Volume 27, Issue 3 (11-2024)
jha 2024, 27(3): 54-69 |
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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: (54 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
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