Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

SAGETRACK

Sign In to gain access to subscriptions and/or personal tools.
Medical Decision Making
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Scalon, J. D.
Right arrow Articles by Cunha, T. A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Scalon, J. D.
Right arrow Articles by Cunha, T. A.
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

Validation of Models for Predicting the Use of Health Technologies

João D. Scalon

Sergio M. Freire

Tacio A. Cunha

Validation must be carried out before a model can be used confidently as a tool of managerial decision making in health care. The authors describe a bootstrap approach to validating models for predicting the utilization of four technologies used in neonatal care: measurement of blood gases (gasometry), the oxygen hood, continuous positive airway pressure (CPAP), and mechanical ventilation. These models were fitted by stepwise multiple linear regression from 20 prognostic covariates of 193 neonates. One hundred bootstrap samples were generated to validate the choices of covariates in the models based on their frequencies of selection. This approach validated the models for the oxygen hood and CPAP. The regression coefficients and standard deviations for the CPAP and oxygen hood models were estimated using 200 additional bootstrap samples. A close agreement between stepwise and bootstrap estimates was observed for both models. These results suggest that bootstrap can be useful for validating models for predicting the utilization of health technologies Key words: ne onatal intensive care, forecasting; health facility planning; health technology; bootstrap; model validation; regression analysis; linear models. (Med Decis Making 1998;18: 311-319)

Medical Decision Making, Vol. 18, No. 3, 311-319 (1998)
DOI: 10.1177/0272989X9801800309


Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?