Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

• Autorzy: Medyńska-Gulij B. , Cybulski P.

Identyfikatory

DOI

10.1515/geocart-2016-0002

• Języki publikacji: EN

Abstrakty

EN

This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.

Słowa kluczowe

EN

previsualisation; visual analysis; cartographic visualisation; public health; health expenditure

PL

analiza wizualna; wizualizacja kartograficzna; zdrowie publiczne

• Wydawca: Komitet Geodezji PAN
• Czasopismo: Geodesy and Cartography
• Rocznik: 2016
• Tom: Vol. 65, no. 1
• Strony: 67--80
• Opis fizyczny: Bibliogr. 30 poz., rys., tab.

Twórcy

autor

Medyńska-Gulij B.

• Adam Mickiewicz University in Poznan, Faculty of Geographic and Geological Scienses, Department of Cartography and Geomatics, 27 Dzięgielowa St., 61-680 Poznan, Poland

autor

Cybulski P.

• Adam Mickiewicz University in Poznan, Faculty of Geographic and Geological Scienses, Department of Cartography and Geomatics, 27 Dzięgielowa St., 61-680 Poznan, Poland

Bibliografia

• [1] Appleby, J. (2013). The hospital bed: On its way out? British Medical Journal, 346(7899), Article number f1563. DOI: http://dx.doi.org/10.1136/bmj.f1563.
• [2] Artazcoz, L., Benach, J., Borrell, C. and Cortès, I. (2004). Unemployment and Mental Health: Understanding the Interactions Among Gender, Family Roles, and Social Class. American Journal of Public Health, 94(1), 82-88. DOI: 10.2105/AJPH.94.1.82.
• [3] Bhowmick, T., Robinson, A.C., Gruver, A., MacEachren, A.M. and Lengerich, E.J. (2008). Distributed usability evolution of the Pennsylvania Cancer Atlas. International Journal of Health Geographics, 7, 36. DOI: 10.1186/1476-072X-7-36.
• [4] Chakrabortty, R.K., Asadujjaman, M. and Nuruzzaman, M. (2014). Fuzzy and AHP approaches for designing a hospital bed: A case study in Bangladesh. International Journal of Industrial Systems Engineering, 17(3), 315-328. DOI: 10.1504/IJISE.2014.062541.
• [5] Cybulski, P. (2014). Presentation of spatio-temporal data in the context of information capacity and visual suggestiveness. Geodesy and Cartography, 63(2), 147-159. DOI: 10.2478/geocart-2014-0011.
• [6] Delamater, P.L., Messina, J.P., Grady, S.C., WinklerPrins, V. and Shortridge A.M. (2013). Do More Hospital Beds Lead to Higher Hospitalization Rates? A Spatial Examination of Roemer’s Law(spatial analysis). PLoS One, 8(2), Article number e54900. DOI: 10.1371/journal.pone.0054900.
• [7] Dent, B.D. (2008). Cartography: thematic map design. Boston: WBC/McGraw-Hill.
• [8] Ferguson, J. (2002). The role of privy council nominees. Pharmaceutical Journal, 269(7209), 157.
• [9] Gaynor, M. and Anderson, G.F. (1995). Uncertain demand, the structure of hospital costs, and the cost of empty hospital beds. Journal of Health Economics, 14, 291-317. DOI: 10.3386/w4460.
• [10] Green, L.V. (2002). How Many Hospital Beds? Inquiry : a journal of medical care organization, provision and financing, 39(4), 400-412. DOI: DOI: 10.5034/inquiryjrnl_39.4.400.
• [11] Green, L.V. and Nguyen, V. (2001). Strategies for cutting hospital beds: The impact on patient service. Health Services Research, 36(2), 421-442. DOI: 10.1177/1077558715572388.
• [12] Ham, C., York, N., Sutch, S. and Shaw, R. (2003). Hospital bed utilisation in the NHS, Kaiser Permanente, and the US Medicare programme: Analysis of routine data. British Medical Journal, 327(7426), 1257-1260. DOI: http://dx.doi.org/10.1136/bmj.327.7426.1257.
• [13] Jenks, G.F. (1967). The Data Model Concept in Statistical Mapping. International Yearbook of Cartography, 7, 186-190.
• [14] Joseph, A.E. and Phillips, D.R. (1984). Accessibility and utilization: geographical perspectives on health care delivery. New York, Harper Row.
• [15] Khan, A.A. (1992) An integrated approach to measuring potential spatial access to health care services. Socio-Economic Planning Sciences, 26(4), 275–287. DOI: 10.1016/0038-0121(92)90004-O.
• [16] Kowarik, A., Meindl, B. and Templ, M. (2015). SparkTable: Generating graphical tables forwebsites and documents with R. R Journal, 7(1), 24-37.
• [17] Klemm, P., Oeltze-Jafra, S., Lawonn, K., Hegenscheid, K., Volzke, H. and Preim, B. (2014). Interactive Visual Analysis of Image-Centric Cohort Study Data. IEEE Transactions on Visualization and Computer Graphics, 20(12), 1673-1682. DOI: 10.1109/TVCG.2014.2346591.
• [18] Kraak, M-J. and Ormeling, F. (2010). Cartography. Visualization of Spatial Data. 3rdedn. London, Prentice Hall.
• [19] Kroneman, M. and Siegers, J. (2004). The effect of hospital bed reduction on the use of beds: A comparative study of 10 European countries. Social Science and Medicine, 59, 1731-1740. DOI: 10.1016/j.socscimed.2004.01.036.
• [20] Mayer, E., Moyen, S. and Stähler, N. (2010). Government Expenditures and Unemployment: A DSGE Perspective. Bundesbank Discussion Paper, Series 1, No. 18/2010.
• [21] Medyńska-Gulij, B. (2011). Kartografia i geowizualizacja. Warszawa. Wydawnictwo Naukowe PWN.
• [22] Medyńska-Gulij, B. (2014) Cartographic sign as a core of multimedia map prepared by non-cartographers in free map services. Geodesy and Cartography, 63, 55-64. DOI: 10.2478/geocart-2014-0004.
• [23] Mosseveld, C.J.P.M. (2003). International comparison of health care expenditure, existing frameworks, innovations and data use. Netherlands: Statistic Netherlands, Voorbugr.
• [24] Ocaña-Riola, R. (2010) Common Errors in Disease Mapping. Geospatial Health, 4(2), 139-154.
• [25] Oliveira, S., Portela, F., Santos, M.F., Machado, J. and Abelha, A. (2014). Predictive models for hospital bed management using data mining techniques. Advances in Intelligent System and Computing, 276(2), 407-416. DOI: 10.1007/978-3-319-05948-8_39.
• [26] Ratajski, L. (1989). Metodyka kartografii społeczno-gospodarczej. 2nd Edn. Warszawa, Wrocław, Państwowe Przedsiębiorstwo Wydawnictw Kartograficznych.
• [27] Schweikart, J. and Kistemann, T. (2013). Mapping Health and Health Care. Kartographische Nachrichten, 1, 3-11.
• [28] Slocum, T.A., McMaster, R.B., Kessler, F.C. and Howard, H.H. (2009). Thematic cartography and geovisualization. 3rd edn. Englewood Cliffs, NJ: Prentice Hall.
• [29] Van Doorslaer, E.K.A. and Van Vliet, R.C.J. (1989). ‘A builtbed is a filled bed?’ An empirical reexamination. Social Science and Medicine, 28, 155-164. DOI: 10.1016/0277-9536(89)90143-3.
• [30] Wei, Luo. (2004). Using a GIS-based floating catchment method to assess areas with shortage of physicians. Health & Place, 10(1), 1–11. DOI: 10.1016/S1353-8292(02)00067-9.