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.
2018 № 4 Development of an algorithm for automated wavelet analysis of clinical oncology dispensary registry data at the regional level
This article describes the issue of overload of the registry on the example of the state budgetary health care institution clinical oncological dispensary No. 1 of the Ministry of health of the Krasnodar territory. Maintaining a schedule of appointments and appointments to the doctor in electronic form plays a key role in healthcare information systems as the most widespread and socially oriented medical service. The aim of the study is to develop an algorithm for automated wavelet analysis of data on the work of the registry. To achieve this goal, there are used the methods of wavelet analysis of information that have been applied in practice and can be reused in other medical institutions. It is possible to create an optimal schedule of work of registrars and as a result reduce the waiting time of patients at the reception, by automating the process of analysis of data on patient’s appointments that contained in the healthcare information system. The reduction in waiting time should increase patient satisfaction and improve the overall impression of the health facility. For each institution, the workload schedule of the registry will be different and may change over time. It follows that the analysis and optimization of work schedules should be carried out regularly and automatically.