Dataset Information

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

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.

SUBMITTER: Shwartz M

PROVIDER: S-EPMC3589966 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature

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Publications

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

Shwartz Michael M Peköz Erol A EA Christiansen Cindy L CL Burgess James F JF Berlowitz Dan D

Health services research 20120620 1

<h4>Objective</h4>To demonstrate the value of shrinkage estimators when calculating a composite quality measure as the weighted average of a set of individual quality indicators.<h4>Data sources</h4>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.<h4>Study design</h4>We compared composite scores calculated from the 28 QIs using both observed rates and shrunken rates derived from ...[more]

PMID: 22716650

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Dataset Information

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

Objective

Data sources

Study design

Principal findings

Conclusion

Publications

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

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