Literature DB >> 24930176

Evaluation of a configural vital signs display for intensive care unit nurses.

Frank A Drews, Alexa Doig.   

Abstract

OBJECTIVE: The objective was to evaluate a configural vital signs (CVS) display designed to support rapid detection and identification of physiological deterioration by graphically presenting patient vital signs data.
BACKGROUND: Current display technology in the intensive care unit (ICU) is not optimized for fast recognition and identification of physiological changes in patients. To support nurses more effectively, graphical or configural vital signs displays need to be developed and evaluated.
METHOD: A CVS display was developed based on findings from studies of the cognitive work of ICU nurses during patient monitoring. A total of 42 ICU nurses interpreted data presented either in a traditional, numerical format (n = 21) or on the CVS display (n = 21). Response time and accuracy in clinical data interpretation (i.e., identification of patient status) were assessed across four scenarios.
RESULTS: Data interpretation speed and accuracy improved significantly in the CVS display condition; for example, in one scenario nurses required only half of the time for data interpretation and showed up to 1.9 times higher accuracy in identifying the patient state compared to the numerical display condition.
CONCLUSION: Providing patient information in a configural display with readily visible trends and data variability can improve the speed and accuracy of data interpretation by ICU nurses. APPLICATION: Although many studies, including this one, support the use of configural displays, the vast majority of ICU monitoring displays still present clinical data in numerical format. The introduction of configural displays in clinical monitoring has potential to improve patient safety.

Entities:  

Mesh:

Year:  2014        PMID: 24930176     DOI: 10.1177/0018720813499367

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  8 in total

1.  Patient information organization in the intensive care setting: expert knowledge elicitation with card sorting methods.

Authors:  Thomas Reese; Noa Segall; Paige Nesbitt; Guilherme Del Fiol; Rosalie Waller; Brekk C Macpherson; Joseph E Tonna; Melanie C Wright
Journal:  J Am Med Inform Assoc       Date:  2018-08-01       Impact factor: 4.497

2.  "Usability of data integration and visualization software for multidisciplinary pediatric intensive care: a human factors approach to assessing technology".

Authors:  Ying Ling Lin; Anne-Marie Guerguerian; Jessica Tomasi; Peter Laussen; Patricia Trbovich
Journal:  BMC Med Inform Decis Mak       Date:  2017-08-14       Impact factor: 2.796

Review 3.  Novel Interface Designs for Patient Monitoring Applications in Critical Care Medicine: Human Factors Review.

Authors:  Evismar Andrade; Leo Quinlan; Richard Harte; Dara Byrne; Enda Fallon; Martina Kelly; Siobhan Casey; Frank Kirrane; Paul O'Connor; Denis O'Hora; Michael Scully; John Laffey; Patrick Pladys; Alain Beuchée; Gearóid ÓLaighin
Journal:  JMIR Hum Factors       Date:  2020-07-03

4.  Critical care information display approaches and design frameworks: A systematic review and meta-analysis.

Authors:  Melanie C Wright; Damian Borbolla; Rosalie G Waller; Guilherme Del Fiol; Thomas Reese; Paige Nesbitt; Noa Segall
Journal:  J Biomed Inform X       Date:  2019-06-22

5.  Avatar-Based Patient Monitoring With Peripheral Vision: A Multicenter Comparative Eye-Tracking Study.

Authors:  Juliane Pfarr; David W Tscholl; Michael T Ganter; Donat R Spahn; Christoph B Noethiger
Journal:  J Med Internet Res       Date:  2019-07-17       Impact factor: 5.428

6.  Association of Data Integration Technologies With Intensive Care Clinician Performance: A Systematic Review and Meta-analysis.

Authors:  Ying Ling Lin; Patricia Trbovich; Lauren Kolodzey; Cheri Nickel; Anne-Marie Guerguerian
Journal:  JAMA Netw Open       Date:  2019-05-03

7.  Informative graphing of continuous safety variables relative to normal reference limits.

Authors:  Christopher D Breder
Journal:  BMC Med Res Methodol       Date:  2018-05-16       Impact factor: 4.615

Review 8.  Situation Awareness-Oriented Patient Monitoring with Visual Patient Technology: A Qualitative Review of the Primary Research.

Authors:  David Werner Tscholl; Julian Rössler; Sadiq Said; Alexander Kaserer; Donat Rudolf Spahn; Christoph Beat Nöthiger
Journal:  Sensors (Basel)       Date:  2020-04-09       Impact factor: 3.576

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.