The healthcare sector is rapidly adopting artificial intelligence (AI), from faster claims processing to customized, large-scale language models that help patients navigate their symptoms and understand their benefits. AI provides smarter, more intuitive systems for patients, healthcare professionals, and society at large.
Here are five global examples of how AI is rapidly advancing the evolution of healthcare.
1. Streamline processing
Kenya's M-TIBA is a mobile healthcare finance platform that integrates machine learning to speed up healthcare claims processing.
Until recently, medical insurance claims could take days or weeks to resolve, creating delays for healthcare providers and patients.
AI-driven validation models can now evaluate and approve certain applications within hours.
The system reviews submitted information against historical trends and alerts you to anomalies to reduce errors, all while reducing administration time.
Shorter evaluation times also improve the overall customer experience.
For insurers, streamlined processing reduces manual reviews and lowers operational costs.
2. Enhanced accessibility and support
Locally, the Fedhealth Medical Scheme recently launched Naledi, an AI agent designed to answer members' basic medical aid-related questions.
Naledi provides general guidance on benefits, plan details, and processes, so you don't have to use a call center or wait for an email response.
Members can receive support much more efficiently, especially for routine queries, and can contact our customer service team for more complex or urgent queries.
In this way, Naledi reflects a broader global trend towards using AI to enhance accessibility and support rather than replace human experts.
3. Pre-approval process
In the US, companies like EviCore are using AI to support the pre-approval process for specialized medical procedures.
These tools review clinical guidelines, past billing behavior, and medical history to ensure that treatment requests meet institutional standards.
The goal of this is to accelerate the approval of needed treatments and reduce bottlenecks faced by both doctors and patients.
While automation is convenient, this type of system also emphasizes the ethical need for transparency.
Specifically, insurers that use AI for approvals will need to ensure human oversight and help patients understand how decisions will be made, especially if their request is denied.
4. Predictive analytics
Australian health insurance company NIB offers an AI-powered symptom checker on its mobile app that acts as a virtual triage tool.
As users enter their symptoms, the tool dynamically adjusts the questions to determine the severity of the case and recommends appropriate next steps.
For example, it can help you identify when it's appropriate to go to the emergency room, when it's appropriate to see your GP, and when symptoms can be safely monitored at home.
In doing so, these types of tools reduce the burden on emergency rooms from unnecessary visits while also supporting increased health literacy.
It also provides peace of mind during times when access to medical facilities is difficult, such as during holidays.
Predictive analytics can also help insurers promote preventive care by identifying emerging health risks early.
5. Detect fraud and improve efficiency
In the US, insurance technology company Curacel's Health AI service instantly responds to health-related claims and uses AI to manage pre-authorization processes quickly and efficiently.
From a healthcare provider perspective, this tool also improves claims efficiency through smart fraud detection, helping reduce losses and increase revenue.
Fraud remains a significant challenge for insurance companies around the world as it increases costs and ultimately impacts customer premiums.
Tools like Health AI are making great strides in reducing fraud, helping insurers maintain relatively stable premiums in the face of rising healthcare costs.
Medical ethics and AI
When it comes to innovation in healthcare, the rise of AI in healthcare offers exciting possibilities by helping healthcare providers respond faster, become more efficient, and become more member- and patient-focused.
According to a trend analysis by Deloitte, the role of AI in healthcare can range from simple tasks such as reviewing and analyzing medical records to more complex tasks such as reading radiology images, making clinical diagnoses, and even talking with patients.
However, while AI is promising, issues such as data privacy, algorithmic fairness, and transparent decision-making must be carefully considered to ensure that AI is used ethically and fairly, especially in the case of naledi in the local medical assistance sector.
Specifically, the tools used to guide health-related decision-making should complement, not replace, expert knowledge, experience, and judgment.
As WEF points out, trust between patients is also likely to be an issue with AI and medical advice, making regulation of these tools even more important.
As AI continues to evolve, every aspect of healthcare services, from hospitals to doctors to medical assistance, has the potential to become more personalized, more intuitive, and more proactive in ways that were not possible a decade ago.
But it is clear, at least for now, that AI will not replace the human side of healthcare, but rather enhance it by helping professionals be more accurate, responsive, and supportive of patients.
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