Development of an Automatically Generated and Wearable-based Early Warning System

University Hospital Basel

Status: Completed

Conditions: Deterioration of Patient's State of Health

Treatments: Other: data collection

Study type: Observational

Funder types: Other

Identifiers

NCT05699967

2022-02093 am22Eckstein5;

Details and patient eligibility

About

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.

Full description

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.

Enrollment: 210 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Planned hospital stay > 24 hours
• Written informed consent as documented by signature from the participant

Exclusion criteria

• Unable or not willing to sign informed consent
• Wearable cannot be worn due to comprehensible reasons (allergic reactions, wounds, amputations, excessive hairiness, edema, venous access, other)
• Significant mental or cognitive impairment