Observational studyPloS one2021
Using data envelopment analysis to perform benchmarking in intensive care units.
Observational study in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Construction and Efficiency Estimation of a Nursing Human Resource Evaluation System in Integrated Medical-Nursing Elderly Care Institutions Using Data Envelopment Analysis.Journal of nursing management · 2026Article
- Performance of Greek Public Hospitals Before and After the Economic Recession and the Pandemic: Application of a Novel Cost Malmquist Index for Comparing Productivity Across Multiple Groups.Healthcare (Basel, Switzerland) · 2025Article
- A novel approach to measuring emergency physician efficiency.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2025Article
- Optimising Healthcare Delivery:Sultan Qaboos University medical journal · 2025Article
- Assessing resource allocation based on workload: a data envelopment analysis study on clinical departments in a class a tertiary public hospital in China.BMC health services research · 2023Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundStudies using Data Envelopment Analysis to benchmark Intensive Care Units (ICUs) are scarce. Previous studies have focused on comparing efficiency using only performance metrics, without accounting for resources. Hence, we aimed to perform a benchmarking analysis of ICUs using data envelopment analysis.
methodsWe performed a retrospective analysis on observational data of patients admitted to ICUs in Brazil (ORCHESTRA Study). The outputs in our data envelopment analysis model were the performance metrics: Standardized Mortality Ratio (SMR) and Standardized Resource Use (SRU); whereas the inputs consisted of three groups of variables that represented staffing patterns, structure, and strain, thus resulting in three models. We compared efficient and non-efficient units for each model. In addition, we compared our results to the efficiency matrix method and presented targets to each non-efficient unit.
resultsWe performed benchmarking in 93 ICUs and 129,680 patients. The median age was 64 years old, and mortality was 12%. Median SMR was 1.00 [interquartile range (IQR): 0.79-1.21] and SRU was 1.15 [IQR: 0.95-1.56]. Efficient units presented lower median physicians per bed ratio (1.44 [IQR: 1.18-1.88] vs. 1.7 [IQR: 1.36-2.00]) and nursing workload (168 hours [IQR: 168-291] vs 396 hours [IQR: 336-672]) but higher nurses per bed ratio (2.02 [1.16-2.48] vs. 1.71 [1.43-2.36]) compared to non-efficient units. Units from for-profit hospitals and specialized ICUs presented the best efficiency scores. Our results were mostly in line with the efficiency matrix method: the efficiency units in our models were mostly in the "most efficient" quadrant.
conclusionData envelopment analysis provides managers the information needed to identify not only the outcomes to be achieved but what are the levels of resources needed to provide efficient care. Different perspectives can be achieved depending on the chosen variables. Its use jointly with the efficiency matrix can provide deeper understanding of ICU performance and efficiency.
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