AI assistant in Moscow region medicine: over a million prescriptions have passed digital control
An AI-powered digital assistant, deployed in the Moscow region's healthcare system in February 2026, has checked over one million medical prescriptions in six months. This is a significant milestone that demonstrates how algorithms are gradually becoming an integral part of clinical practice.
The tool operates in two modes — during in-person patient visits and during telemedicine consultations when a current prescription needs to be extended or adjusted. In automatic mode, the system evaluates each prescription against 15 parameters, including drug compatibility, patient age and gender, as well as potential risks of overdose or exceeding recommended treatment durations.
How the check works
The mechanism is triggered at the moment a prescription is issued. The algorithm cross-references patient data with the prescribed medications and flags potential issues before the person receives the drug. This allows the doctor to adjust the treatment plan on the spot, reducing the likelihood of medical errors.
It is important to emphasize: the technology does not replace the specialist, but merely complements their work. The final decision on therapy always remains with the doctor. The system acts as a "second opinion" that helps avoid typical errors related to the human factor — especially under high workloads on medical staff.
AI in Russian medicine: the trend is gaining momentum
The Moscow region is not the only area where neural networks are being introduced into healthcare. Similar projects are developing both at the federal level and in individual regions. In Moscow, 200 medical AI services have been tested over six years, 67 of which are currently operating in hospitals. More than 2,000 clinics from 75 regions have connected to the city platform "MosMedAI," which provides access to radiology diagnostic algorithms based on imaging.
Yandex is also eyeing this market. At the end of July, the company registered LLC "Yandex Med" to develop medical software. The digital assistant transcribes conversations between doctors and patients, searches for relevant data in the knowledge base, and prepares a brief summary from the medical history.
The use of neural networks extends beyond clinics. With their help, complete genomes of bacteriophages — viruses that infect bacteria — were assembled for the first time. According to the data obtained, 16 of these samples proved viable in the laboratory.
My take: this case is a vivid example of how AI is transitioning from experimental technology to a category of essential tools for improving the quality and safety of medical services. The implementation of such assistants not only reduces risks for patients but also creates vast arrays of structured data that could be used in the future for deeper analysis of drug efficacy and therapeutic protocols. This is a strategically important step for the entire industry.