5 ways AI is fast-tracking the evolution of healthcare

Healthcare is rapidly adopting artificial intelligence (AI) — from speedier claims processing to tailored large language models that help patients navigate symptoms or understand their benefits. AI provides smarter and more intuitive systems for patients, healthcare workers, and society as a whole.
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Image credit: Google DeepMind on Pexels

Here are five global examples of how AI is fast-tracking the evolution of healthcare:

1. Streamlined processing

In Kenya, M-TIBA is a mobile health financing platform that integrates machine learning to speed up medical insurance claims processing.

Up until recently, medical insurance claims could take days or weeks to resolve, creating delays for providers and patients.

With AI-driven verification models, certain claims can now be assessed and approved within hours.

The system reviews submitted information against historical trends, flags anomalies and reduces errors, all while cutting down on administrative time.

Faster assessment times also improve the overall customer experience.

For insurers, streamlined processing means fewer manual reviews, which reduces operational costs.

2. Enhancing accessibility and support

Locally, Fedhealth Medical Scheme has recently launched Naledi, an AI agent designed to answer basic medical aid-related questions for members.

Naledi provides general guidance about benefits, plan details and processes, so they don’t need to use the call centre or wait for a response on email.

Especially for routine queries, members can get help far more efficiently, and are referred to the customer service team for more complex or urgent queries.

In this way, Naledi reflects a broader global trend: using AI not to replace human experts, but to enhance accessibility and support.

3. Pre-authorisation processes

In the United States, companies like EviCore use AI to support the pre-authorisation process for specialised medical procedures.

These tools review clinical guidelines, past claims behaviour and medical histories to see whether a treatment request aligns with a scheme’s criteria.

The goal with this is to accelerate approvals for necessary treatments and reduce bottlenecks faced by both doctors and patients.

While automation is useful, this type of system also highlights the ethical need for transparency.

Specifically, insurers using AI for authorisation must ensure that human oversight is robust and that patients understand how decisions are made – especially when a request is declined.

4. Predictive analytics

Australian health insurer NIB offers an AI-powered symptom checker in its mobile app that works as a virtual triage tool.

Users enter symptoms, and the tool dynamically adjusts questions to determine the severity of the case and recommend appropriate next steps.

For example, it can help identify when to seek emergency care, when a GP visit is appropriate or when symptoms can be safely monitored at home.

In doing so, these types of tools reduce the load on emergency rooms through unnecessary visits, while also supporting better health literacy.

They also offer reassurance during times when medical advice is harder to access, for example, during the holidays.

Predictive analytics are also helping insurers encourage preventative care by identifying emerging health risks early.

5. Detecting fraud and improving efficiency

In the US, insurance tech company Curacel’s Health AI offering gives instant responses to health-related claims and uses AI to manage the pre-authorisation process quickly and efficiently.

From a healthcare provider’s perspective, the tool also boosts claim efficiency with smart fraud detection to help cut losses and increase revenue.

Fraud remains a significant challenge for insurers worldwide, as it drives up costs that ultimately affect customer premiums.

A tool such as Health AI makes significant progress in reducing fraud, allowing insurers to keep premiums relatively stable, even in the face of rising medical costs.

Medical ethics and AI

When it comes to healthcare innovation, the rise of AI in medical care offers exciting possibilities by helping providers become more responsive, more efficient and more member or patient-focused.

As a trends analysis by Deloitte notes, AI’s role in healthcare could range from simple tasks like medical record reviews and analytics through to more complex tasks like reading radiology images, making clinical diagnoses, and even talking with patients.

But as promising as AI is – particularly in the case of Naledi in the local medical aid space – issues such as data privacy, algorithmic fairness, and transparent decision-making will need to be carefully considered so that it’s used ethically and fairly.

Specifically, any tool used to guide health-related decisions should complement, rather than replace, professional expertise, experience and judgement.

As the WEF notes, trust among patients is also likely to be an issue in AI and healthcare advice, making the regulation of these tools even more important.

As AI continues to evolve, all aspects of healthcare service – from hospitals to doctors to medical aid – are likely to become more personalised, more intuitive and more proactive in ways that weren’t possible even a decade ago.

It’s clear, though, that for now at least, AI will not replace the human side of healthcare, but rather enhance it by helping experts become more accurate, responsive, and supportive of their patients.


 
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