An IoMT-based geriatric care management system for achieving smart health in nursing homes
| DOI | https://doi.org/10.1108/IMDS-01-2019-0024 |
| Pages | 1819-1840 |
| Date | 09 September 2019 |
| Published date | 09 September 2019 |
| Author | Valerie Tang,K.L. Choy,G.T.S. Ho,H.Y. Lam,Y.P. Tsang |
| Subject Matter | Information & knowledge management |
An IoMT-based geriatric care
management system for achieving
smart health in nursing homes
Valerie Tang and K.L. Choy
Department of Industrial and Systems Engineering,
Hong Kong Polytechnic University, Kowloon, Hong Kong
G.T.S. Ho and H.Y. Lam
Department of Supply Chain and Information Management,
The Hang Seng University of Hong Kong, Shatin, Hong Kong, and
Y.P. Tsang
Department of Industrial and Systems Engineering,
Hong Kong Polytechnic University, Kowloon, Hong Kong
Abstract
Purpose –The purpose of this paper is to develop an Internet of medical things (IoMT)-based geriatric care
management system (I-GCMS), integrating IoMT and case-based reasoning (CBR) in order to deal with the
global concerns of the increasing demand for elderly care service in nursing homes.
Design/methodology/approach –The I-GCMS is developed under the IoMT environment to collect real-
time biometric data for total health monitoring. When the health of an elderly deteriorates, the CBR is used to
revise and generate the customized care plan, and hence support and improve the geriatric care management
(GCM) service in nursing homes.
Findings –A case study is conducted in a nursing home in Taiwan to evaluate the performance of the
I-GCMS. Under the IoMT environment, the time saving in executing total health monitoring helps improve the
daily operation effectiveness and efficiency. In addition, the proposed system helps leverage a proactive
approach in modifying the content of a care plan in response to the change of health status of elderly.
Originality/value –Considering the needs for demanding and accurate healthcare services, this is the first
time that IoMT and CBR technologies have been integrated in the field of GCM. This paper illustrates how to
seamlessly connect various sensors to capture real-time biometric data to the I-GCMS platform for
responsively supporting decision making in the care plan modification processes. With the aid of I-GCMS, the
efficiency in executing the daily routine processes and the quality of healthcare services can be improved.
Keywords Nursing home, Case-based reasoning, Geriatric care management, Internet of medical things
Paper type Research paper
1. Introduction
Facing the unavoidable phenomenon of the aging population, the need for long-term care
(LTC) has been emphasized for serving the elderly with chronic diseases or disabilities who
have the difficulties in their daily life so as to relieve the pressure faced by hospitals (He and
Chou, 2017; Beard and Bloom, 2015). In order to deliver quality, affordable and accessible
healthcare services to the elderly, a long-term care project (LTCP) was launched in 2007 by
the TaiwanGovernment with the aim of establishing a comprehensive care plan in the
community through the adoption of smart health in the area of geriatric care management
(GCM) (Ministry of Health and Welfare, 2016). This concept of LTCP is widely followed in
other countries such as China and the USA for developing a complete chain of healthcare
services, from preventative care to community-based healthcare support and finally to
hospice care (Feng et al., 2012). As important LTC providers, nursing homes play an Industrial Management & Data
Systems
Vol. 119 No. 8, 2019
pp. 1819-1840
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-01-2019-0024
Received 15 January 2019
Revised 11 July 2019
Accepted 30 July 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
The authors would like to thank the Research Office of the Hong Kong Polytechnic University and the
Comfort Nursing Home for supporting the project (Project Code: RU8J).
1819
IoMT-based
geriatric care
management
system
important role in providing GCM, which refers to a series of steps of assessing, planning,
coordinating, monitoring and providing the healthcare services for the elderly (Wideman,
2012). It not only provides basic healthcare services such as nursing care, personal care and
residential care for fulfilling the needs of the elderly, but also emphasizes on how to
maintain and promote quality of life (Zimmerman et al., 2014).
Currently, three problems are identified in the current GCM workflow, as shown in
Figure 1, which are collection of biometric data separately and repetitively, no data linkage
between health monitoring and the care plan modification processes and, long timeframe for
the complex evaluation in care planmodification. At the time of admission, a customizedcare
plan with thegoals of meeting the needs of an elderly, is formulatedthrough a comprehensive
review on the information related to historical health records of an individual and science of
care. During the time in nursing homes, the health of the elderly inevitably deteriorates, and
thus the monitoring of their health status is important during their stay in nursing homes.
Caregivers are required to check and record the biometricdata, such as vital signs including
heart rate (HR), body temperature (BT) and breathing rate, on manual paper-based daily
worksheets several times per day. Such biometric data are then stored separately for
recording and reference only. Once the regularreview of care plan is executed, such data will
be extracted and integrated from the separate database to analyze the health status of the
elderly for meeting their changing needs. Without a systematic approach in GCM, relevant
data cannot be instantly captured, integrated and managed formonitoring and analysis. As a
result, caregiversmay overlook any abnormalities appearingof the biometric data resultingin
a delay in providing instant treatment in emergency cases. Health deterioration may occur
and even cause harmful effect to the elderly. In addition, since any care plan modification
requires the deep expert knowledge, the current practice needs a long timeframe to complete
the review of the care plan and to make appropriate amendments.
Although Wong et al. (2017) has introduced the adoption of healthcare sensors for
collecting the real-time data, the infrastructure of IoMT, including how healthcare sensors
are connected for collecting the desirable data, how the health data processes and transfers
from sensors to cloud and how the data can be visualized by the users for providing the
personalized-based services, is neglected. In addition, it is found that most research related
to healthcare focused on the area of disease diagnosis, disease prevention and drug reaction
detection, attention rarely is paid to the field of GCM in nursing homes, as well as the
decision support system for analyzing the relevant data and facilitating care plan
formulation. Therefore, in order to fill this research gap, an internet of medical things
(IoMT)-based geriatric care management system (I-GCMS) is proposed in this paper. The
system integrates IoMT and case-based reasoning (CBR) to monitor the real-time biometric
data of the elderly and, support decision making for caregivers in care plan modification.
The data, including barometric data and operation data taken in nursing homes, can be
Biometric data capturing
• Body temperature
• Blood pressure
• Heart rate
• Blood glucose
.
.
.
Health monitoring and recording
Paper-based
daily worksheet
(Manual record) Database for storing
the biometric data
Manual data input Care plan modification
Manual
evaluation
process
• Historical records
• Past care records
• Available healthcare resources
- Staffing - Diet
- Equipment
• General service
Problem 1: collection of biometric
data separately and repetitively
Problem 2: no data linkage
between these two processes
Problem 3: long time frame for
complex evaluation processes
Lacking of systematic approach
- to smooth the operation in implementing
the daily routine process and alert the
abnormalities occurred
- to analyze the collected biometric data for
care plan modification
- to support the decision making in
the care plan modification
processes
Figure 1.
Existing problems in
the geriatric care
management (GCM)
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IMDS
119,8
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