Cost estimation of patients admitted to the intensive care unit: a case study of the Teaching University Hospital of Thessaly

J Med Econ. 2010;13(2):179-84. doi: 10.3111/13696991003684092.

Abstract

Objective: This study aimed to estimate the cost of patients admitted to the Intensive Care Unit (ICU) of the Teaching University Hospital of Thessaly (TUHT) in 2006 and to demonstrate discrepancies between actual hospitalisation cost and social funds' reimbursement.

Methods: Cost analysis was performed using a macro-costing approach, which focused on the estimation of nominal and actual cost per ICU patient. Data were derived from the annual records of resources consumed in each hospital unit and from hospital balance sheets. Sensitivity analysis was also performed by inflating nominal costs to present values.

Results: There were 312 patients admitted to the ICU. Mean actual cost per ICU patient was estimated at €16,516, whereas actual reimbursement from social funds was only €1,671. This means that reimbursement accounted for just 10% of the actual hospitalisation cost. Once nominal costs were inflated to present values, the reimbursement accounted for 25% of the actual hospitalisation cost. The major cost drivers of ICU hospitalisation were personnel costs followed by infrastructure, hotel services and pharmaceutical expenditure. These results may be limited by a lack of consideration for clinical outcomes along with a high level of aggregation in cost data.

Conclusion: Reimbursement should be re-adjusted in order to balance public hospital deficits and make public-private mix viable. This way, intensive care capacity would increase and allow a more equitable distribution of healthcare resources.

MeSH terms

  • Greece
  • Hospital Charges / statistics & numerical data*
  • Hospital Costs / statistics & numerical data*
  • Hospitals, Teaching / economics*
  • Humans
  • Intensive Care Units / economics*
  • Intensive Care Units / organization & administration
  • Length of Stay / statistics & numerical data
  • Organizational Case Studies
  • State Medicine / statistics & numerical data