DOI: 10.5061/dryad.000mn47
title: Data from: Implementation of an automated early warning scoring system in a surgical ward: practical use and effects on patient outcomes

description: Introduction: Early warning scores (EWS) are being increasingly embedded
 in hospitals over the world due to their promise to reduce adverse events
 and improve the outcomes of clinical patients. The aim of this study was
 to evaluate the clinical use of an automated modified EWS (MEWS) for
 patients after surgery. Methods: This study conducted retrospective
 before-and-after comparative analysis of non-automated and automated MEWS
 for patients admitted to the surgical high-dependency unit in a tertiary
 hospital. Operational outcomes included number of recorded assessments of
 the individual MEWS elements, number of complete MEWS assessments, as well
 as adherence rate to related protocols. Clinical outcomes included
 hospital length of stay, in-hospital and 28-day mortality, and ICU
 readmission rate. Results: Recordings in the electronic medical record
 from the control period contained 7929 assessments of MEWS elements and
 were performed in 320 patients. Recordings from the intervention period
 contained 8781 assessments of MEWS elements in 273 patients, of which 3418
 were performed with the automated EWS system. During the control period,
 199 (2.5%) complete MEWS were recorded versus 3991 (45.5%) during
 intervention period. With the automated MEWS systems, the percentage of
 missing assessments and the time until the next assessment for patients
 with a MEWS of ≥2 decreased significantly. The protocol adherence improved
 from 1.1% during the control period to 25.4% when the automated MEWS
 system was involved. There were no significant differences in clinical
 outcomes. Conclusion: Implementation of an automated EWS system on a
 surgical high dependency unit improves the number of complete MEWS
 assessments, registered vital signs, and adherence to the EWS hospital
 protocol. However, this positive effect did not translate into a
 significant decrease in mortality, hospital length of stay, or ICU
 readmissions. Future research and development on automated EWS systems
 should focus on data management and technology interoperability.
description: Clinical
 outcomesThis data file describes
 the clinical data of both control and intervention group. The last columns
 describe the number and percentage of corresponding measurements in both
 the data retrieved from the automated EWS system, as well as from the
 electronic patient records (EMR). This was only applicable for cases in
 the intervention period since both methods (automated EWS system and EMR)
 were used.Automated_EWS_implementation_Mestrom_Bie_Clinical outcomes.xlsxMeasurements_control_periodThis dataset contains every measurement of vital sign(s) recorded in the electronic medical record during the control period.Automated_EWS_implementation_Mestrom_Bie_Measurements_control_period.xlsxMeasurements_intervention_period_EMRThis dataset contains every measurement of vital sign(s) recorded in the electronic medical record during the intervention period.Automated_EWS_implementation_Mestrom_Bie_Measurements_intervention_period_EMR.xlsxMeasurements_intervention_period_EWS_systemThis dataset contains every measurement of vital sign(s) recorded in automated EWS system during the intervention period.Automated_EWS_implementation_Mestrom_Bie_Measurements_intervention_period_EWS_system.xlsx