Población y Salud en Mesoamérica ISSN electrónico: 1659-0201

OAI: https://www.revistas.ucr.ac.cr/index.php/psm/oai
Geographic variability of hospitalizations for acute myocardial infarction in Costa Rica
PDF (Español (España))

Keywords

Myocardial Infarction
Hospitalization
Geographical Distribution (fuente
POPIN
MeSH)
infarto del miocardio
hospitalización
distribución geográfica (fuente
POPIN
DeCS)
Myocardial Infarction
Hospitalization
Geographical Distribution (fuente
MeSH)

How to Cite

Morera Salas, M. (2014). Geographic variability of hospitalizations for acute myocardial infarction in Costa Rica. Población Y Salud En Mesoamérica, 11(2). https://doi.org/10.15517/psm.v11i2.12735

Abstract

This research shows the geographic pattern of hospitalizations due to acute myocardial infarction in the public health care system in Costa Rica from 2010 to 2012. For the geographical analysis we used the geographic representation of the Bayesian smoothed standardized hospitalization ratio and the areas with hospitalization rate significantly different from the national average. Spatial autocorrelation was determined by Moran's I indicator. Amplitude between variations was performed using inter percentile ratio (percentile 95/percentile 5) and the variation coefficient. The gross rate is 5.8 hospitalizations per 10 000 population in men and 2.6/10 000 in women. The range of variation between areas with higher and lower hospitalizations is more than double. The most complex national hospitals are in the metropolitan areas. We found a pattern of low rates of hospitalization for acute myocardial infarction outside of metropolitan areas. This could be related to difficulties in accessing hospital services.
https://doi.org/10.15517/psm.v11i2.12735
PDF (Español (España))

References

Anselin, L., Kim Y-W ySyabri, I. (2004). Web-based analytical tools for the exploration of spatial data.Journal of Geographical Systems, 6,197–218.

Anselin, L. (1996). ‘‘The Moran Scatterplot as an ESDA Tool to Assess Local Instability in Spatial Association.’’In Spatial Analytical Perspectives on GIS in Environmental and Socio-Economic Sciences, 111–25, edited by M. Fischer, H. Scholten, and D. Unwin. London: Taylor and Francis.

Anderson, J. L., Adams, C. D., Antman, E. M., Bridges, C. R.et al. (2007). ACC/AHA 2007 guidelines for the management of patients with unstable angina/non–ST-elevation myocardial infarction: a report of the American College of Cardiology/ American Heart Association Task Force on Practice Guidelines (Writing Committee to Revise the 2002 Guidelines for the Management of Patients With Unstable Angina/Non–ST-Elevation Myocardial Infarction). Circulation, 116, e148–304.

Aparicio, A., Morera, M. (2009). Atlas de mortalidad por todas las causas Costa Rica 200-2007. Editorial Nacional de Salud y Seguridad Social (EDNASSS).

Besag, J., York, J. C. y Mollié, A. (1991). Bayesian image restoration, with two applications in spatial statistics (with discussion). Annals of the Institute of Statistical Mathematics, 43, 1-59.

Fiol, M., Cabadés, A., Sala, J., Marrugat, J.et al. (2001). Variabilidad en el manejo hospitalario del infarto agudo de miocardio en España. Rev. Esp.Cardiol, 54 (4), 443-452.

García, J., Elosúa, R., Tormo, M. J., Audicana, C.et al. (2003). Mortalidad poblacional por infarto agudo de miocardio. Estudio IBERICA. Med Clin (Barc), 121, 606-12.

Krumholz, H. M., Anderson, J. L., Bachelder, B. L., Fesmire, F.et al. (2008). ACC/AHA 2008 performance measures for adults with ST-elevation and non-ST-elevation myocardial infarction: a report of the American College of Cardiology/ American Heart Association Task Force on Performance Measures (Writing Committee to Develop Performance Measures for ST-Elevation and Non–ST-Elevation Myocardial Infarction). Circulation, 118, 2598–648.

Lawson, A., Browne, W. y Vidal, C. (2003). Disease Mapping with WinBUGS and MLwiN.Statistics in Practice.John Wiley and Sons.

Librero, J., Peiró, S., Bernal-Delgado, E., Allepuz, A.et al.(2011). Metodología del Atlas de variaciones en hospitalizaciones potencialmente evitables en el Sistema Nacional de Salud. Atlas Var PractMedSistNac Salud, 4 (2), 371-78.

Márquez-Calderón, S., Jiménez, A., Perea-Milla, E., Briones, E.et al. (2007). Variaciones en la hospitalización por problemas y procedimientos cardiovasculares en el Sistema Nacional de Salud. Atlas de Variabilidad en la Práctica Médica en el Sistema Nacional de Salud. España.

Richardson, S., Thomson, A., Best, N. y Elliott, P. (2004).Interpreting Posterior Relative Risk Estimates in Disease-Mapping Studies. Environmental Health Perspectives, 112(9), 1016-25.

Roe, M. T,, Parsons, L. S., Pollack, C. V., Canto, J. G.et al. (2005). Quality of care by classification of myocardial infarction: Treatment patterns for ST-segment elevation vs non-ST-segment elevation myocardial infarction. Arch Intern Med, 165,1630-6.

Steg, G., James, S., Atar, D., Badano, L.et al.(2012). ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation European Heart Journal, 33, 2569–2619.

Comments

Downloads

Download data is not yet available.