Change search
ReferencesLink to record
Permanent link

Direct link
On the practice of ignoring center-patient interactions in evaluating hospital performance
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics. (Stat4Reg)ORCID iD: 0000-0003-3298-1555
2016 (English)In: Statistics in Medicine, ISSN 0277-6715, E-ISSN 1097-0258, Vol. 35, no 2, 227-238 p.Article in journal (Refereed) Published
Abstract [en]

We evaluate the performance of medical centers based on a continuous or binary patient outcome (e.g., 30-day mortality). Common practice adjusts for differences in patient mix through outcome regression models, which include patient-specific baseline covariates (e.g., age and disease stage) besides center effects. Because a large number of centers may need to be evaluated, the typical model postulates that the effect of a center on outcome is constant over patient characteristics. This may be violated, for example, when some centers are specialized in children or geriatric patients. Including interactions between certain patient characteristics and the many fixed center effects in the model increases the risk for overfitting, however, and could imply a loss of power for detecting centers with deviating mortality. Therefore, we assess how the common practice of ignoring such interactions impacts the bias and precision of directly and indirectly standardized risks. The reassuring conclusion is that the common practice of working with the main effects of a center has minor impact on hospital evaluation, unless some centers actually perform substantially better on a specific group of patients and there is strong confounding through the corresponding patient characteristic. The bias is then driven by an interplay of the relative center size, the overlap between covariate distributions, and the magnitude of the interaction effect. Interestingly, the bias on indirectly standardized risks is smaller than on directly standardized risks. We illustrate our findings by simulation and in an analysis of 30-day mortality on Riksstroke.

Place, publisher, year, edition, pages
2016. Vol. 35, no 2, 227-238 p.
Keyword [en]
Firth correction, causal effects, direct and indirect standardization, misspecified model, quality of care
National Category
Probability Theory and Statistics
Research subject
URN: urn:nbn:se:umu:diva-109660DOI: 10.1002/sim.6634ISI: 000367972400005PubMedID: 26303843ISBN: 1097-0258 (Electronic) 0277-6715 (Linking)OAI: diva2:858589
Available from: 2015-10-02 Created: 2015-10-02 Last updated: 2016-02-10Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Eriksson, Marie
By organisation
In the same journal
Statistics in Medicine
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 57 hits
ReferencesLink to record
Permanent link

Direct link