Literature DB >> 16806641

Calculating early warning scores--a classroom comparison of pen and paper and hand-held computer methods.

David R Prytherch1, Gary B Smith, Paul Schmidt, Peter I Featherstone, Kate Stewart, Debbie Knight, Bernie Higgins.   

Abstract

To assist in the early detection of critical illness, many hospitals now use a "track and trigger" system that allocates points to routine vital signs measurements on the basis of their derangement from an arbitrarily agreed "normal" range. These points are summed to provide an early warning score (EWS). Little is known about the accuracy with which EWS are calculated and charted. We compared the speed and accuracy of charting the weighted value attributed to each vital sign, and of calculating the EWS, using the traditional pen and paper method with that using a specially programmed, personal digital assistant (VitalPAC). Incorrect entries or omissions occurred in 24 (29%) of 84 EWS computed using pen/paper compared to 8 (10%) computed using the VitalPAC method. Fewer incorrect clinical actions were indicated using EWS derived via the VitalPAC method (4/84, 5%) than from those calculated using pen/paper (12/84, 14%). The mean time (+/-S.D.) taken for participants to calculate and chart a set of weighted values and EWS using the pen/paper method was 67.6+/-35.3 s (n=84). The corresponding time taken to enter a set of physiological data using the VitalPAC was 43.0+/-23.5 s (n=84). By comparison with the conventional pen/paper method, the use of VitalPAC was on average 1.6-times faster. The use of a device such as VitalPAC offers significant advantages both in speed and accuracy of recording of EWS.

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Year:  2006        PMID: 16806641     DOI: 10.1016/j.resuscitation.2005.12.002

Source DB:  PubMed          Journal:  Resuscitation        ISSN: 0300-9572            Impact factor:   5.262


  29 in total

1.  Computer-aided National Early Warning Score to predict the risk of sepsis following emergency medical admission to hospital: a model development and external validation study.

Authors:  Muhammad Faisal; Donald Richardson; Andrew J Scally; Robin Howes; Kevin Beatson; Kevin Speed; Mohammed A Mohammed
Journal:  CMAJ       Date:  2019-04-08       Impact factor: 8.262

2.  The National Early Warning Score and its subcomponents recorded within ±24 h of emergency medical admission are poor predictors of hospital-acquired acute kidney injury.

Authors:  Muhammad Faisal; Andy Scally; Musab Ahmed Elgaali; Donald Richardson; Kevin Beatson; Mohammed A Mohammed
Journal:  Clin Med (Lond)       Date:  2018-02       Impact factor: 2.659

3.  In-hospital cardiac arrest and preceding National Early Warning Score (NEWS): A retrospective case-control study.

Authors:  Martin Spångfors; Mats Molt; Karin Samuelson
Journal:  Clin Med (Lond)       Date:  2020-01       Impact factor: 2.659

4.  Development of an electronic daily uterine fibroid symptom diary.

Authors:  Linda S Deal; Valerie S L Williams; Sheri E Fehnel
Journal:  Patient       Date:  2011       Impact factor: 3.883

5.  Quick Sepsis-related Organ Failure Assessment, Systemic Inflammatory Response Syndrome, and Early Warning Scores for Detecting Clinical Deterioration in Infected Patients outside the Intensive Care Unit.

Authors:  Matthew M Churpek; Ashley Snyder; Xuan Han; Sarah Sokol; Natasha Pettit; Michael D Howell; Dana P Edelson
Journal:  Am J Respir Crit Care Med       Date:  2017-04-01       Impact factor: 21.405

6.  The value of vital sign trends for detecting clinical deterioration on the wards.

Authors:  Matthew M Churpek; Richa Adhikari; Dana P Edelson
Journal:  Resuscitation       Date:  2016-02-16       Impact factor: 5.262

Review 7.  Risk stratification of hospitalized patients on the wards.

Authors:  Matthew M Churpek; Trevor C Yuen; Dana P Edelson
Journal:  Chest       Date:  2013-06       Impact factor: 9.410

8.  Using electronic health record data to develop and validate a prediction model for adverse outcomes in the wards*.

Authors:  Matthew M Churpek; Trevor C Yuen; Seo Young Park; Robert Gibbons; Dana P Edelson
Journal:  Crit Care Med       Date:  2014-04       Impact factor: 7.598

9.  A ward-based time study of paper and electronic documentation for recording vital sign observations.

Authors:  David Wong; Timothy Bonnici; Julia Knight; Stephen Gerry; James Turton; Peter Watkinson
Journal:  J Am Med Inform Assoc       Date:  2017-07-01       Impact factor: 4.497

Review 10.  The effectiveness of mobile-health technologies to improve health care service delivery processes: a systematic review and meta-analysis.

Authors:  Caroline Free; Gemma Phillips; Louise Watson; Leandro Galli; Lambert Felix; Phil Edwards; Vikram Patel; Andy Haines
Journal:  PLoS Med       Date:  2013-01-15       Impact factor: 11.069

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