A Knowledge Management System for the Variation in Regional Clinical Pathways of Traditional Chinese Medicine Based on Smart Cloud Services
Author(s) -
Xiaoying Hu,
Jiali Liu,
Shuwu Li,
Kai Li
Publication year - 2019
Publication title -
revue d intelligence artificielle
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.146
H-Index - 14
eISSN - 1958-5748
pISSN - 0992-499X
DOI - 10.18280/ria.330602
Subject(s) - variation (astronomy) , cloud computing , service (business) , service system , warning system , management system , computer science , knowledge management , business , operations management , engineering , telecommunications , marketing , physics , astrophysics , operating system
Received: 10 May 2019 Accepted: 18 September 2019 This paper aims to provide an effective solution to the variation in clinical pathways (CPs) of traditional Chinese medicine (TCM). First, a semi-structured interview was carried out among stakeholders, such as system research and design (R&D) engineers, Chinese medicine hospital managers, medical staff, patients and health bureau officials. Their demand on the knowledge management system (KMS) for TCM CPs variation was summarized through the interview. In the light of the user demand, the author designed a novel KMS for variation in regional TCM CPs (KMS-TCMCPV) based on smart cloud services. The proposed system consists of four modules: variation warning service, variation intervention service, patient-oriented smart service, and smart cloud service. The architecture and implementation of each service were explained in details. The proposed system effectively overcomes the defects of the previous system, such as the lack of variation warning, the limited feedback channel, and the inability to share empirical knowledge. Our system successfully enhances the diagnosis and treatment of Chinese medicine hospitals, and improves the patient satisfaction.
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