The healthcare industry is mired in technological backwardness where digital transformation is highly needed yet enormously underdeveloped. As per a recent McKinsey study, 83.1% of clinic executives rate the digitisation maturity and quality within their clinics as low to medium. Operational inefficiencies are rife, and the high administrative burden exacerbates time pressure during treatments (averaging 8 minutes per patient), increasing the risk of treatment errors up to 25% worldwide. Financial ramifications are also significant, with billing errors at a rate of 20%, amounting to avoidable costs of approximately €17 billion annually.
Avelios Medical aims to solve this problem by offering a trailblazing, holistic, modular plug & play clinic platform enabling comprehensive digitisation across all hospital departments. By interlinking intelligent input fields with medical libraries and databases, it achieves automatic data structuration to generate up to 2,000 data points per patient and treatment. This functions as a foundation for the self-learning AI-powered diagnostic support and workflow engine of Avelios Medical, facilitates actionable medical insights and research possibilities. Our software looked for saving up to 10 minutes on administrative tasks per patient treatment and to drastically improve the quality of care, ensuring that all data processing activities comply with GDPR, safeguarding patient privacy and maintaining high ethical standards. Key features include automatic generation of doctor’s letters, billing with diagnosis coding, and complete digitisation of patient data handling.
The main impacts of the project are:
• 20% less time spent on administrative tasks.
• Up to 80% fewer treatment errors.
• Hospitals save up to €650 per patient; (in global terms, the medical billing error reduction saves €2.8 billion annually).
• Enhanced treatment transparency and efficiency, longer patient interaction times (additional 10 minutes per treatment).
• First-time structuring and utilization of up to 2,000 data points per treatment for meaningful AI-driven medical research.
• Supports EU digital sovereignty and legislative mandates for digital health records.
The integration of social sciences and humanities into the project is fundamental. The interdisciplinary approach ensures that regulatory, ethical, and user-centric perspectives are considered, bridging the gap between technological innovation and humanistic care.
