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

Nitya Ahilandam Kamalanathan, Alan Eardley, Caroline Chibelushi, Tim Collins

Faculty of Computing Engineering and Sciences, Staffordshire University, Stafford, UK.

DOI: 10.4236/ait.2013.32A003                

Abstract

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.

Keywords

National Health Service (NHS); Knowledge Management (KM); Discharge Planning (DP); Internet of Things (IoT); Machine2Machine (M2M)

Conflicts of Interest

The authors declare no conflicts of interest.

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