• 2020 № 2 Telemedicine and COVID-19: quality of patient-initiated teleconsultations in case of acute respiratory disease

    There is a global increase in demand for direct-to-patient telemedicine consultations due to COVID-19 pandemic. We made a quality assessment of the patient-initiated consultations in case of acute respiratory viral infection symptoms (COVID-19). There are 20 teleconsultations of 2 simulated patients in 10 the most popular telehealth services. An incomplete history of the disease was recorded in 50.0% of cases, incomplete allergy anamnesis – in 60.0%, and epidemiology anamnesis – in 35.0%. Information on chronic illnesses (critical for COVID-19 suspected situations) is fully collected only in 50.0% of cases. Due to defects in the history taking the target diagnostic concept was achieved in 30.0% of teleconsultations, target actions were recommended in only 35.0%. Telemedicine services did not provide continuity of medical care. In 60.0% of cases, medications were prescribed, including injectable antibacterial agents, which completely contradicts not only the legislation, but also the accepted international methods and practices of distance counseling. The quality of the direct-to-patient telemedicine services remains unsatisfactory. There is no effective quality control and quality assurance systems.

    Authors: Morozov S. P. [7] Vladzymyrskyy A. V. [7] Simenyura S. S. [2]

    Tags: acute  respiratory  disease1 antibiotics1 covid-194 telemedicine17 telemedicine technologies5

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  • It and economics of health care
  • 2020 № S5 Information exchange system for the implementation of special social payments to medical workers associated with the treatment of Covid-19 coronavirus infection

    The government went to provide medical and other workers engaged in the treatment OF covid‑19 coronavirus
    infection with a fairly large set of benefits, guarantees and compensation. Among the key and most financially intensive of them were incentive payments, which were replaced with special social payments from November 1, 2020.
    At the same time, payments will now be made by the social insurance Fund. The implementation of such a scheme has caused the urgent need to create a complex system of information exchange, in which a large number of subjects participate, large amounts of information are verified and processed.
    This article analyzes the emerging system of information exchange, as well as identifying possible risks and threats.

    Authors: Kadyrov F. N. [4] Chililov A. M. [4]

    Tags: coronavirus infection1 covid-194 information exchange1 information resource1 special social payments1 state support for medical workers1

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  • Decision support systems
  • 2020 № 4 Algorithm for forming a suspicion of a new coronavirus infection based on the analysis of symptoms for use in medical decision support systems

    The course of the COVID‑19 pandemic imposes a significant burden on healthcare systems, including on primary care,
    when it is necessary to correctly suspect and determine further management. The symptoms non-specificity and the manifestations versatility of the COVID‑19 impose difficulties in identifying suspicions. To improve the definition of COVID‑19 symptom checkers and medical decision support systems (MDSS) can potentially be useful. They can give recommendations for determining the disease management.
    The scientific analysis shows the manifestations versatility and the occurrence frequency COVID‑19. We structured the manifestations by occurrence frequency, classified them as “large” and “small”. The rules for their interaction were determined to calculate the level of suspicion for COVID‑19. Recommendations on patient management tactics were developed for each level of suspicion. NLP models were trained to identify the symptoms of COVID‑19 in the unstructured texts of electronic health records. The accuracy of the models on the F-measure metric ranged from 84.6% to 96.0%. Thus, a COVID‑19 prediction method was developed, which can be used in symptom checkers and MDSS to help doctors determine COVID‑19 and support tactical actions.

    Authors: Gavrilov D. V. [2] Serova L. M. [2] Kirilkina A. V. [1]

    Tags: clinical decision support systems2 covid-194 covid‑19 suspicion algorithm1 machine learning7 symptom detection1

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  • Artificial intelligence in health care
  • 2020 № 4 Predictive analytics technologies in the management of the COVID‑19 pandemic

    Recently, a new coronavirus infection, or COVID‑19, caused by the pathogen SARS-CoV‑2, has been continuing to
    spread around the world rapidly. According to the World Health Organization (WHO), which declared this outbreak a pandemic, COVID‑19 is a serious public health problem of international concern. Due to the lack of proven effective treatment and vaccination against COVID‑19, precautions are considered by WHO to be strategic goals and a primary response to the pandemic. It is recommended that country guidelines adopt national health care programs aimed at assessing and reducing the risk of infection spread. Predictive analytics have begun to be actively used to compile population and personal forecasts of the progression of morbidity, mortality, assess the severity of the course of the disease, etc. This article provides an overview of available developments and publications on the use of predictive analytics in the management of COVID‑19 pandemic.

    Authors: Gusev A. V. [8] Novitsky R. E. [3]

    Tags: artificial intelligence10 covid-194 dashboard2 machine learning7 predictive analytics1 software2

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