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Updated: May 23, 2026

Collecting And Measuring Wound Exudate Biochemical Mediators In Surgical Wounds
Published on: October 20, 2012
Cost-effectiveness analysis comparing epidural, patient-controlled intravenous morphine, and continuous wound
P Tilleul1, M Aissou, F Bocquet
1Department of Pharmacy, Assistance Publique-Hopitaux de Paris, St Antoine Hospital Paris, France.
Background:
Continuous wound infiltration (CWI), i.v. patient-controlled analgesia (i.v.-PCA), and epidural analgesia (EDA) are analgesic techniques commonly used for pain relief after open abdominal surgery. The aim of this study was to evaluate the cost-effectiveness of these techniques.
Methods:
A decision analytic model was developed, including values retrieved from clinical trials and from an observational prospective cohort of 85 patients. Efficacy criteria were based on pain at rest (VAS ≤ 30/100 mm at 24 h). Resource use and costs were evaluated from medical record measurements and published data. Probabilistic sensitivity analysis (PSA) was performed.
Results:
When taking into account all resources consumed, the CWI arm (€ 6460) is economically dominant when compared with i.v.-PCA (€ 7273) and EDA (€ 7500). The proportion of patients successfully controlled for their postoperative pain management are 77.4%, 53.9%, and 72.9% for CWI, i.v.-PCA, and EDA, respectively, demonstrating the CWI procedure to be both economically and clinically dominant. PSA reported that CWI remains cost saving in 70.4% of cases in comparison with EDA and in 59.2% of cases when compared with PCA.
Conclusions:
Device-related costs of using CWI for pain management after abdominal laparotomy are partly counterbalanced by a reduction in resource consumption. The cost-effectiveness analysis suggests that CWI is the dominant treatment strategy for managing postoperative pain (i.e. more effective and less costly) in comparison with i.v.-PCA. When compared with EDA, CWI is less costly with almost equivalent efficacy. This economic evaluation may be useful for clinicians to design algorithms for pain management after major abdominal surgery.
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