A Predictive Framework for Efficient Resources Allocation in Healthcare Organisations

• Published in: 2023 24th International Conference on Control Systems and Computer Science (CSCS) pp. 249 - 252
• Main Authors: Coman, Gabriela, Mocanu, Stefan, Dobrescu, Radu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2023
• Subjects: Adaptive systems; complex adaptive system; Complexity theory; Costs; decision making; healthcare; integrated management system; Medical services; Neural networks; Organizations; personalized healthcare; predictive; resources; Standards organizations
• ISSN: 2379-0482
• DOI: 10.1109/CSCS59211.2023.00046

In today's dynamic healthcare environment an efficient allocation of healthcare resources is essential for overall positive outcomes of healthcare processes and patient's satisfaction. A preliminary stage for moving towards an efficient allocation of resources is the existence of an Integrated Management System (IMS) in the healthcare organizations. An IMS consist in a series of requirements on different areas that are mandatory to be implemented.Different modeling tools have been developed to improve the current state of healthcare processes. Those models can aid the decision-making process for allocation of healthcare resources and reduce costs. The purpose of this article is to present a predictive framework for efficient allocation in the healthcare system organization with implemented IMS. Type of resources relevant in the proposed framework were selected based on Pareto's rule. The aim of the predictive framework is to support better allocation and management of healthcare resources, which is critical for reliable healthcare outcomes. The framework integrates value-based concepts and it is focused on finding balance between process performance and cost.