CONTENT OF THE ISSUE
Clinical Research Data Management: Experience of the N. N. Burdenko NMRC of Neurosurgery
Data management is a key process in modern clinical researches, which aims to ensure the unambiguity, completeness,
security, and reliability of the collection and storage of information. Since 2017, in the Federal State Autonomous Institution
Scientific Research Center of Neurosurgery named after ac. N. N. Burdenko of the Ministry of Health of Russia (NMRC of Neurosurgery) the clinical data management process was modified and a special management information system was introduced
into the routine research practice.
This article opens a series of articles on clinical research management at the NMRC of Neurosurgery.
This work was supported by RFBR grant № 16-29-12880.
Web-portal for monitoring patients after allogeneic hematopoietic stem cells transplantation
Prolonged monitoring of the patients health is the important issue in the treatment of patients after allogeneic hematopoietic
stem cell transplantation (allo-HSCT) and is extremely important for the transplant team. The basis of this awareness is the
aggregation, systematization and analysis of data about what happens to the patient outside the hospital, namely those parameters
that are clinically important for physicians. The basis of the future system of patients’ monitoring is a self-monitoring portal for
patients after allo-HSCT. These arrangements will reduce the time of patients’ survey on the following examination and potentially
lead to an increase in overall survival due to timely hospitalization, which in turn will increase the effectiveness of medical care.
Modern methods of analysis and forecasting of time series and use in medicine
The article is a review of Russian and foreign scientific publications related to the use of methods of analysis and
forecasting of time series in medicine. 112 major publications over the past 5 years, located on the Internet resources e-library
and PubMed, are considered. Examples of the application of such methods as exponential smoothing, regression analysis,
the ARIMA method and their variants for time series analysis are shown. Various approaches to mathematical modeling of
the time series are presented. The results of the article can be used to select a method of analysis and forecasting time series
depending on the tasks.
Life cycle of decision support systems as medical technologies
Decision support systems (DSS) in medicine can be classified into reference and intellectual, and the latter, in turn, into
modeling and imitating human reasoning. Modeling systems are based on formalized expert knowledge, and imitating ones are
based on models built by various multidimensional data analysis methods. DSS should be considered as medical technologies,
therefore, after their development, assessing of analytical (technical) and clinical validity should follow, regardless of current
national regulatory documents. Clinical validation have to be based on principles of evidence based medicine and demonstrate
superiority, non-inferiority or equivalence to routine practice. Then a clinical and economic analysis can be carried out in order
to justify the economic feasibility of DSS, and later health technology assessment can be performed.
Automation of the activities of the multidisciplinary rehabilitation team through the ICF WIZARD software package
The article discusses the possibilities of forming a rehabilitation diagnosis using the categories of the directory codes
of the International Classification of Functioning, Disability and Health (ICF) using the ICF WIZARD information system. The possibilities of using the ICF WIZARD information system and its scope are also considered.
Decision support services for the diagnosis and treatment of diseases and their practical application on the example of ckd 5d
The article clarifies the concept of DSS, shows the trend of development of new services in medicine. The article
describes the developed DSS‑service for issuing recommendations for the treatment and diagnostic process on the example of
complications in patients on permanent hemodialysis, in particular, correction of anemia. The information and logical architecture
of the service, the rating and trigger models used, the underlying knowledge base, and their relationship are described.
Based on the theory of decision-making, the principle of making recommendations is shown. Examples of integration of the
service with various information systems and other data sources are given. The analysis of the results of the implementation
of the DSS service for the correction of anemia in patients with CKD5D in the Nephrology and hemodialysis departments of
the medical clinical company Nefrosovet in integration with the information and analytical system for managing treatment and
diagnostic processes Maximus.
The quality of primary direct-to-consumer telemedicine consultations (by results of testing telemedicine services)
The adoption of a number of special regulatory documents has significantly expanded the possibilities of using
telemedicine technologies in the Russian Federation. A significant number of services have appeared on the market, offering
direct-to-consumer and patient initiated telemedicine consultations. The explosive growth in the number of such services requires
a careful study of the telemedicine interaction quality. The research objective is to assess the quality of remote interaction of
participants in primary telemedicine consultations with simulated patients. For testing, we used descriptions of simulated patients
basing on real records of patients from the therapeutic department of the municipal clinical hospital. For objectification and
analysis of the telemedicine interaction process (collection of complaints, questioning, recommendations, etc.) a checklist has been compiled. Initially, the study included such services as “Yandex. Health”, “MMT (OnlineDoctor)”, “TelemedHelp”, “Doctor at work”,
“DoctorSmart”, “DocDoc”; then, for technical reasons, 2 services were excluded from the study. Two simulated patients were sent
to 4 services; as results, 8 primary teleconsultations were made. In all cases, incorrect, incomplete collection of anamnesis data
was recorded. Target diagnosis (in the form of diagnostic concept) was achieved in 25% of cases, and target prescriptions were
made in 50% of cases. A personal consultation and additional examinations were recommended in 75% of teleconsultations.
There was no continuity, drugs were somehow prescribed in 62.5% of cases. As results, an urgent development of methods of
internal and departmental quality control of medical care provided with the use of telemedicine technologies is required.
Methods of Modelling and Prediction of Surgery Duration
Based on the analysis of foreign publications, a comparative characteristic of methods and models of prediction
of surgical operations duration was carried out. The importance of estimating the accuracy of prediction the duration of
operations for effective planning of the use of operating rooms and high-tech equipment is shown. Analyzed statistical and
regression methods to predict the duration of operations, and the use of artificial neural networks to estimate the duration
of an operation. Mathematical expressions are given, allowing to estimate duration of operation as a whole, as well as data
on prediction errors.
Medical information systems
Artificial intelligence in health care
Decision support systems
Mathematical methods of forecasting