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.
RCT Entities:
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.
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
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
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
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
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