ArticleHealthcare (Basel, Switzerland)2024
Performance Evaluation of Hospitals under Data Uncertainty: An Uncertain Common-Weights Data Envelopment Analysis.
Article in Healthcare (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 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
- Evaluating hospital performance with additive DEA and MPI: the Isfahan University of Medical Science case study.BMC health services research · 2025Article
- Z-number network data envelopment analysis approach: A case study on the Iranian insurance industry.PloS one · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the context of healthcare systems, the performance evaluation of hospitals plays a crucial role in assessing the quality of healthcare systems and facilitating informed decision-making processes. However, the presence of data uncertainty poses significant challenges to accurate performance measurement. This paper presents a novel uncertain common-weights data envelopment analysis (UCWDEA) approach for evaluating the performance of hospitals under uncertain environments. The proposed UCWDEA approach addresses the limitations of traditional data envelopment analysis (DEA) models by incorporating the uncertainty theory (UT) to model the inherent uncertainty in input and output data. Also, by utilizing a common set of weights (CSW) technique, the UCWDEA method provides a more robust and reliable assessment of hospital performance. The main advantages of the proposed UCWDEA approach can be succinctly summarized as follows. Firstly, it allows for the comparison of all hospitals on a consistent basis to calculate a realistic efficiency score, rather than an overly optimistic efficiency score. Secondly, the uncertain common-weights DEA approach exhibits linearity, enhancing its applicability. Thirdly, it possesses the capability to extend its utility under various other prevalent uncertainty distributions. Moreover, it enhances the discriminatory power of results, facilitates the ranking of hospitals in the presence of data uncertainty, and aids in identifying the sensitivity and stability levels of hospitals towards data uncertainty. Notably, in order to showcase the pragmatic application and efficacy of the uncertain common-weights DEA model, a genuine dataset has been utilized to evaluate the efficiency of 20 public hospitals in Tehran, all of which are affiliated with the Iran University of Medical Sciences. The results of the experiment demonstrate the efficacy of the UCWDEA approach in assessing and ranking hospitals amidst uncertain conditions. In summary, the research outcomes can offer policymakers valuable insights regarding hospital performance amidst data uncertainty. Additionally, it can provide practical recommendations on optimizing resource allocation, benchmarking performance, and formulating effective policies to augment the overall efficiency and effectiveness of healthcare services.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.