TY - JOUR
T1 - A Novel Continuous Real-Time Vital Signs Viewer for Intensive Care Units
T2 - Design and Evaluation Study
AU - VS viewer study group
AU - Yang, Shiming
AU - Galvagno, Samuel
AU - Badjatia, Neeraj
AU - Stein, Deborah
AU - Teeter, William
AU - Scalea, Thomas
AU - Shackelford, Stacy
AU - Fang, Raymond
AU - Miller, Catriona
AU - Hu, Peter
AU - Mackenzie, Colin
AU - Wade, Sarah
AU - Hartsky, Lauren
AU - Grissom, Thomas
AU - Roux, Napoleon
AU - Floccare, Doug
AU - Engdahl, Ashton
AU - Murray, Scott
AU - Kozar, Rosemary
AU - Murthi, Sarah
AU - Buchanan, Laura
AU - Reynolds, Neal
AU - Parikh, Gunjan
AU - Brenner, Megan
N1 - Publisher Copyright:
© Shiming Yang, Samuel Galvagno, Neeraj Badjatia, Deborah Stein, William Teeter, Thomas Scalea, Stacy Shackelford, Raymond Fang, Catriona Miller, Peter Hu, VS viewer study group. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 05.01.2024. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Human Factors, is properly cited. The complete bibliographic information, a link to the original publication on https://humanfactors.jmir.org, as well as this copyright and license information must be included.
PY - 2024/1
Y1 - 2024/1
N2 - Background: Clinicians working in intensive care units (ICUs) are immersed in a cacophony of alarms and a relentless onslaught of data. Within this frenetic environment, clinicians make high-stakes decisions using many data sources and are often oversaturated with information of varying quality. Traditional bedside monitors only depict static vital signs data, and these data are not easily viewable remotely. Clinicians must rely on separate nursing charts-handwritten or electric-to review physiological patterns, including signs of potential clinical deterioration. An automated physiological data viewer has been developed to provide at-a-glance summaries and to assist with prioritizing care for multiple patients who are critically ill. Objective: This study aims to evaluate a novel vital signs viewer system in a level 1 trauma center by subjectively assessing the viewer's utility in a high-volume ICU setting. Methods: ICU attendings were surveyed during morning rounds. Physicians were asked to conduct rounds normally, using data reported from nurse charts and briefs from fellows to inform their clinical decisions. After the physician finished their assessment and plan for the patient, they were asked to complete a questionnaire. Following completion of the questionnaire, the viewer was presented to ICU physicians on a tablet personal computer that displayed the patient's physiologic data (ie, shock index, blood pressure, heart rate, temperature, respiratory rate, and pulse oximetry), summarized for up to 72 hours. After examining the viewer, ICU physicians completed a postview questionnaire. In both questionnaires, the physicians were asked questions regarding the patient's stability, status, and need for a higher or lower level of care. A hierarchical clustering analysis was used to group participating ICU physicians and assess their general reception of the viewer. Results: A total of 908 anonymous surveys were collected from 28 ICU physicians from February 2015 to June 2017. Regarding physicians' perception of whether the viewer enhanced the ability to assess multiple patients in the ICU, 5% (45/908) strongly agreed, 56.6% (514/908) agreed, 35.3% (321/908) were neutral, 2.9% (26/908) disagreed, and 0.2% (2/908) strongly disagreed. Conclusions: Morning rounds in a trauma center ICU are conducted in a busy environment with many data sources. This study demonstrates that organized physiologic data and visual assessment can improve situation awareness, assist clinicians with recognizing changes in patient status, and prioritize care.
AB - Background: Clinicians working in intensive care units (ICUs) are immersed in a cacophony of alarms and a relentless onslaught of data. Within this frenetic environment, clinicians make high-stakes decisions using many data sources and are often oversaturated with information of varying quality. Traditional bedside monitors only depict static vital signs data, and these data are not easily viewable remotely. Clinicians must rely on separate nursing charts-handwritten or electric-to review physiological patterns, including signs of potential clinical deterioration. An automated physiological data viewer has been developed to provide at-a-glance summaries and to assist with prioritizing care for multiple patients who are critically ill. Objective: This study aims to evaluate a novel vital signs viewer system in a level 1 trauma center by subjectively assessing the viewer's utility in a high-volume ICU setting. Methods: ICU attendings were surveyed during morning rounds. Physicians were asked to conduct rounds normally, using data reported from nurse charts and briefs from fellows to inform their clinical decisions. After the physician finished their assessment and plan for the patient, they were asked to complete a questionnaire. Following completion of the questionnaire, the viewer was presented to ICU physicians on a tablet personal computer that displayed the patient's physiologic data (ie, shock index, blood pressure, heart rate, temperature, respiratory rate, and pulse oximetry), summarized for up to 72 hours. After examining the viewer, ICU physicians completed a postview questionnaire. In both questionnaires, the physicians were asked questions regarding the patient's stability, status, and need for a higher or lower level of care. A hierarchical clustering analysis was used to group participating ICU physicians and assess their general reception of the viewer. Results: A total of 908 anonymous surveys were collected from 28 ICU physicians from February 2015 to June 2017. Regarding physicians' perception of whether the viewer enhanced the ability to assess multiple patients in the ICU, 5% (45/908) strongly agreed, 56.6% (514/908) agreed, 35.3% (321/908) were neutral, 2.9% (26/908) disagreed, and 0.2% (2/908) strongly disagreed. Conclusions: Morning rounds in a trauma center ICU are conducted in a busy environment with many data sources. This study demonstrates that organized physiologic data and visual assessment can improve situation awareness, assist clinicians with recognizing changes in patient status, and prioritize care.
KW - clinical decision-making
KW - health information technology
KW - intensive care units
KW - patient care prioritization
KW - physiological monitoring
KW - visualization
KW - vital signs
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U2 - 10.2196/46030
DO - 10.2196/46030
M3 - Article
C2 - 38180791
AN - SCOPUS:85183960534
SN - 2292-9495
VL - 11
JO - JMIR Human Factors
JF - JMIR Human Factors
IS - 1
M1 - e46030
ER -