An integrated approach to evaluate the performance of psychiatric hospitals with the spotlight of ergonomics and job satisfaction

Abstract

This study examines the performance of psychiatric hospitals in response to Covid-19 pandemic. The fragility of mental health because of pandemic pressurized psychiatric hospitals more than ever. Data Envelopment Analysis (DEA) is applied as a method of performance measurement with the micro and macro ergonomics and job satisfaction indicators. In this manner, at first, we identified all the investigated sub-indices, then, after designing and distributing a standard questionnaire among the employees of psychiatric hospitals, we calculated the efficiency of the hospitals through the optimal DEA model. Accordingly, relying on the results of sensitivity analysis and statistical tests, we studied the impact of each indicator on the performance of hospitals and identified their strengths and weaknesses. Finally, we checked the validity of the optimal DEA model by comparing its results with the Multilayer Perception (MLP) network results that is most utilized type of artificial neural network (ANN) method.

Keywords

• Performance evaluation
• Data envelopment analysis
• Artificial neural network
• psychiatric hospitals
• Ergonomics
• Job satisfaction

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