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Evidence-based Practice and Quality Improvement

A comparison of cost effectiveness analyses about intraoperative goal directed therapy


Ebm, C.; Cecconi, M.; Aya, H.; Geisen, M.; Sutton, L.; Rhodes, A.

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European Journal of Anaesthesiology (EJA): June 2013 - Volume 30 - Issue - p 22-23
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Background: Decisions about adoption and reimbursement of new perioperative strategies are often complicated by the complexity and uncertainty intrinsic to health care. Intraoperative goal directed (GDT) therapy has been shown to improve outcome in high risk surgical patients, yet the cost impact has not been established. Mathematical decision models are increasingly used to capture the relationship between inputs (comorbidities), intervention and output (outcomes) in order to predict future costs and outcomes. The aim of this paper is to assess the cost-effectiveness of GDT by comparing the results of a deterministic decision tree and two probabilistic mathematical simulation models.

Methodology: Comparison of three simulation methods. A simple decision tree, a Marcov analysis and a Monte Carlo Simulation were constructed to replicate the long term follow up period of a high risk surgical patients undergoing high risk surgery and receiving intraoperative goal directed therapy.

Results: Intraoperative goal directed therapy was shown to be cost-effective by all three methods (incremental savings of £1,539.75; £1034.00; £1033.04). The decision tree estimated the highest mean costs, mean cost savings and lowest mean survival (Table 1). The probabilistic Marcov and Monte Carlo simulation estimated fairly similar costs and quality adjusted life expectancy (2.78 years (5.26-8.04) versus 2.67 years (5.16-7.83).

[Incremental and Maximum Costs and Effects of GDT]

Conclusion: Intraoperative goal directed therapy is shown to be a cost effective clinical strategy by all methods used. Probabilistic analysis reported similar results, but significantly diverged from the results estimated by the decision tree. This is thought to be due to the deterministic nature of the decision tree describing average results, and neglecting the random elements inherent in disease recovery. Probabilistic simulation replicates the dynamics of health care more accurately and may be a more useful tool in informing decision makers about resource allocation.

© 2013 European Society of Anaesthesiology