2015 № 1 Information and analytical module of long-term medical surveillance of the patient with coronary atherosclerosis.
We propose a model of software «Information-analytical module for long-term dispensary observation of patients with coronary atherosclerosis,» which allows one to store and retrieval of clinical and statistical information about patients with coronary atherosclerosis, consisting at a dispensary in their long-term monitoring in primary health care. Lists the prototypes created by the program, objectives and tools to help implement the project describes the features, advantages, sections and modules developed software.
2016 № 3 Information support for the provision of high-quality medical care by using medical information systems
Medical information systems are an effective tool for organization of providing quality medical care by providing medical worker with timely and qualified information support. One of the mechanisms of such support is the electronic health records (EHR), the structure of which is based on the standards of medical care and clinical recommendations. The data accumulated in EHR, allow to organize the control process online, to enhance and to complement traditional methods of examination of quality of medical care.
2017 № 1 On the Criteria for evaluating the level of function execution «maintenance of the electronic medical Records of patient».
Describes the main stages of implementing electronic health records (EHR) of a patient in a medical facility and corresponding models of access and organization of primary medicaling documents of different categories of health workers. Reviewed the indicators and criteria used to assess the level of implementation of EHR.
2018 № ips Digital Healthcare Ecosystem
The paper deals with the problem of increasing the efficiency of the medical care system through the creation of a digital ecosystem based on specialized IT products.
2019 № 3 Development of algorithm for searching of clinically homogeneous patients from semistructured text data of oncological electronic health record
The growth in the number of patients with malignant neoplasms in Russia significantly increases the load on a specialized network of oncological institutions and oncologists. It is most likely that this trend will continue in the coming years. One of the ways to improve the efficiency of medical activity is the extraction knowledge from medical data arrays, using modern data analysis methods, by clustering patients into groups of clinically homogeneous (similar) patients from electronic health records. The aim of the study is to develop an algorithm for finding clinically homogeneous patients according to the electronic health records of the oncological dispensary, with follow-up possibility of integration into the clinical decision support system (CDSS). The use of such CDSS in practical medicine and in the field of medical education will allow us to analyze both semistructured and unstructured arrays of information, which will require further implementation and improvement of information systems at all levels of
medical care. The homogeneity of patients was determined by machine learning by cosine distance in the space of vector representations of electronic health records. An experiment on 20 randomly selected electronic health records of patients of Krasnodar Regional Oncological Dispensary showed high efficiency of the algorithm in creating clusters of clinically homogeneous patients.