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Issue 4 (194), article 4

DOI:https://doi.org/10.15407/kvt194.04.061

Kibern. vyčisl. teh., 2018, Issue 4 (194), pp.

Kozak L.M., DSc (Biology), Senior Researcher,
Leading Researcher of the Medical Information Systems Department
e-mail: lmkozak52@gmail.com

Kovalenko A.S., DSc (Medicine), Professor,
Head of the Medical Information Systems Department
e-mail: askov49@gmail.com

Krivova O.A., Researcher of the Medical Information Systems Department
e-mail: ol.kryvova@gmail.com

Romanyuk O.A., Junior Researcher of Medical Information Systems Department
e-mail: ksnksn7@gmail.com

International Research and Training Center for Information Technologies
and Systems of the National Academy of Sciences of Ukraine
and Ministry of Education and Science of Ukraine,
Glushkov ave., 40, Kiev, 03187, Ukraine

DIGITAL TRANSFORMATION IN MEDICINE: FROM FORMALIZED MEDICAL DOCUMENTS TO INFORMATION TECHNOLOGIES OF DIGITAL MEDICINE

Introduction. According to the Concept of Ukraine`s Digital Economy and Society Development in 2018-2020, the key components of “digitalization” are the development of digital infrastructure — broadband Internet throughout Ukraine, and the promotion of digital transformations in various sectors of the economy and society, including medicine.

The purpose of the paper is to analyze the stages of digital transformation in medicine and the results of authors and their colleagues of the MIS department for the development of information technologies of digital medicine.

Results. A generated model of digital transformation in medicine is presented and several main stages of this transformation are highlighted: І — digital transformation of primary medical information; ІІ — development of support systems for the diagnostic and treatment process; ІІІ — development of technologies and systems for supporting the physicians` activities with digital information; IV — mobile medicine; V — the digital medicine globalization. The method of determining the markers of the functional state of the cardiovascular system based on mathematical models of forecasting and classification with the use of Data Mining is proposed. The method allows detecting and determining the prognostic values of ECG parameters of the CVS functional state for different groups of patients. The developed IT for supporting the processes of receiving, transmitting and storing digital medical images is aimed at ensuring the effective operation of a physician with digital information from various sources: functional diagnostic complexes, digital medical data storage and images using Picture Archiving and Communication Systems (PACS) and cloud technologies . The proposed telemedicine systems theory including the formulated principles of organizing these systems, criteria and methods for analyzing digital medical data has been implemented for elaborating and functioning the Telemedicine Centre. It enables to cover the population in more than 20 Ukraine`s regions with qualified medical assistance.

Conclusions. The digital transformation in medicine like any new process takes place with a gradual complication of tasks, methods and means of their implementation: from formalization of primary medical information to improvement of methods of its analysis, transfer and storage to improve the quality of medical care for patients at any point of the world.

Keywords: digital transformation in medicine, formalized medical records, Data Mining, IT for assessing human state and physiological systems` state, telemedicine, m-medicine.

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REFERENCES

1. About the conceptualization of the concept of the development of the digital economy of Ukraine and 2018–2020 on the basis of the plan set for the project: Disposition of the Government of Ukraine. URL: http://www.me.gov.ua/Documents/ (Last accessed: 06.07.18) (in Ukranian).

2. The Nine Elements of Digital Transformation. URL:  https://sloanreview.mit.edu/article/the-nine-elements-of-digital-transformation/?social_token=d65abc6db70ba459408562abb8de32bc &utm_source= facebook&utm_medium=social&mmmmmt (Last accessed: 27.06.18)

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8. Kozak L.M., Lukashenko M.V. The use of information models and integral assessments of the functional state of students for the formation of programs of psychological support. Integrative anthropology. 2008. №2 (12). P. 51–57 (in Russian).

9. Kozak L.M., Lukashenko M.V. Monitoring and correction students ’functional state. Kibernetika i vyčislitel`naâ tehnika. 2014. Issue 176. P. 74–84.

10. M.L. Kochina, L.M. Kozak, A.S. Yevtushenko Analysis of changes in the factor structures of indicators of the functional state of a person with different types of visual load. Bulletin of problems of biology and medicine. 2013, Iss. 1, Vol. 1 (98), pp. 41–45 (in Russian).

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13. Rogozinskaya N.S., Kozak L.M. Complex indicators for the analysis of causal mortality of the population. Clinical informatics and telemedicine. 2013. Vol. 9, Iss. 10. P. 108–116 (in Russian).

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15. Krivova O.A., Kozak L.M. Comprehensive assessment of regional demographic devel-opment. Kibernetika i vyčislitel`naâ tehnika. Issue 182. 2015. P. 70–84 (in Russian).

16. Krivova, OA, Tchaikovsky, I.A., Kalnish, VV, Kozak, L.M. Vidbіr informative shows the variability of the rhythm of the heart – the markers of the reaction to his stimulation. Medical informatics and engineering. 2016. No. 2. pp. 37–44 (in Russian).

17. Tchaikovsky I.A. The concept of multilateral analysis of the electrocardiogram using portable electrocardiographs as part of a preventive medical examination. Preventive medicine. 2014. No. 17 (2). P. 42–48 (in Russian).

18. Sposib Universalnoyi Balnoyi Otcinky EKG: Budnik M.M., Staryska G.A., Tchaikovsky І.A. Pat. 104827 Ukraine, IPC: A61B 5/0402, A61B 5/0205; declare 07.13.2015; publ. 02/25/2016, Bul. No. 4.

19. EN ISO 12052: 2011. Health informatics. Digital work, including workflow and data management URL: http://iso.org. (Last accessed: 23.01.18)

20. Romanyuk O. A., Kovalenko A.S., Kozak L.M. Information support interoperability of instrumental studies and long-term storage of digital medical imaging in health care sys-tem. Kibernetika i vyčislitel`naâ tehnika. 2016. Iss. 184. P. 56–71 (in Russian).

21. Kovalenko A.S., Kozak L.M., Romanyuk O.A. Information technology of digital medi-cine. Kibernetika i vyčislitel`naâ tehnika. 2017. №1(187). P.67–79. (in Russian).

22. Kovalenko A.S., Kozak L.M., Ostashko V.G. Telemedicine — the development of a sin-gle medical information space. Upravlâûŝie sistemy i mašiny. 2005. № 3. P. 86–92 (in Russian).

23. Gritsenko V.I., Kozak L.M., Kovalenko A.S., Pezenzali A.A., Rogozinskaya N.S., Ostashko V.G. Medical information systems as elements of a unified medical informa-tion space. Kibernetika i vyčislitel`naâ tehnika, 2013, Iss. 174. P 30-46 (in Russian).

24. Kovalenko O.S., Kozak L.M., Romaniuk O.O., Maresova T.A., Nenasheva L.V., Fyniak G.I. Mobile applications in the structure of modern medical information systems. Upravlâûŝie sistemy i mašiny, 2018, №4. P. 57-69.

 

Received 29.08.2018

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Issue 1 (187), article 5

DOI: https://doi.org/10.15407/kvt187.01.067

Kibern. vyčisl. teh., 2017, Issue 1 (187), pp.67-80

Kovalenko A.S., Dr Medicine, Prof., Head of Department of Medical Information Systems
e-mail: askov49@gmail.com
Kozak L.M., Dr Biology, Leading Researcher of Department of Medical Information Systems
e-mail: lmkozak52@gmail.com
Romanyuk O.A., Junior Researcher of Department of Medical Information Systems
e-mail: ksnksn7@gmail.com

International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and Ministry of Education and Science of Ukraine,
av. Acad. Glushkova, 40, Kiev, 03680, Ukraine

INFORMATION TECHNOLOGY FOR DIGITAL MEDICINE

Introduction. The need of health care institutions in the repeated use of digital medical images by different specialists during patient care and long-term storage for the analysis of diagnostic information determines the relevance of this work. The need for means and methods of storage of digital medical data with their subsequent processing and analysis, as well as on mobile devices for the collection, digital data processing and exchange increase.

The purpose of the article is to analyze the experience of creating medical information systems, the development of information technology support the storage and processing of digital medical information and the further development of information technology for digital medicine.

Results. Employees of the department of medical information systems for more than 20 years of activities of the International Research and Training Centre for Information Technologies and Systems NAS and MES of Ukraine solved the problem of constructing the medical information systems and information diagnostics technologies with the use of electronic medical records, methods and means of the mathematical analysis of medical data. The developed technology support for storing and processing digital medical information combines into a single functional network the medical information system, instrumental diagnostic systems and a system of conservation and archiving digital medical images. PACS and cloud technologies was used for long-term storage of digital medical images.

Conclusion. Organization of long-term storage of digital medical images obtained from the diagnostic systems in health care facilities, and the ability to use this information by doctors at their workplace in the current diagnostic and treatment process was provided by using the developed information technology support for storing and processing digital medical information.

Keywords: medical information system, information technology, digital medical imaging, long-term storage.

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REFERENCE

  1. Amosov N.M. Voices of Times. Kiev, Oranta-Press, 1999. 500 p. (in Russian).
  2. Medical Information System. Kiev: Nauk. Dumka, 1975. 508 p. (in Russian).
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  6. Budnyk M., Kovalenko A., Berezovska T., Kozlovsky V. Finding of ROI Intervals at Cardiocycle for CAD Study in Magnetocardiography. International Journal of Bioelectromagnetism. 2003. Vol. 5, N 1. P. 107–108.
  7. Kozak L.M., Lukashenko M.V. Monitoring and correction students’ functional state by the information technology tools. Cybernetics and Computer Engineering. 176. 2014. P. 74–84.
  8. Yevtushenko A.S., Kozak L.M., Cochina M.L., Yaworskij A.V. The results of the use of factor models for the evaluation of human functional state when the visual work. Ukrainskiy zhurnal meditsini, biologii ta sportu. 2015. № 2 (2). P. 70–74 (in Russian).
  9. Rogozinskaya N.S., Kozak L.M. Dataware technologies automated health monitoring. Kibernetika i sistemnyy analiz. 2013. № 6. P. 162–173 (in Russian).
  10. Krivova O.A., Kozak L.M. Comprehensive assessment of regional demographic development. Kibernetika i vyčislitelnaâ tehnika. 182. 2015. P. 70–84 (in Russian).
  11. Vasylyk P.V., Kovalenko A.S., Bychkov V.V., Vasilega A.G. The role of environmental factors in the occurrence of bursts of accidents on the roads. Ukraina. Zdorov’ya natsii. 2008. №3–4 (7–8) p. 35–40 (in Russian).
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  13. Provotar A.I. Vasylyk P.V. Model wave and interaction: theoretical and applied aspect. Kiev: Nauk. Dumka. 2014. 296 p. (in Russian).
  14. Kovalenko O.S., Golubchikov N.V., Orlova N.M. Information systems in health and basic requirements for their creation. Management of health care. №1. 2007. P. 42–46 (in Ukrainian).
  15. Litvinov A.A., Kovalenko A.S., Golubchikov M.V. Features of the design of the subsystem “Statistics” hospital information system. Control systems and machine. 2007. №5. P. 61–67 (in Russian).
  16. Pezentsali A.A., Kozak L.M., Kovalenko A.S. Functional model as the basis for management of the project to develop an integrated information system of medical institution. Control systems and machines. 2008. № 4. P. 3–10 (in Russian).
  17. Kovalenko A.S., Kozak L.M., Ostashko V.G. Telemedicine — the development of a single medical information space. Control systems and machines. 2005. № 3. P. 86–92 (in Russian).
  18. Lazorishinets V.V., Slabkiy G.O., Kovalenko O.S et al. Health Informatization of Ukraine and the development of telemedicine. Zhytomyr: Polissya, 2010. 228 p. (in Ukrainian).
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Recieved 27.12.2016

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Issue 185, article 6

DOI:https://doi.org/10.15407/kvt185.03.060

KVT, 2016, Issue 185, pp.60-76

UDC 617.751-057-07

THE ASSESMENT OF CONNECTION STRUCTURE BETWEEN THE FUNCTIONAL INDEXES OF PC OPERATORS DURING THE VISUAL WORK WITH FACTOR MODELS’ USE

Evtushenko A.S.1, Kozak L.M.2, Kochina M.L.3

1Kharkiv Municipal Clinical Hospital №14 named by Prof. L.L. Girshman, Kharkiv, Ukraine

2International Reasearch and Training Center for Information Technologies and Systems of National Academy of Science and Ministry of Science of Ukraine, Kyiv, Ukraine

3Kharkiv Medical Academy of Postgraduate Education, Kharkiv, Ukraine

andrey-eye@yandex.ru , lmkozak52@gmail.com , m_kochina@yahoo.com

Introduction. PC operators’ work is connected to necessity of information large amounts perception from PC display. Such activities require of high attention concentration and particular responsibility for production goals. Arduous visual work of PC operators on close distance results in high psychoemotional stress and exerts an impact on functional state. Severe visual asthenopias in PC operators may be observed on the background of normal values of visual system’s functional indexes that require of such states causes determination for prophylaxis measures development.

The purpose of the article is to evaluate the impact of the visual work at close distance on the structure of relationships between visual system’s indexes and functional state’s indexes.

Methods. 41 PC operators took part in the study. The average age of study subjects was (29,6 ± 4,0) y.o. The functional indexes of visual system were measured in all PC operators before and after visual work. The indexes of functional state were also measured by self-assessment using developed questionnaire. The obtained results processing was performed using descriptive statistics methods, cluster and factor analysis.

Results. On the background of performed research using clustering and factor analysis it was found that younger PC operators with higher visual functions the visual work on close distance results in state similar to spasm of accommodation. The recovery after night rest was worse than in PC operators with low visual functions. Older PC operators have higher quality of recovery after night rest. It may be determined by development of visual fatigue as the result of visual work . The recovery after night rest in case of visual fatigue is better than in case of accommodation spasm.

Conclusion. Visual work on close distance results in configuration change of connection between indexes of visual system that support visual perception. The peculiarities of these changes depend on visual system’s indexes. The results of PC operators functional state’s self-assessment using the questionnaire developed by us had shown that in PC operators with low functional possibilities the common and visual complaints rate was certainly lower than in operators with high functional possibilities.

Keywords: factor models, visual system, functional state, PC operator work.

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References:

1 Danilichev V.F. Sovremennaya oftal’mologiya: rukovodstvo. Izd. Dom “Piter”, 2009, 684p.

2 Dyadina U.V., Rozenblyum YU.Z. Prichiny i mekhanizmy astenopii. Vestnik optometrii, 2003,Vol.1, No3, pp. 26–28.

3 Yemel’yanov G.A. Sostoyaniye akkomodatsii kak indikator sindroma khronicheskoy ustalosti u patsiyentov zritel’no-napryazhennogo truda. Kataraktal’naya i refraktsionnaya khirurgiya, 2013, No1, pp. 23–25.

4 Yemel’yanov G.A., Shchukin S.YU. Sub”yektivnyye narusheniya akkomodatsionno-refraktsionnoy sistemy glaza u cheloveka-operatora zritel’no-napryazhennogo truda.Voyenno-meditsinskiy zhurnal, 2012, Vol.133, No 2, pp.60–62.

5 Yemel’yanov G.A., Gusev YU.A., Kapkova S.G. Dinamika ob”yektivnykh pokazateley akkomodatsii u lits bez patologii organa zreniya v protsesse zritel’no-napryazhennogo truda.Innovatsionnyye tekhnologii v oftal’mologichesko y praktike regionov, Astrakhan’, 2012, pp. 62–63.

6 Kal’nishV.V., Yena A.I. Sovremennoye sostoyaniye professional’nogo psikhofiziologicheskogo otbora v Ukraine. Meditsina truda i promyshlennaya ekologiya, 2006, No 3, pp. 12–17.

7 Kochina M.L., Kozak L.M., Yevtushenko A.S. Analiz izmeneniya faktornykh strukturpokazateley funktsional’nogo sostoyaniya cheloveka pri raznykh vidakh zritel’noy nagruzki. Visnik problem biologii i meditsini, 2013, Vol. 1, No1(98), pp. 41–45.

8 Ovechkin I.G. et.al. Akkomodatsionnyye narusheniya u lits zritel’no-napryazhennogo truda s yavleniyami psikhologicheskoy dezadaptatsii. Rossiyskiy oftal’mologicheskiy zhurnal, 2014, No1, pp.39–41.

9 Ovechkin I.G., Ragimova N.R. Issledovaniye dinamiki funktsional’nogo sostoyaniya sensornogo otdela zritel’nogo analizatora v protsesse professional’noy deyatel’nosti na personal’nom komp’yutere. Oftal’mologiya, 2010, Vol.7, No4, pp. 32–35.

10 Ovechkin I.G. et. al. Primeneniye funktsional’noy korrektsii organa zreniya patsiyentam-operatoram zritel’nogo profilya s pozitsiy sovremennykh trebovaniy k meditsinskoy reabilitatsii. Rossiyskiy oftal’mologicheskiy zhurnal, 2015, Vol.8, No1, pp. 90–97.

11 Yevtushenko A.S., Kozak L.M., Kochina M.l. et.al. Rezul’taty otsenki funktsional’nogo sostoyaniya cheloveka pri zritel’nom trude. Svit meditsini ta biologii, 2015, No 2, pp. 39–44.

12 Rozenblyum YU.Z., Kornyushina T.A., Feygin A.A. Professional’naya oftal’mopatiya. Meditsina truda i promyshlennaya ekologiya, 1995, No4, pp. 14–16.

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15 Shapovalov S.L., Milyavskaya T.I., Ignat’yev S.A. Akkomodatsiya glaza i yeye narusheniya. Izd-vo: MiK, 2012, 188 p.

16 Shapovalov S.L., Aleksandrov A.S. Materialy k probleme zritel’nogo utomleniya u operatorov videodispleynykh terminalov. M. : GKVG im. Akademika N.N. Burdenko, 1999, 174 p.

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Received 20.05.16

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Issue 184, article 5

DOI:https://doi.org/10.15407/kvt184.02.056

KVT, 2016, Issue 184, pp.56-72

UDC 004.75+004.932.2:616

INFORMATION SUPPORT FOR INTEROPERABILITY OF INSTRUMENTAL DIAGNOSTIC SYSTEMS AND LONG-TERM STORAGE SYSTEM OF DIGITAL MEDICAL IMAGES IN HEALTH CARE INSTITUTIONS

Romanyuk O.A., Kovalenko A.S., Kozak L.M.

International Research and Training Center for Information Technologies and Systems of the National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Kiev, Ukraine

ksnksn7@gmail.com , askov49@gmail.com , lmkozak52@gmail.com

 

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Introduction. The need of health care institutions in the repeated use of digital medical images by different specialists during patient care and long-term storage for the analysis of diagnostic information determines the relevance of this work.

The purpose of the article is to form technique for adapting the system of transmission and archiving of digital medical images according to the conditions of the health care institution.

Results. Analysis of medical image storage systems to select the specific software implementation according to the requirements of a particular medical institution was held. After testing and validation in working conditions PACS Conquest DICOM has been selected, its functionality has been verified. The technique of adapting the system for transmission and archiving of digital medical images has been developed, which includes an analysis of instrumental studies systems, installation of database components and configuration of PACS Conquest DICOM-server, connecting the instrumental studies systems and organization of access to digital medical images for medical personnel. Testing of the proposed technique was carried out at the National Institute of Cardiovascular Surgery named by N. Amosov.

Conclusion. The possibility of implementation the free and multi-platform storage system with connection of multiple diagnostic systems for efficient analysis of DMC on each workstation and long-term storage DMC is provided as a result of using the proposed technique.

Keywords: digital medical imaging, standard DICOM, long-term storage.

References:

  1. Kamenshchikov A.A. Interoperability in the field of e-health. Information Technologies and Computing Systems, 2009, № 5, pp. 67–71(in Russian).
  2. Robert Hoyt, Nora Bailey, Ann Yoshihashi. Health Informatics: Practical Guide for Healthcare and Information Technology Professionals (5th ed.). New York.: Lulu.com, 2012, 492p.
  3. EN ISO 12052:2011. Health informatics. Digital imaging and communication in medicine (DICOM) including workflow and data management. Available at: http://iso.org
  4. Oosterwijk Herman. DICOM Basics (3rd ed.). O Tech, 2005, pp. 23–28.
  5. Oosterwijk Herman. PACS Fundamentals (2nd ed.). O Tech, 2004, pp. 25–44.
  6. Dreyer K.J., Hirschorn D.S., Thrall J.H. PACS: A Guide to the Digital Revolution. London.: Springer, 2010, 596p., pp.249–269.

Received 15.12.2015

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Issue 182, article 7

DOI:https://doi.org/10.15407/kvt182.02.084

Kibern. vyčisl. teh., 2015, Issue 182, pp.

Krivova O.A., Kozak L.M.

International Research and Training Center for Information Technologies and
Systems of the National Academy of Sciences of Ukraine and Ministry of Education
and Science of Ukraine (Kiev)

СOMPLEX ESTIMATION OF REGIONAL DEMOGRAPHIC DEVELOPMENT

Introduction. Several studies are being conducted in the world to measure developmental disparities between countries, regions and territorial units. Composite indicators (or indexes) are used whenever a lot of variables are needed for evaluating developmental disparities between territories. Demographic variables are considered as important indicators of socio-economic development of regions. We show how cluster analysis can be combined with elements of multicriteria decision analysis (MCDA) to construct composite index regional demographic development of Ukraine.
The purpose of this article is the development of regional socioeconomic systems analysis methodology and construction of composite indicators of regional demographic development.
Results. We have used 5 territorial social-demographic indicators: 1) total fertility rate; 2) death rate of children under age of five; 3) life expectation at birth; 4) survivorship probabilities for men from 20 to 65 years; 5) survivorship probabilities for women from 20 to 65 years. The following strategy can be pursued in order to construct composite index . First, a cluster analysis (algorithms Ward and K-means) for defining clusters of regions based on the value of the individual indicators is used. The result of the cluster analysis is typological clusters of the selected regions. Second, such as each cluster can be characterized with a centroid, these centroids must be ordered from best to worst. Weights of composite index are calculated as coefficients of the best linear regression model of preference function.
Conclusion. The composite index of regional demographic development allows to assess the degree of variance in regional demographic development and ranking of regions.
Keywords: clustering, a composite indicator, the index of regional demographic development, ordered classification.

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References

  1. Methods of measuring human development regions of Ukraine; Resolution adopted by the College of the State Statistics Committee of Ukraine and Presidium of NAS of Ukraine 14.03.2001 р. № 76 Available at: http://www.ukrstat.gov.ua/metodod_polog/metod_doc/sp/sp_04.pdf. (in Ukrainian).
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Received 01.06.2015