Self-adaptative Early Warning Scoring System
for Smart Hospital
Imen Ben Ida
1(&) , Moez Balti
1,2 , Sondès Chabaane
3 ,
and Abderrazak Jemai
1,4
1 Electronic Systems and Communications Networks Laboratory (SERCOM),
Polytechnic School of Tunisia, Carthage University, Tunis, Tunisia
Imen.benida@gmail.com
2 IsetCom, Carthage University, Tunis, Tunisia
3 CNRS UMR 8201 - LAMIH - Laboratory of Automatic Mechanics
and Industrial and Human Informatics, Hauts-de-France Polytechnic University,
59313 Valenciennes, France
4 INSAT, Carthage University, Tunis, Tunisia
Abstract. With the advent of the Internet of Things (IoT), various interconnected objects can be used to improve the collection and the process of vital
signs with partially or fully automatized methods in smart hospital environment.
The vital signs data are used to evaluate patient health status using heuristic
approaches, such as the early warning scoring (EWS) approach. Several
applications have been proposed based on the early warning scores approach to
improve the recognition of patients at risk of deterioration. However, there is a
lack of efficient tools that enable a personalized monitoring depending on the
patient situations. This paper explores the publish-subscribe pattern to provide a
self-adaptative early warning score system in smart hospital context. We propose an adaptative configuration of the vital sings monitoring process depending
on the patient health status variation and the medical staff decisions.
Keywords: Computing for healthcare Á Early warning scoring system Á Internet
of Things Á Smart hospital
1 Introduction
The smart hospital (SH) is adding the intelligence to traditional hospital system to
improve the quality of healthcare services. It is based on the effective use of technology
and it covers all the resources and the locations with the patient information. A principal functionality in a smart hospital is the automated and continuous control of the
patients during the hospitalization by measuring their vital signs. These observations
are important for preventing health deterioration, reducing costs and hospitalization
time, and potentially minimizing morbidity and mortality [1]. Several medical
approaches are used to evaluate the collected vital sings data. A prevalent example is
the Early warning scoring (EWS) approach which has been in use for several years as a
tool to predict the risk level of patients [2]. It was proposed for the first time as a paperbased method that need periodical checkups to assign a score based on patient’s vital
© The Author(s) 2020
M. Jmaiel et al. (Eds.): ICOST 2020, LNCS 12157, pp. 16–27, 2020.
https://doi.org/10.1007/978-3-030-51517-1_2
for Smart Hospital
Imen Ben Ida
1(&) , Moez Balti
1,2 , Sondès Chabaane
3 ,
and Abderrazak Jemai
1,4
1 Electronic Systems and Communications Networks Laboratory (SERCOM),
Polytechnic School of Tunisia, Carthage University, Tunis, Tunisia
Imen.benida@gmail.com
2 IsetCom, Carthage University, Tunis, Tunisia
3 CNRS UMR 8201 - LAMIH - Laboratory of Automatic Mechanics
and Industrial and Human Informatics, Hauts-de-France Polytechnic University,
59313 Valenciennes, France
4 INSAT, Carthage University, Tunis, Tunisia
Abstract. With the advent of the Internet of Things (IoT), various interconnected objects can be used to improve the collection and the process of vital
signs with partially or fully automatized methods in smart hospital environment.
The vital signs data are used to evaluate patient health status using heuristic
approaches, such as the early warning scoring (EWS) approach. Several
applications have been proposed based on the early warning scores approach to
improve the recognition of patients at risk of deterioration. However, there is a
lack of efficient tools that enable a personalized monitoring depending on the
patient situations. This paper explores the publish-subscribe pattern to provide a
self-adaptative early warning score system in smart hospital context. We propose an adaptative configuration of the vital sings monitoring process depending
on the patient health status variation and the medical staff decisions.
Keywords: Computing for healthcare Á Early warning scoring system Á Internet
of Things Á Smart hospital
1 Introduction
The smart hospital (SH) is adding the intelligence to traditional hospital system to
improve the quality of healthcare services. It is based on the effective use of technology
and it covers all the resources and the locations with the patient information. A principal functionality in a smart hospital is the automated and continuous control of the
patients during the hospitalization by measuring their vital signs. These observations
are important for preventing health deterioration, reducing costs and hospitalization
time, and potentially minimizing morbidity and mortality [1]. Several medical
approaches are used to evaluate the collected vital sings data. A prevalent example is
the Early warning scoring (EWS) approach which has been in use for several years as a
tool to predict the risk level of patients [2]. It was proposed for the first time as a paperbased method that need periodical checkups to assign a score based on patient’s vital
© The Author(s) 2020
M. Jmaiel et al. (Eds.): ICOST 2020, LNCS 12157, pp. 16–27, 2020.
https://doi.org/10.1007/978-3-030-51517-1_2