Improving the Patient Discharge Planning Process through Knowledge Management by Using the Internet of Things

• 作者: Alan Eardley Caroline Chibelushi Nitya Ahilandam Kamalanathan Tim Collins
• 来源期刊: 物联网(英文)
• 学科: 医学
• 关键词: National Health Service (NHS) Knowledge Management (KM) DISCHARGE Planning (DP) Internet of THINGS (IoT) Machine2Machine (M2M)
• 年，卷（期）: 2013,（2）
• 页码范围: 16-26
• 页数: 11页
• 分类号: R73

摘要

The UK National Health Service (NHS) is faced with problems of managing patient discharge and preventing the problems that result from it such as frequent readmissions, delayed discharge, long waiting lists, bed blocking and other such consequences. The problem is exacerbated by the growth in size, complexity and the number of chronic diseases in the NHS. In addition, there is an increase in demand for high quality care, processes and planning. Effective Discharge Planning (DP) requires practitioners to have appropriate, patient personalised and updated knowledge in order to be able to make informed and holistic decisions about a patients’ discharge. This paper examines the role of Knowledge Management (KM) in both sharing knowledge and using tacit knowledge to create appropriate patient discharge pathways. The paper details the factors resulting in inadequate DP, and demonstrates the use of Internet of Things (IoT) and Machine2Machine (M2M) as candidate technologies and possible solutions which can help reduce the problem. The use of devices that a patient can take home and devices which are perused in the hospital generate information, which can serve useful when presented to the right person at the right time, thus harvesting knowledge. The knowledge when fed back can support practitioners in making holistic decisions with regards to a patients’ discharge.