENTAL HEALTH REQUIRES E.I., NOT AI
Boueiz says AI technologies are significantly solving challenges in mental health care and support services in the Middle East by offering innovative options that improve accessibility, personalization, and efficiency.
She believes digital therapy tools, AI-powered chatbots, and virtual therapists provide immediate and scalable mental health support, particularly in regions with limited access to professionals.
Predictive analytics allows for the early detection of mental health issues, leading to timely and personalized interventions. AI applications enhance access to care, improve early detection, and optimize resource use, resulting in better mental health outcomes across the region.
Regarding mental health, Sagar is glad for digital apps like CALM and Headspace that support mental health care development. In his opinion, “This topic is still not voiced out enough, and whatever is voiced out is not addressed well by fellow humans. So, do we need someone artificial help when humans are yet to master it?”
However, mental health is a deeply sensitive area where automated tools loaded with online content cannot always solve a person’s condition. It may auto-suggest but may not fully be relevant.
He adds, “An important battery for mental health is emotional intelligence, so please let AI not trespass on this area.”
ACHIEVING EQUITABLE AI ADOPTION
Purushotaman highlights that AI has the potential to significantly improve access to care when used in collaboration with other technologies, such as telemedicine, teleradiology, and remote care.
Boueiz also points out that these technologies enable timely consultations, continuous health management, and accurate diagnoses, bridging gaps in healthcare availability.
However, several challenges must be addressed to achieve equitable AI adoption, including infrastructure limitations, data privacy concerns, provider training, cost barriers, and cultural adaptability.
By overcoming these obstacles and ensuring that AI technologies are accessible, secure, and effectively integrated, we can improve healthcare delivery and outcomes for populations in even the most remote and underserved regions.
Check out some of the Fast Company Middle East's best-read stories: