The Christian health insurance fund (CM) plans to use artificial intelligence to identify employees at risk of long-term illness before they officially drop out, De Standaard reports.
CM Chairman Luc Van Gorp told De Standaard that the existing framework allows people to work in harmful conditions until their health abruptly crashes. He sees the solution in shift toward root-cause prevention rather than a reactive approach.
Starting in 2027, the mutuality intends to implement a digital early detection system. Algorithms will analyze specific health data parameters to flag vulnerable profiles, such as frequent short-term absences, a streak of ongoing multiple physiotherapy sessions, and ongoing medication usage.
Medical literature confirms such variables can predict who is in danger of takingd a long-term medical leave.
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A pilot project is already underway in collaboration with the Antwerp Management School. Researchers are monitoring staff in under "orange" threat level across 12 diverse companies. These workers experience mounting pressure but remain active on the job.
The project isolates daily triggers. Participating companies are then instructed to deliberately alter their working methods for several weeks to evaluate what effectively prevents a medical exit.
Van Gorp intends to present the strategy to Federal Health Minister Frank Vandenbroucke (Vooruit), noting that legislative adjustments might be required. He also wants to collaborate with other mutualities to scale the preventative approach.
Health insurance funds, also known as mutualities, bear the primary financial and administrative responsibility for workers on extended sick leave in Belgium. The number of individuals currently sitting at home with prolonged illnesses has exploded to roughly 580,000 across the country.
This push for proactive intervention arrives at a complicated time politically. Right-wing parties N-VA and MR are actively targeting the core financing of health insurance funds during the ongoing federal budget negotiations.
Deploying predictive algorithms demands substantial capital and manpower. Van Gorp stressed that technology will strictly serve as a preliminary detection tool.
Human staff, including advising doctors, health consultants, and return-to-work coordinators will exclusively handle the subsequent medical guidance.
