Accuracy versus Transparency in Pharmacoeconomic Modelling
David Eddy ()
PharmacoEconomics, 2006, vol. 24, issue 9, 837-844
Abstract:
As modellers push to make their models more accurate, the ability of others to understand the models can decrease, causing the models to lose transparency. When this type of conflict between accuracy and transparency occurs, the question arises, “Where do we want to operate on that spectrum?” This paper argues that in such cases we should give absolute priority to accuracy: push for whatever degree of accuracy is needed to answer the question being asked, try to maximise transparency within that constraint, and find other ways to replace what we wanted to get from transparency. There are several reasons. The fundamental purpose of a model is to help us get the right answer to a question and, by any measure, the expected value of a model is proportional to its accuracy. Ironically, we use transparency as a way to judge accuracy. But transparency is not a very powerful or useful way to do this. It rarely enables us to actually replicate the model’s results and, even if we could, replication would not tell us the model’s accuracy. Transparency rarely provides even face validity; from the content expert’s perspective, the simplifications that modellers have to make usually raise more questions than they answer. Transparency does enable modellers to alert users to weaknesses in their models, but that can be achieved simply by listing the model’s limitations and does not get us any closer to real accuracy. Sensitivity analysis tests the importance of uncertainty about the variables in a model, but does not tell us about the variables that were omitted or the structure of the model. What people really want to know is whether a model actually works. Transparency by itself can’t answer this; only demonstrations that the model accurately calculates or predicts real events can. Rigorous simulations of clinical trials are a good place to start. This is the type of empirical validation we need to provide if the potential of mathematical models in pharmacoeconomics is to be fully achieved. Copyright Adis Data Information BV 2006
Date: 2006
References: Add references at CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://hdl.handle.net/10.2165/00019053-200624090-00002 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:pharme:v:24:y:2006:i:9:p:837-844
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/40273
DOI: 10.2165/00019053-200624090-00002
Access Statistics for this article
PharmacoEconomics is currently edited by Timothy Wrightson and Christopher I. Carswell
More articles in PharmacoEconomics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().