Features of electronic Early Warning systems which impact clinical decision-making

Atieh Zarabzadeh, Mervyn O’Connell, John O’Donoghue, Tom O’Kane, Simon Woodworth, Joe Gallagher, Siobhan O'Connor, Frederic Adam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Paper-based Modified Early Warning Scorecards (MEWS) have been developed to help nursing staff detect hospital in-patient deterioration at an early stage. MEWS is based on patient vital signs where these values are transformed into a MEWS score. An electronic Modified Early Warning Scorecard (eMEWS) prototype has been designed and developed to fulfill the role of a computerized Clinical Decision Support System (CDSS) and to assist healthcare professionals in their decision making activities. A review of the existing electronic Early Warning Scorecards (eEWS) revealed they lack certain features that assist in capturing a holistic view of the patient health status for example color codes and vital sign trends. The proposed eMEWS prototype employs these features with the aim of assisting healthcare professionals to obtain a clear understanding of the patient status. A survey was conducted to evaluate the impact of paper-based MEWS and
eMEWS as part of the decision making process. The advantages and disadvantages of eMEWS over the paper-based MEWS are presented.
Original languageEnglish
Title of host publication25th IEEE International Symposium on Computer-Based Medical Systems (CBMS)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Publication statusPublished - 22 Jun 2012

Keywords

  • eHealth
  • digital health
  • clinical decision making

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