Title: Data envelopment analysis models for identifying and benchmarking the best healthcare processes

Authors: James C. Benneyan, Aysun Sunnetci, Mehmet Erkan Ceyhan

Addresses: Department of Mechanical and Industrial Engineering, Northeastern University, 360 Huntington Avenue, Boston, MA 02115, USA. ' Northeastern University, 334 Snell Engineering Center, Boston, MA 02115, USA. ' Northeastern University, 334 Snell Engineering Center, Boston, MA 02115, USA

Abstract: We illustrate the use of Data Envelopment Analysis (DEA) models within process improvement work for identifying and benchmarking the best healthcare systems, in terms of most efficiently producing desirable outcomes from consumed resources. This approach is useful when comparing several systems that use multiple types of inputs (e.g., operating costs, clinicians, staff) to produce multiple outputs (e.g., outcomes, satisfaction, access), such as those commonly found in balanced scorecards and dashboard datasets, and provides the analyst with relative scores and rankings for each system, targets for each measure that would move inefficient systems to the best performance frontier, and a list of other systems to benchmark and emulate in order to improve. Modified DEA models are proposed to address four common issues that frequently arise in such contexts, including rationally constraining the weights given to each measure and handling missing, estimated or proportional data (such as adverse event or mortality rates). These models can be used to compare hospitals, departments, national healthcare systems, and regional or state systems and are useful to help understand how to improve sub-optimal processes and set feasible targets. This approach is illustrated at department, hospital, state, and country levels, with overall results showing very little correlation with less quantitative benchmarking studies.

Keywords: benchmarking; healthcare processes; data envelopment analysis; DEA; weight restrictions; proportional data; hyper-efficiency; healthcare comparisons; quality improvement; six sigma.

DOI: 10.1504/IJSSCA.2008.021842

International Journal of Six Sigma and Competitive Advantage, 2008 Vol.4 No.3, pp.305 - 331

Published online: 05 Dec 2008 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article