Zhou, C; Li, R; Xiong, X; Li, J and Gao, Y (2023) Optimization of triage time and sample delivery path in health infrastructure to combat COVID-19. Engineering, Construction and Architectural Management, 30(8), pp. 3620-3644. ISSN 0969-9988
Abstract
Purpose: This study presented the experience of improving the nucleic acid sample collection and transportation service in response to the epidemic. The main purpose is that through intelligent path planning, combined with the time scheduling of sample points, the process of obtaining results to determine the state of COVID-19 patients could be speeding up. Design/methodology/approach: The research optimized the process, including finding an optimal path to traverse all sample points in the hospital area via intelligent path planning method and standardizing the operation through the time sequence scheduling of each round of support staff to collect and send samples in the hospital area, so as to ensure the shortest time in each round. And the study examines these real-time experiments through retrospective examination. Findings: The real-time experiments' data showed that the proposed path planning and scheduling model could provide a reliable reference for improving the efficiency of hospital logistics. Testing is a very important part of diagnosis and prompt results are essential. It shows the possibility of applying the shortest-path algorithms to optimize sample collection processes in the hospital and presents the case study that gives the expected outcomes of such a process. Originality/value: The value of the study lies in the abstraction of a very practical and urgent problem into a TSP. Combining the ant colony algorithm with the genetic algorithm (ACAGA), the performance of path planning is improved. Under the intervention and guidance, the efficiency of hospital regional logistics planning was greatly improved, which may be of greater benefit to critical patients who must go through fever clinic during the epidemic. By detailing how to more rapidly obtain results through engineering method, the paper contributes ideas and plans for practitioners to use. The experience and lessons learned from Tongji Hospital are expected to provide guidance for supporting service measures in national public health infrastructure management and valuable reference for the development of hospitals in other countries or regions.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | innovation; optimization; scheduling |
| Index terms: | methodology, practitioner, logistics planning, lessons learned, COVID-19, scheduling, genetic algorithm, experiment, testing, efficiency, case study, planning method, infrastructure management, public health |
| Subjects: | practitioner, data collection methods, professional practice, operations research, logistics planning, urban planning, professional development, infrastructure engineering, research methods, algorithms, performance management, health risk and incident analysis, environmental health |
| Topics: | Quality Management, Supply Chain Management, Digital Applications, Time Control, Research Practice, Information Management, Engineering Principles, Health and Safety, Sustainability, Governance, Roles and Professions |
| Descriptive scope: | 4 PCTE |
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