Dollars and sense of interval appendectomy in children: a cost analysis.
OBJECTIVE
Although initial nonoperative management of focal, perforated appendicitis in children is increasingly practiced, the need for subsequent interval appendectomy remains debated. We hypothesized that cost comparison would favor continued nonoperative management over routine interval appendectomy.


METHODS
Decision tree analysis was used to compare continued nonoperative management with routine interval appendectomy after initial success with nonoperative management of perforated appendicitis. Outcome probabilities were obtained from literature review and cost estimates from the Kid's Inpatient Database. Sensitivity analyses were performed on the 2 most influential variables in the model, the probability of successful nonoperative management and the costs associated with successful observation. Monte Carlo simulation was performed using the range of cost estimates.


RESULTS
Costs for continued nonoperative observation were estimated at $3080.78 as compared to $5034.58 for the interval appendectomy. Sensitivity analysis confirms a cost savings for nonoperative management as long as the likelihood of successful observation exceeds 60%. As the cost of nonoperative management increased, the required probability for its success also increased. Using wide distributions for both probability estimates as well as costs, Monte Carlo simulation favored continued observation in 75% of scenarios.


CONCLUSIONS
Continued nonoperative management has a cost advantage over routine interval appendectomy after initial success with conservative management in children with focal, perforated appendicitis.
Raval
Mehul V
MV
Division of Research and Optimal Patient Care, American College of Surgeons, Chicago, IL 60611-3211, USA. m-raval@md.northwestern.edu
Lautz
Timothy
T
Reynolds
Marleta
M
Browne
Marybeth
M
D001062:Appendectomy / Q000191:economics*; D001064:Appendicitis / Q000191:economics / Q000601:surgery / Q000628:therapy*; D002648:Child; D003365:Costs and Cost Analysis; D003663:Decision Trees; D006801:Humans; D009010:Monte Carlo Method