Development of an AI-mediated knowledge surveillance system for environmental health care

The Vlaamse Overheid in Belgium from Europe region had released this tender for The Milieugezondheidszorg team of the Department of Health is responsible for the preparation implementation and justification of preventive health policies related to environmental health in Flanders Environmental health is the component of preventive health policy that employs a multidisciplinary approach involving at least the scientific disciplines of medicine toxicology epidemiology healthcare environmental technology and environmental science to prevent early detection and intervention in environmental health damage Within the Flemish Medical Environmental Network VMMN the team collaborates with various authorities research institutions and partner organizations The core activities of the team include climate health risk analysis promoting healthy public spaces environmental health focus areas recreational and drinking water quality indoor environment natural health and soil health Analyses are conducted to assess the environmental health impact and advice is formulated on environmental health aspects However the knowledge landscape in medical environmental science is growing exceptionally rapidly New scientific insights technological developments changing regulations and international social developments generate a continuous flow of information The systematic tracking evaluation and application of this knowledge is currently largely manual and requires significant human resources This leads to an increased risk of knowledge gaps while the Department of Health is expected to provide advice policy decisions and health impact assessments based on the most current and reliable insights To address this challenge the Department of Health aims to develop an AI-mediated knowledge surveillance system This system must automatically detect process structure and make relevant information from internal and external sources accessible to policy staff and experts The solution supports monitoring of scientific literature policy documents reports regulations and other knowledge sources and translates them into actionable document summaries and syntheses The system focuses on the four central narrative lines within Environmental Health Highly Hazardous Substances Climate and Health Healthy Public Space and One Health It organizes knowledge according to the exposure-burden-effect chain BBBE enabling users to quickly find and apply relevant insights in files risk analyses policy preparation and advisory work These initiatives are legally grounded in the prevention decree the decree on general provisions for environmental policy concerning environmental health aspects the MER decree and are implemented in line with the prioritization of the environmental health policy health goals and the climate health plan The intended solution supports human expertise but does not replace it Interpretation validation and policy-oriented interpretation remain the responsibility of content experts Therefore a human-in-the-loop approach is chosen where AI-generated outputs are supplemented with quality checks and human validation The solution must also comply with current requirements regarding privacy information security AI governance and regulations including the GDPR and the EU AI Act It must integrate with the Microsoft and Windows environment of the Department of Health and be aligned with the Policy Information and Data BID and Communication and IT CIT departments to ensure a secure scalable and sustainable solution that can also be applied in other teams within the Department of Health with tender notice no. 667294-2026 published on 06 Oct 2026. The tender expired on 01 Oct 2026. This tender is sourced from TED Europa and is eligible for suppliers interested in Medical information systems, IT services: consulting, software development, Internet and support. Interested bidders can obtain further information including complete bid documents or ways to participate by registering on Tender Impulse and referencing via Tender Impulse ID 15265494.