AI-based referral system aims to curb hospital queues in Armenia

The Unified Information System of Electronic Healthcare (ARMED) is developing an AI-powered tool to reduce hospital queues and enable doctors to provide services remotely, without compromising accuracy or quality.

In some cases, the AI tool would make in-person visits unnecessary.

ARMED CEO Avet Manukyan told Armenpress that the most important current priority is reducing queues, which can arise particularly during the process of issuing referrals for free examinations by family doctors to patients covered by universal insurance.

“For ARMED, the priority task in the near term is to reduce these queues. There is only one way to do this—by avoiding in-person visits. In many cases, this is impossible, because the patient must undergo a physical examination by a doctor in order to clearly assess their health condition and make a well-founded decision about what is happening and which examination can confirm or rule out that suspicion. However, if there are cases in which a doctor can make the same decision with the same quality and accuracy in just 15 minutes without the patient’s physical visit, then we should make that process electronic,” Manukyan explained.

The ARMED executive emphasized that the toolkit, which is currently undergoing limited piloting, can be considered successful if it makes it possible to save time without compromising service quality or harming citizens’ health.

The toolkit planned for implementation with the introduction of artificial intelligence will help doctors save time by enabling them to refer patients for examinations without requiring an in-person visit.

“This will definitely happen. For now, we are simply helping doctors gradually adapt to what is coming, so that in cases where they are able to do so, they can immediately refer citizens for examinations online, without requiring a physical visit. In other words, we aim to reduce doctor–citizen interaction without any loss in quality,” the ARMED CEO said.

According to him, during the limited pilot phase as well as the preparatory training sessions, feedback from medical staff and the issues they have raised regarding this queue-management toolkit are being taken into account.