Volume 27, Issue 3 (11-2024)
jha 2024, 27(3): 54-69 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Kheradranjbar M, Khamseh A, Iranban fard S J. Evaluation of health services portfolio management based on information technology using adaptive neuro-fuzzy inference approach. jha 2024; 27 (3) :54-69
URL: http://jha.iums.ac.ir/article-1-4483-en.html
URL: http://jha.iums.ac.ir/article-1-4483-en.html
1- Department of Technology Management, Faculty of Management and Economics, Science and Research Unit, Islamic Azad University, Tehran
2- Department of Industrial Management, Karaj Branch, Islamic Azad University, Karaj ,abbas.khamseh@kiau.ac.ir
3- Department of Management, Shiraz Branch, Islamic Azad University, Shiraz
2- Department of Industrial Management, Karaj Branch, Islamic Azad University, Karaj ,
3- Department of Management, Shiraz Branch, Islamic Azad University, Shiraz
Abstract: (109 Views)
Introduction: In the dynamic landscape of healthcare management, efficient portfolio management of IT-based health service projects is essential for optimizing resource allocation, mitigating risks, and improving outcomes. This research examines the importance of forecasting and evaluating portfolio management practices in healthcare services, considering growing dependence on information technology to drive innovation and efficiency in service delivery. The main objective was to examine the dimensions and components affecting portfolio management in IT-based health service projects, using an adaptive neuro-fuzzy inference system.
Methods: The research was conducted in two key stages. First, a meta-synthesis analysis was conducted to extract key dimensions and components affecting portfolio management in healthcare IT projects. Subsequently, the identified components were evaluated using an adaptive neuro-fuzzy inference system (ANFIS) to prioritize their importance.
Results: The findings highlight critical factors affecting portfolio management. At the macro level, these include information technology management, cultural factors, and health information technology management. At the micro level, significant components include research and development (R&D) management, project portfolio management, and financial management.
Conclusion: This research provides valuable insights into the multi-level factors shaping portfolio management in IT-based healthcare projects. By understanding and prioritizing these factors, healthcare organizations can enhance their portfolio management strategies, optimize resource allocation, and ultimately improve quality of healthcare services.
Methods: The research was conducted in two key stages. First, a meta-synthesis analysis was conducted to extract key dimensions and components affecting portfolio management in healthcare IT projects. Subsequently, the identified components were evaluated using an adaptive neuro-fuzzy inference system (ANFIS) to prioritize their importance.
Results: The findings highlight critical factors affecting portfolio management. At the macro level, these include information technology management, cultural factors, and health information technology management. At the micro level, significant components include research and development (R&D) management, project portfolio management, and financial management.
Conclusion: This research provides valuable insights into the multi-level factors shaping portfolio management in IT-based healthcare projects. By understanding and prioritizing these factors, healthcare organizations can enhance their portfolio management strategies, optimize resource allocation, and ultimately improve quality of healthcare services.
Keywords: Portfolio management, Research and development, Information technology, Adaptive neuro-fuzzy inference system
Type of Study: Research |
Subject:
Health Information Management
Received: 2024/03/29 | Accepted: 2025/05/22 | Published: 2025/06/8
Received: 2024/03/29 | Accepted: 2025/05/22 | Published: 2025/06/8
References
1. Zayas-Cabán T, Okubo TH, Posnack S. Priorities to accelerate workflow automation in health care. Journal of the American Medical Informatics Association. 2023;30(1):195-201. [DOI:10.1093/jamia/ocac197]
2. Crisan EL, Mihaila A. Health-care information systems adoption - a review of management practices. Vilakshan-XIMB Journal of Management. 2023;20(1):130-139. [DOI:10.1108/XJM-04-2021-0121]
3. Sheikh A, Anderson M, Albala S, Casadei B, Franklin BD, Richards M, et al. Health information technology and digital innovation for national learning health and care systems. Lancet Digital Health. 2021;3(6):e383-e396. [DOI:10.1016/S2589-7500(21)00005-4]
4. Yang CH, Hsu W, Wu YL. A hybrid multiple-criteria decision portfolio with the resource constraints model of a smart healthcare management system for public medical centers. Socio-Economic Planning Sciences. 2022;80:101073. [DOI:10.1016/j.seps.2021.101073]
5. Alzghaibi H, Alharbi AH, Mughal YH, Alwheeb MH, Alhlayl AS. Assessing primary health care readiness for large-scale electronic health record system implementation: project team perspective. Health Informatics Journal. 2023;29(1). doi:10.1177/14604582231152790 [DOI:10.1177/14604582231152790]
6. Saito K, Shofer FS, Saberi P, Green McKenzie J. Health care personnel perception of the privacy of electronic health records. Journal of Occupational and Environmental Medicine. 2017;59(6):535-8. [DOI:10.1097/JOM.0000000000001016]
7. Alolayyan M, Al-Rwaidan R, Hamadneh S, Ahmad A, AlHamad A, Al-Hawary S, et al. The mediating role of operational flexibility on the relationship between quality of health information technology and management capability. Uncertain Supply Chain Management. 2022;10(4):1131-1140. [DOI:10.5267/j.uscm.2022.8.014]
8. Tahvildarzadeh M, Zamani Z, Khani Yusefabad F. Electronic health and its role in delivering healthcare services. In: 19th International Conference on Information Technology, Computer, and Telecommunications; 2023. [In Persian] Available from: https://civilica.com/doc/1712775
9. Haji Ali Asgari F, Tabatabaeian H, Taghva MR, Abolhasani F. Development policies in health organizations: a maturity model for implementing ITIL. Iranian Journal Public Policy. 2018;3(4):29-50. doi:10.22059/ppolicy.2018.65590
10. Mahdavi A, Ebrahimi K, Mehrtak M, Mashoufi M. Scientific mapping of new developments in health information technology based on WoS articles: 2010-2017. Journal of Paramedical Sciences Rehabilitation. 2021;9(4):27-40. doi:10.22038/jpsr.2021.47200.2091
11. Sittig DF, Wright A, Coiera E, et al. Current challenges in health information technology-related patient safety. Health Informatics Journal. 2020;26(1):181-189. https://10.1177/1460458218814893 [DOI:10.1177/1460458218814893]
12. Salman A, Fakhraldeen S, Chun S, Jamil K, Gasana J, Al-Hunayan A. Enhancing research and development in the health sciences as a strategy to establish a knowledge-based economy in the state of Kuwait: A call for action. Journal of Healthcare. 2020;8(3):264. https://doi:10.3390/healthcare8030264 [DOI:10.3390/healthcare8030264]
13. Sandelowski M, Barroso J. Handbook for synthesizing qualitative research. New York: Springer Publishing Company; 2007.
14. Abraham A. Adaptation of fuzzy inference system using neural learning, studies in fuzziness and soft computing. Fuzzy System Engineering. 2005;181:53-83. [DOI:10.1007/11339366_3]
15. Azar A, Faraji H. Fuzzy management science. 5th ed. Tehran: Ketab Mehraban Publishing; 2016. [In Persian].
16. Pinheiro Gondim de Violoncellos E, Nunes Muritiba S, Muller Affonso Prado S, Dalva Caparroz Vancetto M, Morilha Muritiba P. Analyzing R&D projects on health products. INMR - Innovation Management Review. 2016:199-210. Available from: https://www.redalyc.org/pdf/973/97347030006.pdf [DOI:10.1016/j.rai.2016.06.001]
17. Katz A, Salamanca-Buentello R, Silva F, Diego S. R&D during public health emergencies: the value(s) of trust, governance and collaboration. BMJ Global Health. 2022;7(2):63-92. [DOI:10.1136/bmjgh-2021-007873]
18. Wissenburg R, Kusters R, Martin H. Relationships between IT Project Portfolio risk and IT Project portfolio health. In: 2023 IEEE 25th Conference on Business Informatics (CBI); 2023; Prague, Czech Republic. p. 1-10. doi:10.1109/CBI58679.2023.10187481. [DOI:10.1109/CBI58679.2023.10187481]
19. Abedi S, Hamidi F, Sanaei MR. Designing a fuzzy artificial intelligence system for selecting health technology in the foresight process. Journal of Future Studies Management. 2022; [cited 2025 Jan 24]. [In Persian]. Available from: [DOI:10.30495/jmfr.2022.20262]
20. Aghajanian S, Tabaian SK, Radfar R, Seyed Hossieni SM. Conceptual framework of the capabilities of open innovation project managers. Innovation Management in Defensive Organizations. 2021;3(4):1-28. doi: 10.22034/qjimdo.2020.218255.1266
21. Derakhshan S, Dalvi MR, Dehghan M. Project portfolio management and information technology projects. Health Information Management. 2015;12(2):150-161. Available from: https://him.mui.ac.ir/article_11399.html?lang=en
22. Baigi M, Morténius H, Amir. Promoting the creation of R&D intentions in primary healthcare measured by a validated instrument. Health Research Policy and Systems. 2019;17:107. [DOI:10.1186/s12961-019-0513-3]
23. Mikhailova D. Quality management system for R&D project and portfolio management in pharmaceutical company. In: Schweizer L, Dingermann T, Russe O, Jansen C, editors. Advances in pharma business management and research. Cham: Springer; 2020. [DOI:10.1007/978-3-030-35918-8_3]
24. Terry RF, Yamey G, Miyazaki-Krause R. Funding global health product R&D: The Portfolio-To-Impact Model (P2I), a new tool for modelling the impact of different research portfolios. Gates Open Research. 2018;6:2-24. [DOI:10.12688/gatesopenres.12816.2]
25. Biranvand A, Samadbeik M, Khasseh A. Mapping of knowledge structure in the field of health information management and technology: a co-word analysis. Depiction Health. 2020;11(2):117-136. [DOI:10.34172/doh.2020.13]
26. Provost LP, Murray SK. The health care data guide: learning from data for improvement. Hoboken: John Wiley & Sons; 2022.
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
Site Keywords
Health, Administration, Scientific Article, Iran University of Medical Sciences,
