Performance of patient acuity rating by rapid response team nurses for predicting short-term prognosis

Hyung Jun Kim, Hyun Ju Min, Dong Seon Lee, Yun Young Choi, Miae Yoon, Da Yun Lee, In ae Song, Jun Yeun Cho, Jong Sun Park, Young Jae Cho, You Hwan Jo, Ho Il Yoon, Jae Ho Lee, Choon Taek Lee, Yeon Joo Lee

Research output: Contribution to journalArticle

Abstract

Background Although scoring and machine learning methods have been developed to predict patient deterioration, bedside assessment by nurses should not be overlooked. This study aimed to evaluate the performance of subjective bedside assessment of the patient by the rapid response team (RRT) nurses in predicting short-term patient deterioration. Methods Patients noticed by RRT nurses based on the vital sign instability, abnormal laboratory results, and direct contact via phone between November 1, 2016, and December 12, 2017, were included. Five RRT nurses visited the patients according to their shifts and assessed the possibility of patient deterioration. Patient acuity rating (PAR), a scale of 1–7, was used as the tool of bedside assessment. Other scores, including the modified early warning score, VitalPAC early warning score, standardised early warning score, and cardiac arrest risk triage, were calculated afterwards. The performance of these scores in predicting mortality and/or intensive care unit admission within 1 day was compared by calculating the area under the receiver operating curve. Results A total of 1,426 patients were included in the study, of which 258 (18.1%) died or were admitted to the intensive care unit within 1 day. The area under the receiver operating curve of PAR was 0.87 (95% confidence interval [CI] 0.84–0.89), which was higher than those of modified early warning score (0.66, 95% CI 0.62–0.70), VitalPAC early warning score (0.69, 95% CI 0.66–0.73), standardised early warning score (0.67, 95% CI 0.63–0.70) and cardiac arrest risk triage (0.63, 95% CI 0.59–0.66) (P<0.001). Conclusions PAR assessed by RRT nurses can be a useful tool for assessing short-term patient prognosis in the RRT setting.

Original languageEnglish
Article numbere0225229
JournalPLoS ONE
Volume14
Issue number11
DOIs
StatePublished - 1 Jan 2019

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Patient Acuity
nurses
prognosis
Deterioration
Intensive care units
Nurses
Confidence Intervals
confidence interval
Learning systems
Triage
Heart Arrest
cardiac arrest
Intensive Care Units
deterioration
Vital Signs
rating scales
artificial intelligence
direct contact
Mortality

Cite this

@article{a6e3ed1f35824764aaab062ddb6db534,
title = "Performance of patient acuity rating by rapid response team nurses for predicting short-term prognosis",
abstract = "Background Although scoring and machine learning methods have been developed to predict patient deterioration, bedside assessment by nurses should not be overlooked. This study aimed to evaluate the performance of subjective bedside assessment of the patient by the rapid response team (RRT) nurses in predicting short-term patient deterioration. Methods Patients noticed by RRT nurses based on the vital sign instability, abnormal laboratory results, and direct contact via phone between November 1, 2016, and December 12, 2017, were included. Five RRT nurses visited the patients according to their shifts and assessed the possibility of patient deterioration. Patient acuity rating (PAR), a scale of 1–7, was used as the tool of bedside assessment. Other scores, including the modified early warning score, VitalPAC early warning score, standardised early warning score, and cardiac arrest risk triage, were calculated afterwards. The performance of these scores in predicting mortality and/or intensive care unit admission within 1 day was compared by calculating the area under the receiver operating curve. Results A total of 1,426 patients were included in the study, of which 258 (18.1{\%}) died or were admitted to the intensive care unit within 1 day. The area under the receiver operating curve of PAR was 0.87 (95{\%} confidence interval [CI] 0.84–0.89), which was higher than those of modified early warning score (0.66, 95{\%} CI 0.62–0.70), VitalPAC early warning score (0.69, 95{\%} CI 0.66–0.73), standardised early warning score (0.67, 95{\%} CI 0.63–0.70) and cardiac arrest risk triage (0.63, 95{\%} CI 0.59–0.66) (P<0.001). Conclusions PAR assessed by RRT nurses can be a useful tool for assessing short-term patient prognosis in the RRT setting.",
author = "Kim, {Hyung Jun} and Min, {Hyun Ju} and Lee, {Dong Seon} and Choi, {Yun Young} and Miae Yoon and Lee, {Da Yun} and Song, {In ae} and Cho, {Jun Yeun} and Park, {Jong Sun} and Cho, {Young Jae} and Jo, {You Hwan} and Yoon, {Ho Il} and Lee, {Jae Ho} and Lee, {Choon Taek} and Lee, {Yeon Joo}",
year = "2019",
month = "1",
day = "1",
doi = "10.1371/journal.pone.0225229",
language = "English",
volume = "14",
journal = "PloS one",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "11",

}

Performance of patient acuity rating by rapid response team nurses for predicting short-term prognosis. / Kim, Hyung Jun; Min, Hyun Ju; Lee, Dong Seon; Choi, Yun Young; Yoon, Miae; Lee, Da Yun; Song, In ae; Cho, Jun Yeun; Park, Jong Sun; Cho, Young Jae; Jo, You Hwan; Yoon, Ho Il; Lee, Jae Ho; Lee, Choon Taek; Lee, Yeon Joo.

In: PLoS ONE, Vol. 14, No. 11, e0225229, 01.01.2019.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Performance of patient acuity rating by rapid response team nurses for predicting short-term prognosis

AU - Kim, Hyung Jun

AU - Min, Hyun Ju

AU - Lee, Dong Seon

AU - Choi, Yun Young

AU - Yoon, Miae

AU - Lee, Da Yun

AU - Song, In ae

AU - Cho, Jun Yeun

AU - Park, Jong Sun

AU - Cho, Young Jae

AU - Jo, You Hwan

AU - Yoon, Ho Il

AU - Lee, Jae Ho

AU - Lee, Choon Taek

AU - Lee, Yeon Joo

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Background Although scoring and machine learning methods have been developed to predict patient deterioration, bedside assessment by nurses should not be overlooked. This study aimed to evaluate the performance of subjective bedside assessment of the patient by the rapid response team (RRT) nurses in predicting short-term patient deterioration. Methods Patients noticed by RRT nurses based on the vital sign instability, abnormal laboratory results, and direct contact via phone between November 1, 2016, and December 12, 2017, were included. Five RRT nurses visited the patients according to their shifts and assessed the possibility of patient deterioration. Patient acuity rating (PAR), a scale of 1–7, was used as the tool of bedside assessment. Other scores, including the modified early warning score, VitalPAC early warning score, standardised early warning score, and cardiac arrest risk triage, were calculated afterwards. The performance of these scores in predicting mortality and/or intensive care unit admission within 1 day was compared by calculating the area under the receiver operating curve. Results A total of 1,426 patients were included in the study, of which 258 (18.1%) died or were admitted to the intensive care unit within 1 day. The area under the receiver operating curve of PAR was 0.87 (95% confidence interval [CI] 0.84–0.89), which was higher than those of modified early warning score (0.66, 95% CI 0.62–0.70), VitalPAC early warning score (0.69, 95% CI 0.66–0.73), standardised early warning score (0.67, 95% CI 0.63–0.70) and cardiac arrest risk triage (0.63, 95% CI 0.59–0.66) (P<0.001). Conclusions PAR assessed by RRT nurses can be a useful tool for assessing short-term patient prognosis in the RRT setting.

AB - Background Although scoring and machine learning methods have been developed to predict patient deterioration, bedside assessment by nurses should not be overlooked. This study aimed to evaluate the performance of subjective bedside assessment of the patient by the rapid response team (RRT) nurses in predicting short-term patient deterioration. Methods Patients noticed by RRT nurses based on the vital sign instability, abnormal laboratory results, and direct contact via phone between November 1, 2016, and December 12, 2017, were included. Five RRT nurses visited the patients according to their shifts and assessed the possibility of patient deterioration. Patient acuity rating (PAR), a scale of 1–7, was used as the tool of bedside assessment. Other scores, including the modified early warning score, VitalPAC early warning score, standardised early warning score, and cardiac arrest risk triage, were calculated afterwards. The performance of these scores in predicting mortality and/or intensive care unit admission within 1 day was compared by calculating the area under the receiver operating curve. Results A total of 1,426 patients were included in the study, of which 258 (18.1%) died or were admitted to the intensive care unit within 1 day. The area under the receiver operating curve of PAR was 0.87 (95% confidence interval [CI] 0.84–0.89), which was higher than those of modified early warning score (0.66, 95% CI 0.62–0.70), VitalPAC early warning score (0.69, 95% CI 0.66–0.73), standardised early warning score (0.67, 95% CI 0.63–0.70) and cardiac arrest risk triage (0.63, 95% CI 0.59–0.66) (P<0.001). Conclusions PAR assessed by RRT nurses can be a useful tool for assessing short-term patient prognosis in the RRT setting.

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U2 - 10.1371/journal.pone.0225229

DO - 10.1371/journal.pone.0225229

M3 - Article

C2 - 31725773

AN - SCOPUS:85075060558

VL - 14

JO - PloS one

JF - PloS one

SN - 1932-6203

IS - 11

M1 - e0225229

ER -