Deep Learning Based Early Warning Score in Rapid Response Team Activation

Seoul National University

Status: Unknown

Conditions: Hospital Rapid Response Team; Hospital Medical Emergency Team

Treatments: Diagnostic Test: Deep Learning Based Early Warning Score (DEWS)

Study type: Observational

Funder types: Other

Identifiers

NCT04951973

DEWS_2021

Details and patient eligibility

About

The objective of this study is to evaluate the safety and clinical usefulness of the Deep learning based Early Warning Score (DEWS).

Full description

SPTTS is the representative trigger tracking system. In addition to the conventional SPTTS, DEWS will be calculated at each time point by the previously developed algorithm. SPTTS and DEWS will be shown simulataneously on the screening board. The rapid response team performs the rescue activity as before, using both SPTTS and DEWS simultaneously.

The alarm threshold setting of DEWS will be changed to 70 points, 75 points, and 80 points every month.

The primary and secondary outcomes will be evaluated to compare SPTTS and DEWS (based on each threshold).

Enrollment: 50,000 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients admitted to general ward and monitored by in-hospital rapid response system

Exclusion criteria

• patients admitted to pediatric ward
• patients in emergency room, intensive care unit, and operating room