Rudnev S.G.1,2, Nikolaev D.V.1,3, Korostylev K.A.1,3, Starunova O.A.1,3, Schelykalina S.P.1,3, Eryukova T.A.1,3, Kolesnikov V.A.1,3, Starodubov V.I.1
1Federal Research Institute for Health Organization and Informatics of Ministry of Health of the Russian Federation, Moscow
2Institute of Numerical Mathematics of the Russian Academy of Sciences, Moscow
3“Medas” Scientific Research Centre, Moscow
4Pirogov Russian National Research Medical University, Moscow
Contacts: Sergey G. Rudnev, e-mail:
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This article was prepared under the framework of the Russian
Science Foundation project ‘Development of methodology for population
screening of physical growth and development, state of health and
nutrition. Assessment of epidemiological risks’ (grant no. 14-15-01085).
Abstract. Significance. The national
network of Health Centers is a complex distributed system that
continuously, since 2010, generates mass data on preventive screening.
Manual analysis of quality and reliability of the data collected in
Health Centers is not possible, while official reporting of Health
Centers may not, in some cases, reflect the real situation. So it is
necessary to develop automated algorithms for quality control and
enhancement of reliability of preventive screening data.
The purpose of the study was to implement elements of
the big data technology for analyzing results of preventive screening in
Health Centers exemplified by the bioimpedance measurement data,
retrospectively evaluate quality and reliability of data, and explore
their applicability for epidemiological monitoring.
Materials and methods. Bioimpedance data from the
Federal Information Resource of Health Centers database was combined
with the submitted data of bioimpedance measurements according to the
letter by the Ministry of Health of the Russian Federation
#14-1/10/2-3200 as of October 24, 2012, as well as with the submitted
data according to the letter by the Federal Research Institute for
Health Organization and Informatics of the Russian Health Ministry
#7-5/434 as of July 2, 2015. The initial number of records in the
bioimpedance database was 2.35 million. The data were obtained from 320
Health Centers in 62 Federal Subjects and eight Federal Districts of the
Russian Federation.
Results. In half of the Health Centers the quality of
bioimpedance data was 93.5% or higher. However, the proportion of
incorrect data grew steadily reaching 28.1% in 2014. The incorrect data
consisted mainly of frauds (50.6%) and measurement errors (48.5%). The
number of records in the database after removal of incorrect data and
repeated measurements equaled to 1.64 million. Based on calculated
parameters of the distributions of body mass index using the software
package GAMLSS, the prevalence of overweight, obesity and wasting in the
study group was estimated among males according to the WHO criteria.
The age-standardized obesity prevalence in males was 11.0% at the age of
5-17 years, and 17.7% at the age of 18-85 years.
Discussion. The use of big data technology
allowed to evaluate quality of data and identify incorrect data of
bioimpedance measurements. This offers an opportunity for taking
managerial decisions to correct the identified violations. Results of
the comparison with independent anthropometric data show
representativeness of the Health Centers’ data for children and
adolescents.
Conclusions. 1) Based on bioimpedance data, our
mass data analysis showed that quality and accuracy of the raw data on
preventive screening in Health Centers was gradually decreasing. This
suggests ineffectiveness of control measures.
2) Effective quality management of Health Centers’ activities is possible through the use of big data technology.
3) Data of the Federal Information Resource of Health Centers may be
suitable for epidemiological monitoring upon application of the
selection criteria.
Keywords. Health Centers; Federal Information Resource
of Health Centers; preventive screening; big data; frauds detection and
removal; data compression; data standardization.
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