Constructing a Traditional Chinese Medicine Data Warehouse Application
📝 Abstract
The explosive growth in the development of Traditional Chinese Medicine (TCM) has resulted in the continued increase in clinical and research data. The lack of standardised terminology, flaws in data quality planning and management of TCM informatics are preventing clinical decision-making, drug discovery and education. This paper argues that the introduction of data warehousing technologies to enhance the effectiveness and durability in TCM is paramount. To showcase the role of data warehousing in the improvement of TCM, this paper presents a practical model for data warehousing with detailed explanation, which is based on the structured electronic records, for TCM clinical researches and medical knowledge discovery.
💡 Analysis
The explosive growth in the development of Traditional Chinese Medicine (TCM) has resulted in the continued increase in clinical and research data. The lack of standardised terminology, flaws in data quality planning and management of TCM informatics are preventing clinical decision-making, drug discovery and education. This paper argues that the introduction of data warehousing technologies to enhance the effectiveness and durability in TCM is paramount. To showcase the role of data warehousing in the improvement of TCM, this paper presents a practical model for data warehousing with detailed explanation, which is based on the structured electronic records, for TCM clinical researches and medical knowledge discovery.
📄 Content
Australasian Conference on Information Systems
Lam, Sahama, Gajanayake 2015, Adelaide
Constructing TCM DW Application
CONSTRUCTING A TRADITIONAL CHINESE MEDICINE
DATA WAREHOUSE APPLICATION
Wing-Kit Sunny Lam
School of Electrical Engineering and Computer Science,
Science and Engineering Faculty
Queensland University of Technology (QUT)
Brisbane, Australia
Email: wingkit.lam@connect.qut.edu.au
Tony Sahama
School of Electrical Engineering and Computer Science,
Science and Engineering Faculty
Queensland University of Technology (QUT)
Brisbane, Australia
Email: t.sahama@qut.edu.au
Randike Gajanayake
SMS Management & Technology
Brisbane, Australia
Email: randike.gajanayake@gmail.com
Abstract
The explosive growth in the development of Traditional Chinese Medicine (TCM) has resulted in the
continued increase in clinical and research data. The lack of standardised terminology, flaws in data
quality planning and management of TCM informatics are preventing clinical decision-making, drug
discovery and education. This paper argues that the introduction of data warehousing technologies to
enhance the effectiveness and durability in TCM is paramount. To showcase the role of data
warehousing in the improvement of TCM, this paper presents a practical model for data warehousing
with detailed explanation, which is based on the structured electronic records, for TCM clinical
researches and medical knowledge discovery.
Keywords
TCM, Traditional Chinese Medicine, Data Warehouse
1 Introduction
With the on-going changes in the living environment of humans, the increase of physical and mental
disease has undergone great shifts. Diseases such as immune dysfunction, cancer, environmental
pollution disease and other age-related illnesses have increased significantly, and the existing western
chemical treatments are not fully meeting the community’s need. As a result, the treatment has been
changed from simple disease management to a comprehensive treatment paradigm, which includes
prevention, health care, medical treatment and rehabilitation (Chou 2003). Traditional Chinese
medicine (TCM) is an ancient system of health care from China. It is a unique system to diagnose and
cure illnesses and it was developed more than 2000 years ago. It includes herbal and nutritional
therapy, restorative physical exercises, meditation, acupuncture and remedial massage. TCM takes a
complete approach to understanding normal functions and disease processes, focusing on the
prevention of illness as much as it does on the treatment (MedcineNet.Com 2015). As a result of its
incredible success rate, TCM has gained respect around the world. According to China Daily (2015),
the World Federation of Chinese Medicine Societies (WFCMS) has established an official relationship
with the World Health Organisation (WHO), providing technical support to WHO and cooperating
with other non-governmental organisations to promote TCM around the world.
As reported by Helmut Kaiser Consultancy (2015), there are more than 3,000 enterprises currently
engaging in the manufacturing and processing of TCM. It was reported that TCM had a financial
value of AUD $36.8 billion in 2010, and it will continue to rise to AUD $96.2 billion by 2025. With a
global market for TCM, it is no surprise that many countries and multinational companies are keen to
invest in its research and development. In 2014, the Australian government signed a memorandum of
understanding (MOU) with the Chinese government to boost Australia’s position in this global TCM
Australasian Conference on Information Systems
Lam, Sahama, Gajanayake 2015, Adelaide
Constructing TCM DW Application
market. The partnership between the Beijing University of Chinese Medicine and the University of Western Sydney will develop a research platform and clinical service at the National Institute of Complementary Medicine (NICM). The focus of this research will be the quality, safety and effectiveness of Chinese medicine. Its aim will be to provide a world-class facility of integrated clinical services, education and research facilitates that will serve the Australian people and help to promote Chinese medicine to the world (Australian Trade Commission 2014). While TCM development is growing exponentially, large amounts of information are being simultaneously published in the Internet. This includes ancient literatures and clinical researches data, and Internet users can obtain these TCM materials easily by performing searches in engines such as Google, Yahoo or Bing®. According to SEOMoz (2015), these web search engines use their own algorithms to evaluate the query and return the results to users, and the results can be ranked and sorted by: • Keywords and the relevant degree • Quality and timeliness of web content • URL and title of website • Popularity of website However, Wikipedia (2015) states that most of the web searc
This content is AI-processed based on ArXiv data.