Benchmarking nursing homes using the Order Rated Effectiveness model
Benchmarking, a critical process to compare relative performance of nursing homes, was implemented in an earlier study applying multicriteria measures of operational and quality of care efficiencies. In that study those measures were aggregated and optimized using Data Envelopment Analysis (Shimshak et al., 2009) . The authors concluded that while providing useful analysis, the DEA results did not discriminate well among the nursing homes. In this paper we apply the Order Rated Effectiveness (ORE) model (Klimberg and Ratick, 2018; Klimberg and Ratick, 2020a; Klimberg and Ratick, 2020b) [2,3,4], to the Shimshak et al. data set to address that issue. The ORE model utilizes Order Weighted Averaging (OWA) to aggregate operational and quality performance measures, providing a range of relative performance measures for each nursing home. These aggregates are then used within a Data Envelopment Analysis (DEA) optimization framework. The use of OWA helps capture the implied preferences of multiple decision makers within the different nursing homes. We compare and evaluate the ORE results to those obtained in the original Shimshak et al. study. The ORE process provided aggregate comprehensive measures of relative performance that addressed both the multi-objective and multi-decision-maker character of this decision problem essential to making effective and actionable comparisons of nursing home performance. © 2023 Elsevier Ltd
Socio-Economic Planning Sciences
benchmarking, Data Envelopment Analysis, multicriteria performance measurement, nursing home performance, operational effectiveness, order rated effectiveness, ordered weighted average
Klimberg, Ronald and Ratick, Sam, "Benchmarking nursing homes using the Order Rated Effectiveness model" (2023). Geography. 955.