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Investigation of Relationship Between Spatial Distribution of Medical Equipment and Preventable Mortality

Author

Listed:
  • Beata Gavurova

    (Technical University of Košice, 04001 Košice, Slovak Republic
    Research and Innovation Centre Bioinformatics, University Science Park Technicom, 042 00 Košice, Slovak Republic)

  • David Tucek

    (Faculty of Management and Economics, Tomas Bata University, 76001 Zlín, Czech Republic)

  • Viliam Kovac

    (Technical University of Košice, 04001 Košice, Slovak Republic
    Research and Innovation Centre Bioinformatics, University Science Park Technicom, 042 00 Košice, Slovak Republic)

Abstract

The aim of the study is to investigate the relationship between the spatial distribution of the selected medical equipment and the preventable mortality rate in the regions of the Slovak Republic. The main analytical approach is carried out through the cluster analysis based on a Euclidean distance technique in order to get similarity of the administrative divisions in form of a district and a pseudot2 approach aimed at the determination of a number of the districts in a cluster. A number of medical equipment had a rising tendency from the year 2008. The most extreme position according to a localisation distribution of the computed tomographs and the magnetic resonance imaging scanners is held by the Košice IV District at the level of 7.50630. From an angle of view of the preventable mortality, the Piešťany District holds the most extreme position peaking at the level of 10.97969 for the female sex and the Kežmarok District with the value of 9.44088. The study has the significant dissemination outputs for health policy interventions, especially to draw up regional health plans for computed tomography and magnetic resonance imaging deployment, mainly in locations with a high preventable mortality rate for both sexes.

Suggested Citation

  • Beata Gavurova & David Tucek & Viliam Kovac, 2019. "Investigation of Relationship Between Spatial Distribution of Medical Equipment and Preventable Mortality," IJERPH, MDPI, vol. 16(16), pages 1-33, August.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:16:p:2913-:d:257590
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    References listed on IDEAS

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    1. Xing, Zhang & Oyama, Tatsuo, 2016. "Measuring the impact of Japanese local public hospital reform on national medical expenditure via panel data regression," Technological Forecasting and Social Change, Elsevier, vol. 113(PB), pages 460-467.
    2. Bach, Luder & Hoberg, Rolf, 1985. "A planning model for regional systems of CT scanners," Socio-Economic Planning Sciences, Elsevier, vol. 19(3), pages 189-199.
    3. Robert Stefko & Beata Gavurova & Kristina Kocisova, 2018. "Healthcare efficiency assessment using DEA analysis in the Slovak Republic," Health Economics Review, Springer, vol. 8(1), pages 1-12, December.
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    Cited by:

    1. Silvia Megyesiova & Vanda Lieskovska, 2019. "Premature Mortality for Chronic Diseases in the EU Member States," IJERPH, MDPI, vol. 16(20), pages 1-23, October.

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