A Study on Improving Procurement Efficiency of Medical Consumables Based on the SPD Supply Chain Management Model

Establish a medical consumables order information management system based on the SPD model to improve distribution response efficiency and assess its impact on procurement efficiency. Method:The SPD supply chain model was implemented at a tertiary hospital in Guangzhou, focusing on the analysis of order and distribution data for 10 high-value consumables during 2023 and the first half of 2024. Key metrics analyzed included the number of orders, the quantity of consumables, and the time consumed at each stage (measured in days). Descriptive analysis was used, with measurements expressed as mean ± standard deviation (±s). Statistical analysis was performed using independent sample T-tests. Results: After the SPD implementation, the number of orders and the distribution volume increased by 23.91% and 78.14%, respectively, and the total logistics time was significantly shortened to 2.49 ± 2.05 days (T=18.745, P<0.05). The time from order placement to hospital review was reduced by 0.74 days (T=9.412, P<0.05), and the time from warehouse dispatch to hospital receipt was reduced to 1.14 ± 1.09 days (T=18.745, P<0.05). Conclusion: The implementation of SPD intelligent logistics management significantly reduced the total logistics time for high-value medical consumables procurement at Hospital Z. Future improvements can focus on optimizing supplier response capabilities, enhancing integration with hospital information systems, and expanding the scope of services to further improve medical consumables management efficiency.

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Published
2024-09-20
DOI
https://doi.org/10.1109/iiotbdsc64371.2024.00053
Primary Topic
Outsourcing and Supply Chain Management
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article

A Study on Improving Procurement Efficiency of Medical Consumables Based on the SPD Supply Chain Management Model

Jiechao Chen, Wenjia Luo, Jiehui Tan, Jiaqing Miao et al.
Outsourcing and Supply Chain Management
article

A Study on Improving Procurement Efficiency of Medical Consumables Based on the SPD Supply Chain Management Model

Jiechao Chen, Wenjia Luo, Jiehui Tan, Jiaqing Miao, Yuyao Wang, Wu Lihua, Donglan Yu
article en

Abstract

Establish a medical consumables order information management system based on the SPD model to improve distribution response efficiency and assess its impact on procurement efficiency. Method:The SPD supply chain model was implemented at a tertiary hospital in Guangzhou, focusing on the analysis of order and distribution data for 10 high-value consumables during 2023 and the first half of 2024. Key metrics analyzed included the number of orders, the quantity of consumables, and the time consumed at each stage (measured in days). Descriptive analysis was used, with measurements expressed as mean ± standard deviation (±s). Statistical analysis was performed using independent sample T-tests. Results: After the SPD implementation, the number of orders and the distribution volume increased by 23.91% and 78.14%, respectively, and the total logistics time was significantly shortened to 2.49 ± 2.05 days (T=18.745, P<0.05). The time from order placement to hospital review was reduced by 0.74 days (T=9.412, P<0.05), and the time from warehouse dispatch to hospital receipt was reduced to 1.14 ± 1.09 days (T=18.745, P<0.05). Conclusion: The implementation of SPD intelligent logistics management significantly reduced the total logistics time for high-value medical consumables procurement at Hospital Z. Future improvements can focus on optimizing supplier response capabilities, enhancing integration with hospital information systems, and expanding the scope of services to further improve medical consumables management efficiency.

Sun Yat-sen University (CN), The First Affiliated Hospital, Sun Yat-sen University (CN), Tsinghua University (CN)
Zero hunger
Openalex Percentile: Top 57%
Outsourcing and Supply Chain Management
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A Study on Improving Procurement Efficiency of Medical Consumables Based on the SPD Supply Chain Management Model — Jiechao Chen, Wenjia Luo, et al. · (2024) | TGRS Research Map | TGRS