Welcome to BCEAweb
BCEAweb provides a web interface to the
R package
BCEA, designed to post-process the results of a statistical model and standardise
health economic evaluations, as described in the following graph.
First, a statistical model is constructed and fitted to estimate relevant population
parameters (the red rounded box). These are then fed to an economic model (the grey box),
which combines them to obtain suitable summaries that quantify the incremental population
average for clinical benefits (e.g. QALYs) and costs (e.g. £). These are the fundamental
quantities used to make the decision analysis (orange box). And this is the process that
BCEA and
BCEAweb can perform, by producing standardise output to aid in the assessment of the economic
evaluation. In addition, provided suitable data are provided by the user,
BCEAweb can also perform
Probabilistic Sensitivity Analysis i.e. the process of analysing the impact of (parameter or model) uncertainty on the
results of the decision analysis (the olive box).
BCEAweb assumes that the results of the statistical model are available in the form of a
large number of simulations for all the relevant model parameters. These can be stored
and uploaded by the user using three different formats:
- A spreadsheet, in .csv format, e.g. a file produced by MS Excel. Download an example here;
- Files in 'coda' format. These are typically saved as the results of running MCMC software such as OpenBUGS. Coda produces an 'index' file and one output file for each Markov Chain used in the
analysis. Download a .zip file with an example here.
- A R object, available in the current session. This can be a spreadsheet imported in R (e.g. using the
read.csv
function). Or the output of a full Bayesian analysis (e.g. performed using OpenBUGS). The resulting data will be pre-processed to eliminate linear dependency across the variables.
The parameters simulations are uploaded at the 'Parameter simulations' tab. Once the simulations
are uploaded,
BCEAweb will produce graphical summaries and tables so that the user can assess whether the results
are consistent with the assumptions or, in the case of a full Bayesian analysis, analysis
convergence of the MCMC process through suitable diagnostics.
BCEAweb assumes that the user has saved simulations for the measures of effectiveness and costs for each of the interventions
being assessed in a .csv file. The order of the variables in this file
needs
to be like in the following picture (e.g. effectiveness and costs for each intervention, in sequence).
An example of such a file can be obtained
here. These simulations are uploaded in the 'Economic analysis' tab, where the user can specify some options. Clicking the button
Run the analysis
in the 'Economic analysis tab' will run
BCEA in the background and create all the relevant economic summaries, including a detailed
Probabilistic Sensitivity Analysis. The tab 'Value of information' also automatically computes the
Expected Value of Perfect Information and allows the user to run an analysis of the Expected Value of
Partial Perfect Information. This is computed using computational efficient methods
and provides a valuable tool to assess the impact of current uncertainty on the decision-making process
and to determine research prioritisation. Crucially, these methods cannot be implemented in non-specialised
software (e.g. MS Excel) and thus the use of statistical programmes such as
R, is essential. The results of the
economic evaluation performed using
BCEAweb can be exported in either .pdf or .doc
format. The resulting report contains some pre-formatted text, aimed at guiding the user through
the interpretation of the results.
Copyright:
Gianluca Baio, Polina Hadjipanayiotou,
Andrea Berardi,
Anna Heath