From Computers to AI: Bryansk Region Moves Hospitals to Russian Software
The Bryansk Region has completed a major project to transition healthcare organizations to Russian software. More than 10,000 computers across 61 medical facilities in the region now run on domestic software.
In 2020, healthcare organizations in the Bryansk Region were using foreign software. The regional health department faced the challenge of switching to Russian alternatives while keeping hospitals and clinics running smoothly and protecting their IT infrastructure.
RED SOFT, a developer and supplier of IT solutions and services, became the project's key technology partner. The transition to the RED OS operating system was carried out in stages. In 2020, 4,700 workstations were migrated to the system, followed by another 1,000 in 2021 and 1,500 in 2023. In addition, 2,500 computers already in operation were switched to the Russian OS.
The workstation migration was completed by the end of 2024. Over the following year, the region also completed the transition to the certified server edition of RED OS and migrated the resources of its regional State Healthcare Information System. As a result, Russian software accounted for 100% of the software installed on healthcare workers' workstations.
For medical staff, this means that familiar workflows now run on a unified technology platform. The region can also develop and upgrade digital services using Russian software, without relying on imported products.
AI Analyzes Medical Images
Alongside the transition to Russian software, the Bryansk Region continued developing an artificial intelligence system for medical image analysis. AI services from Platforma Tret’ye Mneniye (Third Opinion Platform) process fluorography images, mammograms, X-rays and CT scans of the chest and brain.
The algorithms now process around 50,000 imaging studies each month. Their purpose is to help medical professionals spot areas that may indicate pathological changes and draw the physician's attention to them. The technology is an additional image-analysis tool, not a diagnostic system. Its findings are sent to medical information systems, where physicians can review the additional information at their workstations and make the diagnosis themselves.
“The region was one of the first in the country to deploy a system that allows radiologists to see areas on medical images that may indicate pathological changes,” said Maksim Tishchenko, director of the Bryansk Region Medical Information and Analytical Center.
Systems Work Together
The AI services are integrated through the Central Archive of Medical Images (Tsentralny Arkhiv Meditsinskikh Izobrazheniy, TsAMI), which is itself connected to radiology and medical information systems. The algorithm analyzes each image and sends its findings to these systems as machine-readable data. The images then serve as an evidence base for prioritizing examinations and organizing patient referrals.
This approach benefits more than radiologists. The additional information can also help other healthcare professionals involved in examining and treating patients. AI deployment has also expanded the range of users, from laboratory technicians who assess image quality to oncologists, pulmonologists and cardiologists.
“The Bryansk Region uses five different types of medical image analysis and an expanded model for interaction between AI and information systems, built on the LINS LookInside platform and the MED-KOMPLIT medical information system. Closer integration between these systems makes it possible to achieve greater benefits from AI deployment,” said Andrey Povarenkin, director of commercial strategy and business development at Platforma Tret’ye Mneniye.
The Future of Digital Healthcare
The infrastructure now in place creates opportunities to develop additional healthcare IT services based entirely on Russian software. The region can connect new image-analysis algorithms, including those designed to detect cancer and cardiovascular disease, introduce automated prioritization of imaging studies that may indicate serious conditions, and expand remote consultations between district and regional medical centers.
Another promising area is the use of de-identified medical data to train algorithms and assess their performance. All applicable legal requirements for protecting personal information are being observed.
In the future, AI could help physicians do more than analyze medical images. It could also compare imaging results with a patient's medical history and relevant clinical recommendations.
