TY - JOUR
T1 - How to improve the digital management level of medical waste through “digital technology and business data”?
AU - Liu, Hao
AU - Yan, Zhijun
N1 - Publisher Copyright:
© 2025 Emerald Publishing Limited
PY - 2025
Y1 - 2025
N2 - Purpose – The difficulty of medical waste management lies in data management. Digital technology can improve the digital management ability of medical waste, and data are the core. But what are the key data of medical waste itself and its business processes, such as generation, collection, classification, weighing, packaging, storage and transportation? How to integrate digital technology with business data to drive the digital management of hospital medical waste? These are the main research purposes. Design/methodology/approach – Business Process Reengineering and Data-Driven Decision-Making are the theoretical method bases. The business process of medical waste recycling and classification was restructured and divided into four business links. The attribute characteristics of medical waste and the key data indicators of each business link were determined. Meanwhile, the composition of business data flow is analyzed, and how to deeply integrate Radio Frequency Identification (RFID), sensors and other digital technologies with data flow to optimize business process is discussed. Findings – The improvement of the digital management level of medical waste, on the one hand, requires the use of RFID, sensors and other digital technologies to reconstruct business processes to achieve the automation and intelligence of recycling and classification. On the other hand, the key business data types and index characteristics need to be refined to form data sets and transform them into data assets to provide support for medical waste management decisions. Originality/value – This study constructed a dual-driven mode of “Digital technology and Business data”, which provided technical application scenarios and theoretical methods for digital management of medical waste.
AB - Purpose – The difficulty of medical waste management lies in data management. Digital technology can improve the digital management ability of medical waste, and data are the core. But what are the key data of medical waste itself and its business processes, such as generation, collection, classification, weighing, packaging, storage and transportation? How to integrate digital technology with business data to drive the digital management of hospital medical waste? These are the main research purposes. Design/methodology/approach – Business Process Reengineering and Data-Driven Decision-Making are the theoretical method bases. The business process of medical waste recycling and classification was restructured and divided into four business links. The attribute characteristics of medical waste and the key data indicators of each business link were determined. Meanwhile, the composition of business data flow is analyzed, and how to deeply integrate Radio Frequency Identification (RFID), sensors and other digital technologies with data flow to optimize business process is discussed. Findings – The improvement of the digital management level of medical waste, on the one hand, requires the use of RFID, sensors and other digital technologies to reconstruct business processes to achieve the automation and intelligence of recycling and classification. On the other hand, the key business data types and index characteristics need to be refined to form data sets and transform them into data assets to provide support for medical waste management decisions. Originality/value – This study constructed a dual-driven mode of “Digital technology and Business data”, which provided technical application scenarios and theoretical methods for digital management of medical waste.
KW - Business data
KW - Business process
KW - Digital management
KW - Digital technology
KW - Medical waste
UR - https://www.scopus.com/pages/publications/105024567134
U2 - 10.1108/IMDS-11-2024-1176
DO - 10.1108/IMDS-11-2024-1176
M3 - Article
AN - SCOPUS:105024567134
SN - 0263-5577
SP - 1
EP - 27
JO - Industrial Management and Data Systems
JF - Industrial Management and Data Systems
ER -