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Intensive care services in Hungary 2000 to 2010: an analysis of bed numbers, occupancy rates, case mix and economics


The purpose of this study is to describe the changes in pattern of intensive care (ICU) use over a 10-year period in Hungary. We attempt to analyze national data in order to improve resource use.


A retrospective analysis of national data provided by the hospitals for reimbursement of care to the National Healthcare Fund of Hungary between 2000 and 2010.


The total number of active hospital beds decreased by 33.4% (from 65,532 to 44,300); however, the number of ICU beds increased by 9.8% (from 1,189 to 1,306) between 2000 and 2010. As a result, the percentage of ICU beds to hospital beds increased from 1.89% in 2000 to 2.95% in 2010. The ICU bed occupancy rate ranged between 58.43% and 63.78%; it showed no correlation with the case mix index (r2 = 0.2799). The number of ventilator days increased from 28.9% to 66.1%; it showed good correlation with the case mix index (r2 = 0.9125). Analysing 2010 data, we found significantly lower mortality in level III units (30 ± 18%) compared to level II (51 ± 20%) and level I (56 ± 19%) care (P = 0.001 and 0.003), without significant differences in case mix index (Table 1). The mean ICU bed occupancy rate was 59.5% (SD ±12%), and length of hospital stay was 12.3 (SD ±3.0) in 2010. Geographic distribution of ICU beds per 100,000 population ranged between 7.3 and 27.4 (nationwide 12.9/100,000); it showed no correlation with regional gross domestic product values (r2 = 0.4593).

Table 1 Distribution of intensive care services in 2010


Our data suggest that intensive care beds are not utilized; a progressive level of care does not function and also there are unnecessary regional differences in intensive care provision in Hungary.

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Correspondence to A Csomos.

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Csomos, A., Fulesdi, B. & Gresz, M. Intensive care services in Hungary 2000 to 2010: an analysis of bed numbers, occupancy rates, case mix and economics. Crit Care 16, P509 (2012).

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  • Care Service
  • Regional Difference
  • Domestic Product
  • Lower Mortality
  • National Data