Measuring Hospital Efficiency with Data Envelopment Analysis: Nonsubstitutable vs. Substitutable Inputs and Outputs View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2011-12

AUTHORS

Darold T. Barnum, Surrey M. Walton, Karen L. Shields, Glen T. Schumock

ABSTRACT

There is a conflict between Data Envelopment Analysis (DEA) theory's requirement that inputs (outputs) be substitutable, and the ubiquitous use of nonsubstitutable inputs and outputs in DEA applications to hospitals. This paper develops efficiency indicators valid for nonsubstitutable variables. Then, using a sample of 87 community hospitals, it compares the new measures' efficiency estimates with those of conventional DEA measures. DEA substantially overestimated the hospitals' efficiency on the average, and reported many inefficient hospitals to be efficient. Further, it greatly overestimated the efficiency of some hospitals but only slightly overestimated the efficiency of others, thus making any comparisons among hospitals questionable. These results suggest that conventional DEA models should not be used to estimate the efficiency of hospitals unless there is empirical evidence that the inputs (outputs) are substitutable. If inputs (outputs) are not substitutes, efficiency indicators valid for nonsubstitutability should be employed, or, before applying DEA, the nonsubstitutable variables should be combined using an appropriate weighting scheme or statistical methodology. More... »

PAGES

1393-1401

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10916-009-9416-0

DOI

http://dx.doi.org/10.1007/s10916-009-9416-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1008524126

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20703515


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