Prediction of temporary disability due to of circulatory system diseases in housing and communal services employees

Abstract

Aim. To develop a prognostic model of incidence of temporary (short-term) disability due to cardiovascular diseases in a housing and communal services employees using the example of the State Unitary Enterprise (SUE) “Vodokanal of St. Petersburg”.

Methods. The study included 4634 people, observed in the departmental outpatient clinic of SUE “Vodokanal of St. Petersburg”, between 2015 and 2017 years. We calculated extensive indicators determining the disease patterns and intensive indicators characterizing the prevalence of the pathological process in the study of morbidity by the findings of periodic health examinations and incidence of short-term disability. The incidence of short-term disability was predicted by using the method of sequential analysis A. Wald modified by E.V. Gubler and the neural network.

Results. We found that based on the operational and statistical data of the medical and sanitary unit, using a neural network, relying on linear and nonlinear dependence of comorbidity, in particular, respiratory diseases, it is possible to predict (in 92.4% of cases) the incidence of temporary disability due to cardiovascular diseases in employees of the housing and communal services SUE “Vodokanal of St. Petersburg”. The high sensitivity (97.7%) and specificity (90.7%) of the method allows it to predict the need for treatment and prophylaxis measures in the contingent attached to the medical and sanitary unit.

Conclusion. The developed model allows to determine the main directions of preventive work to reduce the incidence of circulatory system diseases with temporary disability: prevention of high blood pressure and respiratory diseases.

Keywords

disease prediction / neural network / temporary (short-term) disability / cardiovascular system

RIGHTS & PERMISSIONS

Bendyuk G.Y., Grishina N.K., Dokhov M.A., Sidorov A.A.