Kazan medical journalKazan medical journal0368-48142587-9359Eco-Vector231910.17816/KMJ2319Research ArticleModelling the health condition of medical workers using a multivariate statistical analysisErmolinaT Ataniaermolina@yandex.ruShilovskayaN A-MartynovaN A-KalininA G-KrasilnikovS V-Northern (Arctic) Federal University, Arkhangelsk, RussiaFirst City Clinical Hospital named after E.E. Volosevich, Arkhangelsk, Russia1504201293231832128032016Copyright © 2012, Ermolina T.A., Shilovskaya N.A., Martynova N.A., Kalinin A.G., Krasilnikov S.V.2012Aim. To identify the most important differential diagnostic criteria of the immunological parameters with the help of discriminant analysis in order to assess the level of health of medical personnel of an oncology dispensary. Methods. With the aim to model the generalized indicators of the health level, evaluated was the health of physicians and nurses, and a cross-sectional study of the immune status of health workers of the oncology dispensary was conducted. Firstly the content of T- and B-lymphocytes with different phenotypes was studied. The model «level of health of medical workers» was built on the basis of a sample of 96 observations (the group of medical personnel, the work of whom is associated with emitting apparatuses). The control group consisted of 98 people of the same medical institution, who are mainly office staff. Results. The health status can be described using macro parameters. At the same time under the state of health in the most general sense a specific value of the hierarchically interrelated parameters of the additive model of health is understood. Carrying out a differential diagnosis based on the assessment of clinical and laboratory data, functional parameters and their significance makes it possible to predict the level of health of medical workers. Conclusion. Informative features for differential diagnosis are the work at the department of radiology, working in surgical departments, working with the emitting apparatuses, secondary professional or higher professional education of the worker, the age of the employee, gender of the employee and the employee’s length of service for the department; the most informative features - work at the department of radiology (F=22.292), at the surgical departments (F=7.890), as well as work with the emitting apparatuses (F=3.985).medical workersmorbiditymodellingpredictinglevel of healthdiscriminant analysisмедицинские работникизаболеваемостьмоделированиепрогнозированиеуровень здоровьядискриминантный анализ[Токмачев М.С. Здоровье населения региона: модели и управление // Проблем. управл. - 2010. - № 6. - С. 45-52.][Фаткуллина И.Б., Протопопова Н.В., Михалевич И.М. Дискриминантный анализ как метод проведения дифференциальной диагностики артериальной гипертензии при беременности // Вестн. нов. мед. технол. - 2011. - Т. XVIII, №1. - С. 134-135.]