Identifying Individual Changes in Performance With Composite Quality Indicators While Accounting for Regression to the Mean

Byron J. Gajewski and Nancy Dunton

Medical Decision Making, 2013, vol. 33, issue 3, 396-406

Abstract: Almost a decade ago Morton and Torgerson indicated that perceived medical benefits could be due to “regression to the mean.†Despite this caution, the regression to the mean “effects on the identification of changes in institutional performance do not seem to have been considered previously in any depth†(Jones and Spiegelhalter). As a response, Jones and Spiegelhalter provide a methodology to adjust for regression to the mean when modeling recent changes in institutional performance for one-variable quality indicators. Therefore, in our view, Jones and Spiegelhalter provide a breakthrough methodology for performance measures. At the same time, in the interests of parsimony, it is useful to aggregate individual quality indicators into a composite score. Our question is, can we develop and demonstrate a methodology that extends the “regression to the mean†literature to allow for composite quality indicators? Using a latent variable modeling approach, we extend the methodology to the composite indicator case. We demonstrate the approach on 4 indicators collected by the National Database of Nursing Quality Indicators. A simulation study further demonstrates its “proof of concept.â€

Keywords: provider profiling; individual changes; National Database of Nursing Quality Indicators; regression to the mean; Bayesian analysis (search for similar items in EconPapers)
Date: 2013
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X12461855 (text/html)

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:sae:medema:v:33:y:2013:i:3:p:396-406

DOI: 10.1177/0272989X12461855

Access Statistics for this article

More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().