Display Settings:

Format

Send to:

Choose Destination
Health Serv Res. 2013 Feb;48(1):271-89. doi: 10.1111/j.1475-6773.2012.01437.x. Epub 2012 Jun 20.

Shrinkage estimators for a composite measure of quality conceptualized as a formative construct.

Author information

  • 1School of Management, Boston University, Boston, MA 02130, USA. mshwartz@bu.edu

Abstract

OBJECTIVE:

To demonstrate the value of shrinkage estimators when calculating a composite quality measure as the weighted average of a set of individual quality indicators.

DATA SOURCES:

Rates of 28 quality indicators (QIs) calculated from the minimum dataset from residents of 112 Veterans Health Administration nursing homes in fiscal years 2005-2008.

STUDY DESIGN:

We compared composite scores calculated from the 28 QIs using both observed rates and shrunken rates derived from a Bayesian multivariate normal-binomial model.

PRINCIPAL FINDINGS:

Shrunken-rate composite scores, because they take into account unreliability of estimates from small samples and the correlation among QIs, have more intuitive appeal than observed-rate composite scores. Facilities can be profiled based on more policy-relevant measures than point estimates of composite scores, and interval estimates can be calculated without assuming the QIs are independent. Usually, shrunken-rate composite scores in 1 year are better able to predict the observed total number of QI events or the observed-rate composite scores in the following year than the initial year observed-rate composite scores.

CONCLUSION:

Shrinkage estimators can be useful when a composite measure is conceptualized as a formative construct.

© Health Research and Educational Trust.

PMID:
22716650
[PubMed - indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Blackwell Publishing
    Loading ...
    Write to the Help Desk