A Comparison of Four Software Programs for Implementing Decision Analytic Cost-Effectiveness Models
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Published on: September 10, 2018
Chase Hollman1, Mike Paulden2,3, Petros Pechlivanoglou4,5,6
1Department of Emergency Medicine, University of Alberta, 3-264 Edmonton Clinic Health Academy, 11405 87 Ave NW, Edmonton, AB, T6G 1C9, Canada.
Abstract:
The volume and technical complexity of both academic and commercial research using decision analytic modelling has increased rapidly over the last two decades. The range of software programs used for their implementation has also increased, but it remains true that a small number of programs account for the vast majority of cost-effectiveness modelling work. We report a comparison of four software programs: TreeAge Pro, Microsoft Excel, R and MATLAB. Our focus is on software commonly used for building Markov models and decision trees to conduct cohort simulations, given their predominance in the published literature around cost-effectiveness modelling. Our comparison uses three qualitative criteria as proposed by Eddy et al.: "transparency and validation", "learning curve" and "capability". In addition, we introduce the quantitative criterion of processing speed. We also consider the cost of each program to academic users and commercial users. We rank the programs based on each of these criteria. We find that, whilst Microsoft Excel and TreeAge Pro are good programs for educational purposes and for producing the types of analyses typically required by health technology assessment agencies, the efficiency and transparency advantages of programming languages such as MATLAB and R become increasingly valuable when more complex analyses are required.
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