Dataset for "Costs and cost-effectiveness of user-testing of health professionals’ guidelines to reduce the frequency of intravenous medicines administration errors by nurses in the United Kingdom: a probabilistic model based on voriconazole administration"

  • Matthew Jones (University of Bath) (Contributor)
  • Bryony Dean Franklin (Creator)
  • D K Raynor (Creator)
  • Howard H Z Thom (Contributor)
  • Margaret Watson (University of Bath) (Contributor)
  • Rebecca Kandiyali (Contributor)

Dataset

Description

This dataset relates to a paper describing the costs and cost-effectiveness of user-testing injectable medicines guidelines, which was analysed using a probabilistic decision-analytic model. The dataset contains the Excel models used in the analysis and the STATA meta-analysis output used to determine one of the model inputs (the risk ratio for a medication administration error following a double-check by a nurse [compared with no double-check]).,Please see the detailed description given in the related open-access paper.,Microsoft Excel 365 STATA 16.0,The data contained in the two Excel model files are described within the files using cell comments. These models are based on a number of Excel worksheets in each, which are described below: Analysis - this worksheet is used to enter model input parameters (for time horizon, annual number of voriconazole doses, number of user testing interviews) and display the results. The run the model, first press the 'Monte Carlo Macro' button, then the 'Cost-effectiveness & EVPI curves' button Control model figure - this worksheet displays a diagramatic representation of the decision tree model for the no user testing scenario UT model figure - this worksheet displays a diagramatic representation of the decision tree model for the user testing scenario CE Curve - this worksheet displays the calculated cost-effectiveness acceptability curve EVPI - this worksheet displays the calculated expected value of perfect information curve Parameters - this worksheet displays and defines all the model input parameters and their distributions Dirichlet dist - this worksheet derives the Dirichlet distributions for error types and error severity Inflation - this worksheet derives the value for inflation Live model outputs - this worksheet derives the output for each simulation when the model is run. These outputs are then recorded in the 'Recorded model outputs' worksheet Recorded model outputs - this worksheet records the output for each simulation when the model is run. These data are then used by the 'Analysis' worksheet to calculate mean values and 95% credible intervals.,
Date made available3 Aug 2021
PublisherUniversity of Bath

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