IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

A methodology for measuring the relative effectiveness of healthcare services

Listed author(s):
  • Giorgio Vittadini
  • Simona Caterina Minotti

In this paper we propose a methodology for measuring the ‘relative effectiveness’ of healthcare services (i.e. the effect of hospital care on patients) under general conditions, in which: a) a healthcare outcome underlies qualitative and quantitative observable indicators; ß) we are interested in studying the simultaneous dependency of multiple outcomes on covariates (where the outcomes can also be correlated to each other); ?) the relative effectiveness is adjusted for hospital-specific covariates; d) we hypothesise a general distribution for random disturbances and the random parameters of relative effectiveness. For this topic, a generalisation of the SURE (seemingly unrelated regression equations) multilevel model is proposed. The solutions are obtained by means of Bayesian inference methods. Since there is currently no software available to estimate this model, an SAS procedure based on Markov Chain Monte Carlo methods has been developed by the authors, in line with Goldstein & Spiegelhalter (1996, J. R. Stat. Soc. Ser. A, 159, 385–443), Spiegelhalter et al. (1996, Bayesian Using Gibbs Sampling Manual. Cambridge: MRC Biostatistic Unit, Institute of Public Health) and Albert & Chib (1997, J. Am. Stat. Assoc., 92, 916–925). In addition, a new theoretical result regarding the joint posterior distribution for the parameters is provided. The model proposed has been implemented for an effectiveness study of a selection of Lombard hospitals.

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.

Paper provided by Università degli Studi di Milano-Bicocca, Dipartimento di Statistica in its series Working Papers with number 20050401.

in new window

Length: 16 pages
Date of creation: 2005
Publication status: Published in IMA Journal of Management Mathematics, 2005, vol. 16, pages 239–254
Handle: RePEc:mis:wpaper:20050401
Contact details of provider: Postal:
Via Bicocca degli Arcimboldi 8, 20126 Milano

Web page:

More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

in new window

  1. Gertler, Paul J, 1988. "A Latent-Variable Model of Quality Determination," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(1), pages 97-104, January.
  2. Forrest Young, 1981. "Quantitative analysis of qualitative data," Psychometrika, Springer;The Psychometric Society, vol. 46(4), pages 357-388, December.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:mis:wpaper:20050401. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Matteo Pelagatti)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.