In 2006, national healthcare expenditures reached ;This dissertation is focused on improving healthcare efficiency using operations research tools. It is divided into three major sections as outlined below to tackle benchmarking over time, a distributed framework, and computation issues in the healthcare sector. First, to identify the benchmark that performs consistently well across time periods, an extended data envelopment analysis (DEA) model with window and facet analysis over multiple time periods is proposed for selecting the best practice benchmarking that includes performance trends. The benchmarks identified by the proposed approach can be used by less efficient units as a benchmark in improving their efficiency.;Secondly, to improve resource allocation and thereby improve hospital operation efficiency, a bi-level framework for distributed resource allocation in healthcare is proposed. A multiple-tool integrated methodology (MTIM) integrates genetic algorithm, simulation, and DEA as a solution method for complex distributed heath care resource allocation systems in order to solve efficiency and budget constraints for hospitals and headquarters, respectively.;Finally, to improve the heavy computational demand of MTIM, an enhanced MTIM for distributed healthcare resource allocation is developed. By exploiting the usual structure a reduced set of DEA dual models are executed. This reduces the number of LP's solved. This is of particular value in a problem of this type where the size of the DEA formulations is changed iteration by iteration.
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