Vol: 15, Issue: 4 2025

Page: 85-103

The Economic Role of the Accounting Information Systems in Optimizing Resource Management in Dental Clinics in Iraq

Hussein Ali Saad Alsrai, Thaer Najm Kadhim, Eyad Abd Al-Sayed Aneen

Received Date: 2025-10-18

Accepted Date: 2025-12-03

Published Date: 2025-12-07

http://doi.org/10.37648/ijtbm.v15i04.006

The Cost and resource organization is one of the major problems of dentistry clinics in the 21st century. This article elaborates an economic link between Accounting Information Systems (AIS) and dental practice, with a particular focus on resource allocation dimension. Statistical analysis of 75 clinics was performed employing descriptive statistics and multiple linear regression models to understand which aspects might improve clinical macroeconomic performance. The bottom line is that clinic economic performance is largely determined by five determinants, the biggest of which were innovation and growth, resource allocation, economic productivity, financial sustainability, and economic efficiency. The amount of accounting information systems use and return on investment (ROI) would not have a direct and significant effect on the model, which means indirectly that the economics of Accounting Information Systems can be realized if the organizational and operational aspects are enhanced. This means spending on accounting information system must be implemented as part of an overall transformation plan covering process redesign and human resources training to be able to achieve sustainable efficiency and return gains from the investment.

References

• Adedoyin Ezenwoke, O., Ezenwoke, A., Eluyela, F. D., & Olusanmi, O. (2019). A bibliometric study of accounting information systems research from 1975–2017.
• Alaghemandan, H., Yarmohammadian, M. H., Khorasani, E., & Rezaee, S. (2014). Efficiency improvement of dentistry clinics: Introducing an intervening package for dentistry clinics, Isfahan, Iran.
• Alfiah, A., Bakri, A. A., Fatimah, F., & Syahdan, R. (2023). Capability to manage financial reports for MSMEs utilizing accounting information systems.
• Ali, M. A. (2024). The role of artificial intelligence in modern dentistry: Applications, challenges, and future directions.
• Ayatollahi, H., Nazemi, Z., & Haghani, H. (2016). Patient accounting systems: Are they fit with the users’ requirements?
• Bennett, C. (2012). Clinical productivity system – A decision support model.
• Baltazar, E. G. (2019). Análisis y evaluación de una política de inventario para reducir los costos de aprovisionamiento de una MiPyME de servicios dentales.
• Cinquini, L., & Campanale, C. (1970). Il costo dell’intervento chirurgico in laparoscopia con l’Activity Based Costing.
• Carlos Vargas Zambrano, J. (2016). Desarrollo de un sistema de inventarios para dispositivos médicos en la empresa dental Nader S.A.S.
• De Fagbemi, O. T., & Olaoye, J. A. (2016). Evaluation of accounting information system and performance of SMEs in Kwara State.
• Edith Gutiérrez Baltazar, B. (2019). Análisis y evaluación de una política de inventario para reducir los costos de aprovisionamiento de una MiPyME de servicios dentales.
• Fahmi, M., Muda, I., & Kesuma, S. A. (2022). Implementation of internal control procedures that enable cost savings in dealing with threats cycles: Revenue cycle.
• Finkbeiner, B. L., Finkbeiner, C. A., & Koberna, L. (2025). Practice management for the dental team.
• Fu, L. (2015). The value of integrated information systems for U.S. general hospitals.
• Goh, W. P., Tao, X., Zhang, J., & Yong, J. (2016). Decision support systems for adoption in dental clinics: A survey.
• Gutiérrez Baltazar, B. E. (2019). Análisis y evaluación de una política de inventario... (duplicate reference removed; retained once above)
• Haryaningsih, S., Elyta, E., & Nikodimus, N. (2023). Benefits of accounting information systems to improve service quality at Regional General Hospital Dr. Agoesdjam Ketapang District.
• Irwin, J. Y., Torres-Urquidy, M. H., Schleyer, T., & Monaco, V. (2009). A preliminary model of work during initial examination and treatment planning appointments.
• Jacques, N. (2025). Analyzing the role of health investments in driving economic growth: Evidence from Rwanda.
• Jha, K., Mandal, Y., Jnaneswar, A., Kumar, G., Suresan, V., & Singh, A. (2021). Teledentistry and advancements in traditional dental care.
• Kalavani, K., & Akhondzardaini, R. (2024). Investigating dental challenges in developing countries based on the WHO functional dimensions model.
• Laourou, A. B. F. (2025). Adoption and implementation of data mining in AIS within the Nigerian public sector.
• Li, Y. (2023). The application of hospital investment decision-making and financial analysis methods.
• Lyu, J. C., Han, E. L., & Luli, G. K. (2021). COVID-19 vaccine–related discussion on Twitter: Topic modeling and sentiment analysis.
• Marcu, M., Hedesiu, M., Bogdan, L., Armencea, G., et al. (2020). Financial efficiency estimation for a dental radiology laboratory.
• Meiyana, N. S., Susanto, T., Rokhmah, D., Yunanto, R. A., Rahmawati, I., & Hernawati, S. Analysis of hospital management information system satisfaction using the EUCS method.
• Neiroukh, S., Emeagwali, O. L., & Aljuhmani, H. Y. (2024). AI capability and organizational performance: Mediating mechanisms of decision-making processes.
• Nour, Q., Azzaldeen, A., Mai, A., & Muhamad, A. H. (2024). Digital technologies in dentistry.
• Pheng Goh, W., Tao, X., Zhang, J., & Yong, J. (2016). Decision support systems for adoption in dental clinics: A survey.
• Pirskanen, J. (2018). Dental health care technologies: Factors affecting technology adoption and latest IT solutions.
• Rahayu, R. N., & Rifandi, M. (2023). Accounting information system performance in hospital: A case study.
• Rauscher, S. (2010). Revenue cycle management in the U.S. hospital industry.
• Schwendicke, F., & Krois, J. (2022). Data dentistry: How data are changing clinical care and research.
• Sunitha, D., Patra, R. K., Babu, N. V., et al. (2022). Twitter sentiment analysis using ensemble-based deep learning model towards COVID-19 in India and European countries.
• Tajul Urus, S., Hasim, K., Nazri, N. F. S., & Zainun, T. M. (2020). Critical success factors of AIS: Evidence from Malaysian organizations.
• Tilahun, M. (2018). Determinants of computerized AIS adoption by hospitals in Addis Ababa. (Duplicate entry removed; retained once)
• Vasileiou, A., Sfakianaki, E., & Tsekouropoulos, G. (2024). Sustainability and efficiency improvements in healthcare: A qualitative study.
• Wager, K. A., Lee, F. W., & Glaser, J. P. (2021). Health care information systems: A practical approach for health care management
• Weinstein, M. (2006). Recent developments in decision-analytic modelling for economic evaluation.
• Wolff, J., Pauling, J. K., Keck, A., & Baumbach, J. (2020). The economic impact of AI in healthcare: A systematic review.