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Practical issues in handling data input and uncertainty in a budget impact analysis

Nuijten, M. J. C.; Mittendorf, T. and Persson, Ulf LU (2011) In European Journal of Health Economics 12(3). p.231-241
Abstract
The objective of this paper was to address the importance of dealing systematically and comprehensively with uncertainty in a budget impact analysis (BIA) in more detail. The handling of uncertainty in health economics was used as a point of reference for addressing the uncertainty in a BIA. This overview shows that standard methods of sensitivity analysis, which are used for standard data set in a health economic model (clinical probabilities, treatment patterns, resource utilisation and prices/tariffs), cannot always be used for the input data for the BIA model beyond the health economic data set for various reasons. Whereas in a health economic model, only limited data may come from a Delphi panel, a BIA model often relies on a majority... (More)
The objective of this paper was to address the importance of dealing systematically and comprehensively with uncertainty in a budget impact analysis (BIA) in more detail. The handling of uncertainty in health economics was used as a point of reference for addressing the uncertainty in a BIA. This overview shows that standard methods of sensitivity analysis, which are used for standard data set in a health economic model (clinical probabilities, treatment patterns, resource utilisation and prices/tariffs), cannot always be used for the input data for the BIA model beyond the health economic data set for various reasons. Whereas in a health economic model, only limited data may come from a Delphi panel, a BIA model often relies on a majority of data taken from a Delphi panel. In addition, the dataset in a BIA model also includes forecasts (e.g. annual growth, uptakes curves, substitution effects, changes in prescription restrictions and guidelines, future distribution of the available treatment modalities, off-label use). As a consequence, the use of standard sensitivity analyses for BIA data set might be limited because of the lack of appropriate distributions as data sources are limited, or because of the need for forecasting. Therefore, scenario analyses might be more appropriate to capture the uncertainty in the BIA data set in the overall BIA model. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
* Model * Budget impact * Data source
in
European Journal of Health Economics
volume
12
issue
3
pages
231 - 241
publisher
Springer
external identifiers
  • wos:000289575600005
  • scopus:79958040730
ISSN
1618-7601
DOI
10.1007/s10198-010-0236-4
language
English
LU publication?
yes
id
ff654b5d-e03d-4b60-b053-c3d71122a612 (old id 1965056)
alternative location
http://www.springerlink.com/content/tn6472m472l745l3/
date added to LUP
2011-05-23 15:44:53
date last changed
2017-11-19 03:15:07
@article{ff654b5d-e03d-4b60-b053-c3d71122a612,
  abstract     = {The objective of this paper was to address the importance of dealing systematically and comprehensively with uncertainty in a budget impact analysis (BIA) in more detail. The handling of uncertainty in health economics was used as a point of reference for addressing the uncertainty in a BIA. This overview shows that standard methods of sensitivity analysis, which are used for standard data set in a health economic model (clinical probabilities, treatment patterns, resource utilisation and prices/tariffs), cannot always be used for the input data for the BIA model beyond the health economic data set for various reasons. Whereas in a health economic model, only limited data may come from a Delphi panel, a BIA model often relies on a majority of data taken from a Delphi panel. In addition, the dataset in a BIA model also includes forecasts (e.g. annual growth, uptakes curves, substitution effects, changes in prescription restrictions and guidelines, future distribution of the available treatment modalities, off-label use). As a consequence, the use of standard sensitivity analyses for BIA data set might be limited because of the lack of appropriate distributions as data sources are limited, or because of the need for forecasting. Therefore, scenario analyses might be more appropriate to capture the uncertainty in the BIA data set in the overall BIA model.},
  author       = {Nuijten, M. J. C. and Mittendorf, T. and Persson, Ulf},
  issn         = {1618-7601},
  keyword      = {* Model
* Budget impact
* Data source},
  language     = {eng},
  number       = {3},
  pages        = {231--241},
  publisher    = {Springer},
  series       = {European Journal of Health Economics},
  title        = {Practical issues in handling data input and uncertainty in a budget impact analysis},
  url          = {http://dx.doi.org/10.1007/s10198-010-0236-4},
  volume       = {12},
  year         = {2011},
}