TITLE:
Improving the Patient Discharge Planning Process through Knowledge Management by Using the Internet of Things
AUTHORS:
Nitya Ahilandam Kamalanathan, Alan Eardley, Caroline Chibelushi, Tim Collins
KEYWORDS:
National Health Service (NHS); Knowledge Management (KM); Discharge Planning (DP); Internet of Things (IoT); Machine2Machine (M2M)
JOURNAL NAME:
Advances in Internet of Things,
Vol.3 No.2A,
June
18,
2013
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.