An intelligent algorithm for optimizing emergency department job and patient satisfaction
International Journal of Health Care Quality Assurance
ISSN: 0952-6862
Article publication date: 11 June 2018
Abstract
Purpose
Resilience engineering, job satisfaction and patient satisfaction were evaluated and analyzed in one Tehran emergency department (ED) to determine ED strengths, weaknesses and opportunities to improve safety, performance, staff and patient satisfaction. The paper aims to discuss these issues.
Design/methodology/approach
The algorithm included data envelopment analysis (DEA), two artificial neural networks: multilayer perceptron and radial basis function. Data were based on integrated resilience engineering (IRE) and satisfaction indicators. IRE indicators are considered inputs and job and patient satisfaction indicators are considered output variables. Methods were based on mean absolute percentage error analysis. Subsequently, the algorithm was employed for measuring staff and patient satisfaction separately. Each indicator is also identified through sensitivity analysis.
Findings
The results showed that salary, wage, patient admission and discharge are the crucial factors influencing job and patient satisfaction. The results obtained by the algorithm were validated by comparing them with DEA.
Practical implications
The approach is a decision-making tool that helps health managers to assess and improve performance and take corrective action.
Originality/value
This study presents an IRE and intelligent algorithm for analyzing ED job and patient satisfaction – the first study to present an integrated IRE, neural network and mathematical programming approach for optimizing job and patient satisfaction, which simultaneously optimizes job and patient satisfaction, and IRE. The results are validated by DEA through statistical methods.
Keywords
Acknowledgements
Unfortunately, Professor Ali Azadeh died before this paper was published. Ali Azadeh was an Eminent University Professor and the Department of Industrial Engineering Founder. Ali Azadeh co-found the Research Institute of Energy Management and Planning, Tehran University. Ali Azadeh received the 1992 Phi Beta Kappa Alumni Award for excellence in research and innovation for the doctoral dissertation in the USA. Ali Azadeh was also the recipient of National Eminent Researcher Award in Iran. Professor Azadeh published more than 700 papers in reputable academic journals and conference proceedings. This study was supported by grants from Tehran University (No. 8106013/1/20) and INSF (No. 94002128). The authors are grateful for the support provided by the College of Engineering staff, Tehran University, Iran.
Citation
Azadeh, A., Yazdanparast, R., Abdolhossein Zadeh, S. and Keramati, A. (2018), "An intelligent algorithm for optimizing emergency department job and patient satisfaction", International Journal of Health Care Quality Assurance, Vol. 31 No. 5, pp. 374-390. https://doi.org/10.1108/IJHCQA-06-2016-0086
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited