Background: It is essential to evaluate the performance of hospitals in the health system. Hospitals need a performance evaluation system to develop and compete in order to measure the efficiency and effectiveness of their programs, processes, and human resources. This study aimed to evaluate the performance of teaching hospitals using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method and hierarchical analysis.

Materials And Methods: This was a cross-sectional and descriptive study conducted in 2019 in all teaching hospitals affiliated to Shahid Beheshti University of Medical Sciences. The required data were collected using a standard checklist. The collected data were analyzed using the analytic hierarchy process (AHP) and TOPSIS. In the first phase, annual indicators of hospital evaluation were collected. Following the AHP, key performance indicators (KPIs) were selected and prioritized in hospitals.

Results: The questionnaires were provided to 15 experts to weigh KPIs, and the most important indicators were selected. The results of hierarchical analysis showed that three main indicators in evaluating the performance of hospitals were bed turnover rate, emergency clients, and length of stay.

Conclusions: One of the problems in evaluating hospitals is the use of key indicators that alone measure the quantity or quality of their performance. Multicriteria decision-making can be used to determine key indicators first, and then by combining these indicators into a multicriteria decision-making model, a better assessment of the role and performance of hospitals can be provided.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7530430PMC
http://dx.doi.org/10.4103/jehp.jehp_89_20DOI Listing

Publication Analysis

Top Keywords

teaching hospitals
12
multicriteria decision-making
12
performance hospitals
12
performance teaching
8
hospitals
8
evaluate performance
8
key indicators
8
performance
7
indicators
7
assessment performance
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!