A Novel Hybrid Parametric and Non-Parametric Optimisation Model for Average Technical Efficiency Assessment in Public Hospitals during and Post-COVID-19 Pandemic

Mirpouya Mirmozaffari; Reza Yazdani; Elham Shadkam; Seyed Mohammad Khalili; Leyla Sadat Tavassoli; Azam Boskabadi

doi:10.3390/bioengineering9010007

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). 2021 Dec 27;9(1):7. doi: 10.3390/bioengineering9010007.

Authors

Mirpouya Mirmozaffari¹, Reza Yazdani², Elham Shadkam³, Seyed Mohammad Khalili³, Leyla Sadat Tavassoli⁴, Azam Boskabadi⁵

Affiliations

¹ Department of Industrial Engineering, Dalhousie University, 5269 Morris Street, Halifax, NS B3H 4R2, Canada.
² Department of Accounting, Technical and Vocational University (TVU), Tehran 1345120727, Iran.
³ Department of Industrial Engineering, Faculty of Engineering, Khayyam University, Mashhad 9189747178, Iran.
⁴ Department of Industrial Manufacturing and Systems Engineering, University of Texas at Arlington, Arlington, TX 76019, USA.
⁵ Department of Finance and Management Science, Carson College of Business, Washington State University, Pullman, WA 99163, USA.

Abstract

The COVID-19 pandemic has had a significant impact on hospitals and healthcare systems around the world. The cost of business disruption combined with lingering COVID-19 costs has placed many public hospitals on a course to insolvency. To quickly return to financial stability, hospitals should implement efficiency measure. An average technical efficiency (ATE) model made up of data envelopment analysis (DEA) and stochastic frontier analysis (SFA) for assessing efficiency in public hospitals during and after the COVID-19 pandemic is offered. The DEA method is a non-parametric method that requires no information other than the input and output quantities. SFA is a parametric method that considers stochastic noise in data and allows statistical testing of hypotheses about production structure and degree of inefficiency. The rationale for using these two competing approaches is to balance each method's strengths, weaknesses and introduce a novel integrated approach. To show the applicability and efficacy of the proposed hybrid VRS-CRS-SFA (VCS) model, a case study is presented.

Keywords: COVID-19; artificial intelligence; average technical efficiency; data envelopment analysis; parametric and non-parametric models; public hospitals.