The Impact of Hospital Demographic Factors on Total Quality Management Implementation: A Case Study of UAE Hospitals
DOI:
https://doi.org/10.11576/seejph-5758Keywords:
Total Quality Management, Quality Improvement Strategy, Hospital Service Quality, Hospital Size, Hospital Demographic Factors, Binary Logical Regression ModelAbstract
Aim: Maintaining service quality and value using quality and management tools is crucial in any organization. In essence, improving service quality boosts both efficiency of organizations and consumer pleasure. The deployment of quality development programs such as Total Quality Management (TQM) is one technique that businesses may employ to deliver exceptional customer service. The health sector, in particular, is one of the industries that require TQM adoption due to its complexity and the need for constant service improvement. TQM helps to improve service quality in health facilities through advanced clinical and administrative procedures. This research comprehensively assesses TQM levels and the impact of hospital demographics on its implementation process in hospitals in the United Arab Emirates (UAE).
Methods: The study used a quantitative research strategy based on a survey study design. Questionnaires were used to gather primary data from respondents deployed a self-administered technique. 1850 questionnaires were delivered to the hospital's senior staff based on their number in each hospital. Of the 1850 questionnaires distributed, 1238 usable questionnaires were analyzed, yielding a response rate of 66.9%. The study used a binary logistic regression model to determine if hospital demographics affected TQM implementation. The study data were examined and analysed using version 25.0 of the SPSS software.
Results: The results show that most of the health facilities with an overall TQM between 4.12 and 4.82 were utilized, governmental, accredited and utilized and large hospitals, while the hospitals with a mean between 2.91 and 3.45 were small, unaccredited private, and non-specialised. Thus, large hospitals have a higher TQM utilization rate than small hospitals. In addition, the findings of the t-test revealed that a high TQM is represented by means of 4.68, 4.67, 4.43, and 4.12 for accredited, utilized, governmental and large hospitals. The binary regression analysis also reveals similar results: large, governmental, utilized and accredited hospitals have greater chances of TQM adoption than other categories of hospitals (Exp (B): 1.2; 95%CI: 1.001 – 1.421, P< .05); (Exp (B): 1.3; 95%CI: 1.012 – 1.721, P< .05); (Exp (B): 1.5; 95%CI: 1.127 – 2.051, P< .01); and (Exp
(B): 1.5; 95%CI: 1.102 – 2.012, P< .05); correspondingly. Another observation from the results is that hospitals that implemented technological tools had a greater chance of successfully executing the TQM program than hospitals that did not utilize advanced technologies due to the limited availability of resources (Exp (B): 1.7; 95%CI: 1.332 – 2.187, P< .01).
Conclusion: Even though health facilities need to adopt TQM, its implementation depends on the hospital size and demographics that significantly influence the adoption of TQM programs. However, this study will help bridge the current gap on the usage of TQM in the health context by examine the influence of demographic factors on adopting TQM in hospitals. Hence, provide adequate information to help the UAE hospital administrators appropriately execute the TQM program in the hospitals and enhance the efficacy of their operations.
Conflict of interest: None declared
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Shaima Aljasmi, Ihssan Aburayya, Sameeha Almarzooqi, Maryam Alawadhi, Ahmad Aburayya, Said A. Salloum, Khalid Adel
This work is licensed under a Creative Commons Attribution 4.0 International License.