ArticleBioengineering (Basel, Switzerland)2021
Developing a Novel Integrated Generalised Data Envelopment Analysis (DEA) to Evaluate Hospitals Providing Stroke Care Services.
Article in Bioengineering (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed, 45 citations in OpenAlex.
- Identifying High-Risk Pre-Term Pregnancies Using the Fetal Heart Rate and Machine Learning.Bioengineering (Basel, Switzerland) · 2026Article
- The novel additive star-NDEA model for hospital performance evaluation.BMC health services research · 2025Article
- An Integrated Predictive Impact-Enhanced Process Mining Framework for Strategic Oncology Workflow Optimization: Case Study in Iran.Bioengineering (Basel, Switzerland) · 2025Article
- Construction of Diagnostic Model for Regulatory T Cell-Related Genes in Sepsis Based on Machine Learning.Biomedicines · 2025Article
- Identification of Gene Expression in Different Stages of Breast Cancer with Machine Learning.Cancers · 2024Article
- Pipeline failure evaluation and prediction using failure probability and neural network based on measured data.Heliyon · 2024Article
- The Application of Data Envelopment Analysis to Emergency Departments and Management of Emergency Conditions: A Narrative Review.Healthcare (Basel, Switzerland) · 2023Review
- Analysis of IoT Security Challenges and Its Solutions Using Artificial Intelligence.Brain sciences · 2023Review
- Predicting Overall Survival with Deep Learning from 18F-FDG PET-CT Images in Patients with Hepatocellular Carcinoma before Liver Transplantation.Diagnostics (Basel, Switzerland) · 2023Article
- Multi-Process Remora Enhanced Hyperparameters of Convolutional Neural Network for Lung Cancer Prediction.Biomedicines · 2023Article
- Evaluating Cardiac Lateralization by MRI to Simplify Estimation of Cardiopulmonary Impairment in Pectus Excavatum.Diagnostics (Basel, Switzerland) · 2023Article
- A Hybrid Machine Learning Approach to Screen Optimal Predictors for the Classification of Primary Breast Tumors from Gene Expression Microarray Data.Diagnostics (Basel, Switzerland) · 2023Article
- Planning feasible and efficient operational scenarios for a university hospital through multimethodology.Socio-economic planning sciences · 2022Article
- Home Health Care Problem with Synchronization Visits and Considering Samples Transferring Time: A Case Study in Tehran, Iran.International journal of environmental research and public health · 2022Article
- The Core of Healthcare Efficiency: A Comprehensive Bibliometric Review on Frontier Analysis of Hospitals.Healthcare (Basel, Switzerland) · 2022Review
- Dynamic Performance Assessment of Hospitals by Applying Credibility-Based Fuzzy Window Data Envelopment Analysis.Healthcare (Basel, Switzerland) · 2022Article
- Developing a Risk Reduction Support System for Health System in Iran: A Case Study in Blood Supply Chain Management.International journal of environmental research and public health · 2022Article
- A Novel Hybrid Parametric and Non-Parametric Optimisation Model for Average Technical Efficiency Assessment in Public Hospitals during and Post-COVID-19 Pandemic.Bioengineering (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stroke is the biggest cause of adult disability and the third biggest cause of death in the US. Stroke is a medical emergency, and the treatment given in the early hours is important in shaping the patient's long-term recovery and prognosis. Despite the fact that substantial attention has been dedicated to this complex and difficult issue in healthcare, novel strategies such as operation research-based approaches have hardly been used to deal with the difficult challenges associated with stroke. This study proposes a novel approach with data envelopment analysis (DEA) and multi-objective linear programming (MOLP) in hospitals that provide stroke care services to select the most efficient approach, which will be a new experiment in literature perception. DEA and MOLP are widely used for performance evaluation and efficiency measurement. Despite their similarities and common concepts, the two disciplines have evolved separately. The generalised DEA (GDEA) cannot incorporate the preferences of decision-makers (DMs) preferences and historical efficiency data. In contrast, MOLP can incorporate the DM's preferences into the decision-making process. We transform the GDEA model into MOLP through the max-ordering approach to (i) solve the problem interactively; (ii) use the step method (STEM) and consider DM's preferences; (iii) eliminate the need for predetermined preference information; and (iv) apply the most preferred solution (MPS) to identify the most efficient approach. A case study of hospitals that provide stroke care services is taken as an example to illustrate the potential application of the proposed approach method.
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.