The Ministry of Science and ICT announced on the 20th that it has started the ‘AI Specialized Hospital AX-Ready Pilot Project’ to support AI transition in medical settings. The application period is until May 26.
This project is on a scale of up to 10 billion KRW over two years. Up to 5 billion KRW will be invested in the project this year. Applications will be processed electronically through the NIPA Project Management System starting April 29.
Eligibility requires general hospital-level public medical institutions to be the lead organization, with mandatory participation from AI solution companies and cloud companies in a consortium. Applications from individual companies or private hospitals alone are not allowed.
The key difference from existing AI introduction projects is the scope. Instead of introducing AI for specific disease diagnosis one by one, the goal is to implement the entire ‘Patient Journey’ as a single package, covering diagnosis, treatment, administration, and post-discharge management.
The three essential packages that must be demonstrated are as follows. Package① aims to establish an integrated operation base by introducing commercialized medical AI solutions like Dr. Answer and digital therapy devices throughout the hospital cycle.
Package② focuses on creating a collaborative platform that shares medical records and images between primary screening hospitals and secondary and tertiary treatment hospitals through cloud, and AI summarizes vast medical records for medical staff.
Package③ involves introducing systems such as voice recognition charts, automatic generation of customized discharge education materials, automation of insurance claims and pricing, and real-time patient safety monitoring systems for falls and pressure ulcers.
All three packages must be linked as a single scenario. The Ministry of Science and ICT will focus on ‘AX Leadership’ (whether there is a direct implementation structure under the director), ‘Connectivity’ (integration between packages), and ‘Scalability’ (economic analysis and pricing linkage plans) in the selection evaluation.
The background of this project stems from a longstanding issue. According to the Ministry of Science and ICT, 26 AI medical solutions developed through the Dr. Answer project have obtained MFDS approval. Technology verification is complete. The problem is these solutions are not integrated into actual hospital operations. This pilot project aims to address this point of non-utilized technology despite approval.
Targeting public medical institutions is also significant. Large private hospitals have the capacity for self-investment. In contrast, regional public hospitals often fall behind in digital transformation while managing essential and vulnerable group healthcare.
The initiative aims to first create a leading AI-based public hospital model to fill regional healthcare gaps. Including a pricing linkage plan in the ‘Scalability’ selection criteria reflects the realistic assessment that sustainable technology must be integrated with the insurance fee system.
The first key to the project’s success lies within the hospital. AI system implementation is more an organizational challenge than a technical one. It involves changing existing workflows of medical staff and redesigning medical processes.
This is why the Ministry of Science and ICT set ‘AX Leadership’ as a separate evaluation criterion, checking for a direct implementation structure under the director. Without the management’s determination, it’s difficult to gain participation from field doctors and nurses.
The requirement to connect the three packages as ‘one scenario’ also aligns with this reasoning. Implementing packages separately and then connecting them later has a high potential for integration failure.
For the entire process of outpatient visits, hospitalization, and discharge to be seamlessly connected by AI, an integrated structure must be established from the design stage. Since the participating consortium comprises hospitals, AI companies, and cloud companies, the meticulousness with which initial roles are divided and data interconnectivity protocols are configured will be key, experts point out.
Another hurdle to overcome is the difficulty of maintenance without pricing linkage. For the AI system to survive in hospitals even after the pilot project ends, medical staff must receive appropriate compensation for utilizing AI in medical practices.
The Ministry of Science and ICT’s inclusion of economic analysis and pricing linkage plans in the selection evaluation highlights awareness of this issue. There is criticism that discussions among related departments must accompany the pilot project results, leading to a reorganization of the health insurance fee structure.
The Ministry plans to use the results of this pilot project as a foundation to establish a regional ‘AI Specialized Hospital Network.’ The ultimate vision is a full-stack model encompassing infrastructure, platforms, and AI services in medical settings. Since the pilot project is merely the first gateway, setting clear standards for selecting participating institutions and measuring subsequent outcomes will influence the trust in the project.