The aim of this project is to create an automated EWS and analyze whether the use of wearable devices is suitable for vital sign measurements in a hospital by using the recording of vital parameters taken by nurses via the Clinical Information System (HIS) combining them with vital sign measurements coming from wearable devices.
Acute deteriorations of patients are often preceded by changes in their vital signs and can thus lead to adverse events in hospital wards. Some of these events may be preventable if the deterioration is detected in time and appropriate measures are taken. Early Warning Scores (EWS) have been developed to systematically assess the vital signs of all patients. There are different versions of EWS but all of the systems have the same purpose: they are intended to timely identify the risk of patients deteriorating by monitoring the health status of patients during their hospital stay on the basis of routinely measured vital signs by ward staff. The EWS is an aggregated scoring system, the higher the score, the higher the risk of a deterioration. EWS have limitations as classical EWS are userdependent systems prone to incomplete recordings, calculation errors in the EWS and nonadherence to referral protocols. The aim of this project is to create an automated EWS and analyze whether the use of wearable devices is suitable for vital sign measurements in a hospital by using the recording of vital parameters taken by nurses via the Clinical Information System (HIS) combining them with vital sign measurements coming from wearable devices. The National Early Warning Score 2 (NEWS2), which was developed to standardize the approach to detection of clinical deterioration, shall be used. The NEWS2 is a predictive scoring system that uses 6 physiological parameters: heart rate (HR), respiratory rate (RR), oxygen saturation levels (SpO2) including supplemental oxygen, systolic blood pressure, temperature and level of consciousness. A score of 0, 1, 2 or 3 is allocated to each parameter. A higher score means the parameter is further from the normal range. The NEWS2 is then constituted by combining the individual scores of every parameter to an aggregated score, the NEWS2 Score. Mobile sensors (wearables) are able to monitor some of the components of the EWS and their use has the potential to provide timely information on the patient's health status thanks to continuous automated data collection, especially with regard to vital signs like the respiratory rate. This study is to make a first step towards the development of an application which automatically generates the National Early Warning Score 2 (NEWS2) using the recordings of vital parameters via wearables and combining them with data documented in the Clinical Information System and to evaluate the feasibility of this application in terms of accuracy of the calculated scores.
Study Type
OBSERVATIONAL
Enrollment
210
Participants wear a wristband with a Photoplethysmography (PPG), heart rate and respiratory rate sensor continuously for 3 days. Once gateway and device are linked, all data will be transmitted continuously via Bluetooth to an in-house database. The Device Hub allows to control data availability and signal quality of the wearables, but no scores will be calculated and visualized. The data obtained for calculating the NEWS2 is solely observational and for the study staff. It has no clinical consequence on the treatment of the patient. It is analyzed whether the score with values form the wearables and Electronic Health Record (EHR) corresponds to the conventionally calculated NEWS2 score with values coming only from the EHR.
University Hospital Basel, Division of Internal Medicine
Basel, Switzerland
Number of correctly automatically calculated scores
Comparing the NEWS2 calculated with values from the EHR and the automatically calculated NEWS2 with values from the EHR and wearable devices: The number of correctly automatically calculated scores will be assessed.
Time frame: one time assessment at Day 1
Compliance of the study subjects concerning the wearable device
Compliance of the study subjects evaluated by the time the wearable was effectively worn by the patient divided by the time the wearable was supposed to be worn by the participant
Time frame: one time assessment at Day 1
Patient acceptance of the approach
Participants' feedback about the approach collected by a semi structured interview
Time frame: one time assessment at Day 1
Number of incomplete datasets
Number of incomplete datasets for analysis of the technical feasibility and practical usability
Time frame: one time assessment at Day 1
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