Importance of Statistical Evidence in Estimating Valid DEA Scores.

Data Envelopment Analysis (DEA) allows healthcare scholars to measure productivity in a holistic manner. It combines a production unit's multiple outputs and multiple inputs into a single measure of its overall performance relative to other units in the sample being analyzed. It accomplishes this task by aggregating a unit's weighted outputs and dividing the output sum by the unit's aggregated weighted inputs, choosing output and input weights that maximize its output/input ratio when the same weights are applied to other units in the sample.

Improving the efficiency of distributive and clinical services in hospital pharmacy.

Three problems impede the assessment of hospital pharmacy efficiency. First, although multiple efficiency indicators are utilized to measure a large variety of activities, it has not been possible to validly measure overall efficiency. Second, there have been no widely-used clinical activity indicators, so key outputs often have not been accounted for.

Measuring hospital efficiency with Data Envelopment Analysis: nonsubstitutable vs. substitutable inputs and outputs.

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.