Improving Claims Processing in the Medical Aid Sector Through Robotic Process Automation: A Scoping Review

Every time a doctor treats a patient and sends a bill to a health insurance plan, a complex administrative journey begins. This journey, known as claims processing, is the engine that keeps private healthcare running, ensuring providers get paid and patients receive their reimbursements. For years, this engine has relied heavily on human hands. Workers sit at desks, manually typing data from paper forms or digital files, checking if a patient is eligible, verifying diagnoses, and calculating payments. It is a slow, repetitive, and often error-prone task. When volumes of claims grow, as they have in South Africa's medical aid sector, the system clogs. Delays pile up, costs rise, and the people waiting for answers grow frustrated. In an era where technology promises to streamline almost every aspect of modern life, the question has become whether machines can take over these tedious, rule-based tasks to free up human workers for more complex problems.

This is the central puzzle tackled by Masego Precious Mmotlana in a recent scoping review, a type of research that maps out what is already known about a topic rather than conducting a single new experiment. Mmotlana, a researcher at Tshwane University of Technology, set out to gather and organize existing studies on Robotic Process Automation, or RPA, specifically within the context of medical aid claims. RPA is a form of software that acts like a digital worker. It does not possess human intelligence or the ability to make creative judgments; instead, it follows strict, pre-programmed instructions to perform repetitive tasks such as copying data from one system to another, checking documents against a list of rules, or sending standard emails. The review sought to understand if this technology could truly speed up the claims process in South Africa, how it changes the speed and accuracy of work, and what hurdles organizations face when trying to install it.

To build a clear picture, the researcher cast a wide net, searching through thousands of academic papers, industry reports, and government documents published between 2021 and 2026. The search began with over a thousand records from various databases, but the process was rigorous. Duplicate entries were removed, and studies that did not focus specifically on claims processing or the medical aid environment were set aside. After carefully screening titles, abstracts, and full texts, the final selection narrowed down to twenty studies that offered the most relevant insights. These included journal articles, conference papers, and industry reports from around the world, with a notable gap: only one of the twenty studies focused specifically on the South African healthcare context, and even that one looked at public hospitals rather than private medical aid schemes. This scarcity of local data meant the review had to lean heavily on international evidence to draw conclusions about the South African situation.

The findings paint a consistent and promising picture of what RPA can achieve when applied to claims processing. The studies reviewed suggest that when organizations introduce these digital workers, the results are immediate and tangible. The software excels at handling high volumes of repetitive tasks, such as data entry and document verification, which are the primary bottlenecks in the current system. By taking over these duties, RPA significantly reduces the time it takes to process a claim. It also cuts down on human error, as a machine does not get tired or distracted when checking the same rule thousands of times a day. The result is a smoother workflow where claims move faster from submission to payment, leading to better service for patients and less administrative burden for staff. The review indicates that this technology does not just speed things up; it makes the entire process more reliable and consistent.

However, the path to installing this technology is not without its obstacles. The research highlights that simply buying the software is not enough to guarantee success. The studies point to several significant challenges that organizations must navigate. One major hurdle is system integration; the new robots often struggle to talk to the older, existing computer systems that hospitals and insurance companies have used for decades. There are also concerns about data quality; if the information fed into the system is messy or incomplete, the robots cannot work correctly. Furthermore, the human element plays a crucial role. The review suggests that employees may resist the change, fearing that automation will replace their jobs, and that organizations often lack the necessary governance structures to manage these new tools effectively. Without clear rules, standardized processes, and a workforce that is ready to adapt, the implementation of RPA can stall or fail to deliver its full potential.

A striking aspect of this review is the disconnect between the global evidence and the local reality in South Africa. While the international literature is rich with examples of successful automation in insurance and healthcare, the specific evidence for South African medical aid schemes is thin. The review found that while industry reports suggest major South African schemes are already beginning to adopt these technologies, academic research has not yet caught up to document the real-world outcomes. The single study that did focus on South Africa looked at public healthcare institutions, leaving a gap in our understanding of how these tools function within the private medical aid sector, which serves millions of beneficiaries. This lack of local data means that while the potential benefits are clear, the specific challenges and success stories within the South African context remain largely unexplored in the academic record.

Ultimately, the review concludes that Robotic Process Automation holds significant promise for transforming claims processing in the medical aid sector. It offers a way to reduce delays, lower costs, and improve the accuracy of payments, provided that organizations are willing to do the hard work of preparation. Success depends not just on the technology itself, but on the organization's readiness to standardize its processes, ensure data is clean, and manage the change among its staff. The researcher recommends that medical aid organizations prioritize these foundational steps before rolling out automation. For the future, the review calls for more research specifically focused on the South African medical aid industry to fill the current evidence gap. Until then, the picture remains one of high potential tempered by the need for careful, strategic implementation, ensuring that the digital workers are guided by strong human leadership to create a more efficient and responsive healthcare system.