Pioneering research began at the Semmelweis Emergency Clinic in cooperation with XUND. Developments here could radically change the future of hospital care, as the emergency clinic is often patients’ first point of contact with the healthcare system.
The research was conducted with the participation of patients
In the research, which began in October and lasted more than two years, and which included patients coming to the clinic with a wide range of problems, medical history, symptoms provided by patients and other health data were used together.
They are testing the extent to which machine learning-based predictive models can improve the quality of healthcare.
Among other things, the study will test AI-assisted medical history assessment, the need for certain diagnostic tests, and the effectiveness of predicting return visits.
This collaboration is groundbreaking because there has never been an opportunity to use an AI-based system in the emergency department as a digital admission portal and thus attempt to map the subsequent patient journey, reducing the burden on the care system and waiting time.
Emergency departments are overcrowded
Patients who present to the emergency department with non-severe or mild health problems are often discharged after a long waiting period and referred to a general practitioner or outpatient specialist.
In the future, it would be desirable to identify these patients as early as possible and thus direct them immediately to a place of care with a level of care appropriate to their condition. Therefore, tools that support rapid and accurate assessment of patients without the need for additional human resources are extremely important
– said Csaba Varga, Director of the Emergency Medical Clinic and Associate Professor at the University.
AI-powered medical history analysis in the emergency department is still new, and the systems tested so far have not proven effective. This is where XUND steps in to help patients interpret their symptoms and find the right level of care.
– Share Tamas Petrovic, Co-Founder and Managing Director of XUND. He added that their goal is to reduce the burden on emergency workers and help patients get better and faster care.
Artificial intelligence assesses the patient’s condition instantly
After the initial risk analysis (triage), patients waiting in the emergency department fill out a 2-minute digital questionnaire on a tablet on a voluntary basis. With the help of the self-developed XUND algorithm, it instantly and automatically assesses the patient’s condition based on symptoms, compared to hundreds of possible diagnoses, so that each query is personalized.
In the future, the use of such an application may enable complete data-driven management of patients within the entire healthcare system, which may contribute to optimal use of scarce resources and increased patient and medical staff satisfaction.
– said Zoltan Tarabo, Co-Founder and Medical Director of XUND.
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