A Hybrid Analytic Hierarchy Process and Likert Scale Approach for the Quality Assessment of Medical Education Programs

Alfonso Maria Ponsiglione, Francesco Amato, Santolo Cozzolino, Giuseppe Russo, Maria Romano and Giovanni Improta
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Alfonso Maria Ponsiglione: Department of Electrical Engineering and Information Technology, University of Naples “Federico II”, 80125 Naples, Italy
Francesco Amato: Department of Electrical Engineering and Information Technology, University of Naples “Federico II”, 80125 Naples, Italy
Santolo Cozzolino: U.O.C. Formazione, Ricerca e Cooperazione Internazionale, National Hospital A.O.R.N. “A. Cardarelli”, 80131 Naples, Italy
Giuseppe Russo: National Hospital A.O.R.N. “A. Cardarelli”, 80131 Naples, Italy
Maria Romano: Department of Electrical Engineering and Information Technology, University of Naples “Federico II”, 80125 Naples, Italy
Giovanni Improta: Interdepartmental Center for Research in Healthcare Management and Innovation in Healthcare (CIRMIS), University of Naples “Federico II”, 80125 Naples, Italy

Mathematics, 2022, vol. 10, issue 9, 1-20

Abstract: The quality assessment of training courses is of utmost importance in the medical education field to improve the quality of the training. This work proposes a hybrid multicriteria decision-making approach based on two methodologies, a Likert scale (LS) and the analytic hierarchy process (AHP), for the quality assessment of medical education programs. On one hand, the qualitative LS method was adopted to estimate the degree of consensus on specific topics; on the other hand, the quantitative AHP technique was employed to prioritize parameters involved in complex decision-making problems. The approach was validated in a real scenario for evaluating healthcare training activities carried out at the Centre of Biotechnology of the National Hospital A.O.R.N. “A. Cardarelli” of Naples (Italy). The rational combination of the two methodologies proved to be a promising decision-making tool for decision makers to identify those aspects of a medical education program characterized by a lower user satisfaction degree (revealed by the LS) and a higher priority degree (revealed by the AHP), potentially suggesting strategies to increase the quality of the service provided and to reduce the waste of resources. The results show how this hybrid approach can provide decision makers with helpful information to select the most important characteristics of the delivered education program and to possibly improve the weakest ones, thus enhancing the whole quality of the training courses.

Keywords: medical education; analytic hierarchy process; Likert scale; multicriteria decision making (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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