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Title: Data envelopment analysis for measuring the efficiency of head trauma care in England and Wales
Author: Al-Rashidi, A.
ISNI:       0000 0004 5921 2630
Awarding Body: University of Salford
Current Institution: University of Salford
Date of Award: 2016
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This research develops a comprehensive model for evaluating the efficiency and productivity of the sector of head trauma injury (HTI) care in England and Wales, in order to reduce the costs associated with trauma care. After assessing the advantages and disadvantages of various efficiency measurement approaches, the data envelopment analysis (DEA) methodology is chosen for this research, including both the DEA-based Malmquist index model and the bootstrapping DEA model. Since the variables selected for these models include some missing data, the approach known as multiple imputation by chained equations (MICE) is proposed to deal with such missing data situations, in order to ensure the accuracy of the inferential and predictive results that our analyses generate. In addition, an experimental study is provided to simulate this approach, in order to investigate its validity as a methodology for replacing such missing values within DEA applications. This experimental study is based on a real data set of 66 hospitals provided by the Trauma Audit and Research Network (TARN), within Salford Royal NHS Foundation Trust. The results of this experimental study show that MICE works well and gives an acceptable estimate of true efficiency. Furthermore, this research introduces a framework that combines DEA with structural equation modelling (SEM) in order to investigate the effects of uncontrollable variables on efficiencies. While the use of DEA provides valuable results, our SEM analysis reveals additional findings that were not identified in previous studies. For example, unlike previous second stage analysis studies in DEA that focused on only the direct effects of environmental factors on the efficiency scores, this study uses SEM to investigate further any indirect effects and the total effects of these uncontrollable factors on the efficiencies. This additional information is shown to be more useful and more informative than the results generated by the previous studies. The methodologies proposed and developed in this thesis are then applied to the full set of available TARN data in order to measure the efficiency and productivity of HTI care, demonstrating real possibilities for reducing the costs of head trauma care.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available