Aanesthetic Agents for Day Surgery - NIHR Health Technology ...

CESA models
Differences in the use of prophylactic
anti-emetics
Approach
Decision analysis was used to estimate the
expected costs, rates of PONV and ICERs if
prophylactic anti-emetics were added to the
anaesthetic regimen used in the CESA RCT
(adults), or different anaesthetic agents were
used for children. The structures of the decision
trees (models) were validated, ensuring that the
branch representing practice in the CESA RCT
replicated the results of the trial.
Probabilistic sensitivity analysis was used to
generate mean expected costs and outcomes
and statistical measures of expected variance
around the mean. This allows estimation of the
probability and extent to which uncertainty and
variation in the data used affect the absolute and
relative costs and outcomes. 257 For this analysis
each variable was assigned a base case or average
value and a distribution of possible values. The
probabilistic analysis summed the results of
multiple analyses (iterations). Each iteration
sampled the values for the variables at random
from the specified distributions. The simulation
package contained a component to determine
the most appropriate distributional form to
model the results of the empirical study. In
some cases the package did not identify the
distributional form that predicted the results
of the empirical study. In these cases, a manual
fit was obtained by identifying the distributional
form that best predicted the empirical data
available from the trial. Examples of the distributional
forms that were explored are triangular,
normal, truncated normal, uniform and
beta subjective.
Patient anaesthesised for
day surgery
No anti-emetic
prophylaxis (CESA RCT)
No anti-emetic
prophylaxis (model)
© Queen’s Printer and Controller of HMSO 2002. All rights reserved.
Health Technology Assessment 2002; Vol. 6: No. 30
The sampling method used was Latin Hypercube,
expected value. The simulation software used
was @RISK, 258 as an add on to Microsoft Office
Excel v. 7.0 ® . Every simulation requires sufficient
iterations to ensure that each variable is sampled
over the full distribution of values specified and
that the statistics generated are reliable. As the
number of iterations increases, the distribution
of the outcomes is described in more detail and
becomes more stable. The amount of change in
the percentile values, mean and SD decreases
with each subsequent iteration. The number of
iterations for each simulation was determined by
the software, which halted the simulation when
convergence at less than 1.5% in percentile values,
mean and SD was achieved. The simulation
analyses gave estimates of the probability that the
expected ICERs calculated could occur. The
decision tree for the model was structured to
mirror the trial. The literature review indicated
that the likely sequence and structure of events
was the same with and without anti-emetic
prophylaxis (i.e. practice in the CESA RCT).
What was expected to differ was the incidence
and intensity of PONV, and the subsequent
impact on costs.
The decision tree is presented in Figure 1. One
branch emanating from the decision node of the
tree represents the CESA RCT when a day patient
was anaesthetised with one of the four anaesthetic
agents (trial) and not given anti-emetic prophylaxis.
The second branch of the decision model
represents the scenario when a day patient was
anaesthetised with one of the four anaesthetic
agents and received a prophylactic 4 mg intravenous
dose of ondansetron (model). Four
decision trees, one for each anaesthetic
regimen in the CESA RCT, were defined.
PONV
No PONV
PONV
No PONV
FIGURE 1 The decision analytic model used to simulate the use of prophylactic anti-emetics
Cost path 1
Cost path 2
Cost path 3
Cost path 4
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