signs (i.e., heart rate, respiration rate, body temperature, blood pressure). The score of
each medical sign depends on the non-respect of a predefined normal interval. The
summation of all scores reflects the global patients risk level [2].
By exploring the Internet of Things technologies, the vital signs control solutions
are automated based on various medical devices and sensors. Smart medical devices
constitute the core part of the smart hospital environment. Their main purpose is to
gather vital signs data or other patient physiological conditions. These automated
systems reduce the errors of the manual Early Warning Score systems [3] and facilitate
the nurses’ functions such as constantly gathering and storing the vital signs records.
The emergence of the Internet of Things, the electronic records and the computerized transaction systems have improved the efficiency and effectiveness of EWS
systems.
In spite of such advantages using IoT, there are currently two important challenges
of early warning scores systems and they need to be considered. The first issue is how
to ensure a personalized monitoring of patients’ vital signs depending on their situations and the medical experts’ requirements especially in case of controlling an
important number of patients.
The second issue is the need of timely response of medical staff in case of problem
detection.
Our work is motivated by the challenges described above and its main objective is a
self-adaptative Early Warning Scoring system that supports the change of the patient
control frequency depending on his situation.
This paper is organized as follows: In Sect. 2 we describe the vital signs evaluation
with the early warning score systems and we present some related works. Our proposed
solution is detailed in Sect. 3. The Implementation and the evaluation are presented and
discussed in Sect. 4. The Sect. 5 presents the concluding remarks and future work.
2 Background and Related Works
Early warning systems, also known as ‘track-and-trigger’ (T&T) systems, consist of
evaluating vital sings using scores to recognize patients at risk of deterioration. Since
85% of severe adverse events (SAE) are preceded by abnormal vital signs, the vital
signs monitoring based on EWS approach have evolved as a means of alerting health
professionals to patient clinical decline [4].
In smart hospitals, particularly in intensive care units, the Early Warning Score
(EWS) is a prevalent tool, by which patient’s vital signs are periodically recorded and
the emergency level is interpreted [3]. To this end, a score (0 for a perfect condition and
3 for the worst condition) is allocated to each vital sign according to its value and the
predefined limits. The summation of the obtained scores indicates the degree of health
deterioration of the patient (the higher the EWS, the worse the patient’s health
condition).
Self-adaptative Early Warning Scoring System for Smart Hospital
17
each medical sign depends on the non-respect of a predefined normal interval. The
summation of all scores reflects the global patients risk level [2].
By exploring the Internet of Things technologies, the vital signs control solutions
are automated based on various medical devices and sensors. Smart medical devices
constitute the core part of the smart hospital environment. Their main purpose is to
gather vital signs data or other patient physiological conditions. These automated
systems reduce the errors of the manual Early Warning Score systems [3] and facilitate
the nurses’ functions such as constantly gathering and storing the vital signs records.
The emergence of the Internet of Things, the electronic records and the computerized transaction systems have improved the efficiency and effectiveness of EWS
systems.
In spite of such advantages using IoT, there are currently two important challenges
of early warning scores systems and they need to be considered. The first issue is how
to ensure a personalized monitoring of patients’ vital signs depending on their situations and the medical experts’ requirements especially in case of controlling an
important number of patients.
The second issue is the need of timely response of medical staff in case of problem
detection.
Our work is motivated by the challenges described above and its main objective is a
self-adaptative Early Warning Scoring system that supports the change of the patient
control frequency depending on his situation.
This paper is organized as follows: In Sect. 2 we describe the vital signs evaluation
with the early warning score systems and we present some related works. Our proposed
solution is detailed in Sect. 3. The Implementation and the evaluation are presented and
discussed in Sect. 4. The Sect. 5 presents the concluding remarks and future work.
2 Background and Related Works
Early warning systems, also known as ‘track-and-trigger’ (T&T) systems, consist of
evaluating vital sings using scores to recognize patients at risk of deterioration. Since
85% of severe adverse events (SAE) are preceded by abnormal vital signs, the vital
signs monitoring based on EWS approach have evolved as a means of alerting health
professionals to patient clinical decline [4].
In smart hospitals, particularly in intensive care units, the Early Warning Score
(EWS) is a prevalent tool, by which patient’s vital signs are periodically recorded and
the emergency level is interpreted [3]. To this end, a score (0 for a perfect condition and
3 for the worst condition) is allocated to each vital sign according to its value and the
predefined limits. The summation of the obtained scores indicates the degree of health
deterioration of the patient (the higher the EWS, the worse the patient’s health
condition).
Self-adaptative Early Warning Scoring System for Smart Hospital
17