Differences in the Clinical Characteristics of Rapid Response System Activation in Patients Admitted to Medical or Surgical Services
Variability in rapid response system (RRS) characteristics based on the admitted wards is unknown. We aimed to compare differences in the clinical characteristics of RRS activation between patients admitted to medical versus surgical services. We reviewed patients admitted to the hospital who were d...
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Published in | Journal of Korean medical science Vol. 32; no. 4; pp. 688 - 694 |
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Main Authors | , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Korea (South)
The Korean Academy of Medical Sciences
01.04.2017
대한의학회 |
Subjects | |
Online Access | Get full text |
ISSN | 1011-8934 1598-6357 1598-6357 |
DOI | 10.3346/jkms.2017.32.4.688 |
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Abstract | Variability in rapid response system (RRS) characteristics based on the admitted wards is unknown. We aimed to compare differences in the clinical characteristics of RRS activation between patients admitted to medical versus surgical services. We reviewed patients admitted to the hospital who were detected by the RRS from October 2012 to February 2014 at a tertiary care academic hospital. We compared the triggers for RRS activation, interventions performed, and outcomes of the 2 patient groups. The RRS was activated for 460 patients, and the activation rate was almost 2.3 times higher for surgical services than that for medical services (70% vs. 30%). The triggers for RRS activation significantly differed between patient groups (P = 0.001). They included abnormal values for the respiratory rate (23.2%) and blood gas analysis (20.3%), and low blood pressure (18.8%) in the medical group; and low blood pressure (32.0%), low oxygen saturation (20.8%), and an abnormal heart rate (17.7%) in the surgical group. Patients were more likely classified as do not resuscitate or required intensive care unit admission in the medical group compared to those in the surgical group (65.3% vs. 54.7%, P = 0.045). In multivariate analysis, whether the patient belongs to medical services was found to be an independent predictor of mortality after adjusting for the modified early warning score, Charlson comorbidity index, and intervention performed by the RRS team. Our data suggest that RRS triggers, interventions, and outcomes greatly differ between patient groups. Further research is needed to evaluate the efficacy of an RRS approach tailored to specific patient groups. |
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AbstractList | Variability in rapid response system (RRS) characteristics based on the admitted wards is unknown. We aimed to compare differences in the clinical characteristics of RRS activation between patients admitted to medical versus surgical services. We reviewed patients admitted to the hospital who were detected by the RRS from October 2012 to February 2014 at a tertiary care academic hospital. We compared the triggers for RRS activation, interventions performed, and outcomes of the 2 patient groups. The RRS was activated for 460 patients, and the activation rate was almost 2.3 times higher for surgical services than that for medical services (70% vs. 30%). The triggers for RRS activation significantly differed between patient groups (P = 0.001). They included abnormal values for the respiratory rate (23.2%) and blood gas analysis (20.3%), and low blood pressure (18.8%) in the medical group; and low blood pressure (32.0%), low oxygen saturation (20.8%), and an abnormal heart rate (17.7%) in the surgical group. Patients were more likely classified as do not resuscitate or required intensive care unit admission in the medical group compared to those in the surgical group (65.3% vs. 54.7%, P = 0.045). In multivariate analysis, whether the patient belongs to medical services was found to be an independent predictor of mortality after adjusting for the modified early warning score, Charlson comorbidity index, and intervention performed by the RRS team. Our data suggest that RRS triggers, interventions, and outcomes greatly differ between patient groups. Further research is needed to evaluate the efficacy of an RRS approach tailored to specific patient groups. Variability in rapid response system (RRS) characteristics based on the admitted wards is unknown. We aimed to compare differences in the clinical characteristics of RRS activation between patients admitted to medical versus surgical services. We reviewed patients admitted to the hospital who were detected by the RRS from October 2012 to February 2014 at a tertiary care academic hospital. We compared the triggers for RRS activation, interventions performed, and outcomes of the 2 patient groups. The RRS was activated for 460 patients, and the activation rate was almost 2.3 times higher for surgical services than that for medical services (70% vs. 30%). The triggers for RRS activation significantly differed between patient groups (P = 0.001). They included abnormal values for the respiratory rate (23.2%) and blood gas analysis (20.3%), and low blood pressure (18.8%) in the medical group; and low blood pressure (32.0%), low oxygen saturation (20.8%), and an abnormal heart rate (17.7%) in the surgical group. Patients were more likely classified as do not resuscitate or required intensive care unit admission in the medical group compared to those in the surgical group (65.3% vs. 54.7%, P = 0.045). In multivariate analysis, whether the patient belongs to medical services was found to be an independent predictor of mortality after adjusting for the modified early warning score, Charlson comorbidity index, and intervention performed by the RRS team. Our data suggest that RRS triggers, interventions, and outcomes greatly differ between patient groups. Further research is needed to evaluate the efficacy of an RRS approach tailored to specific patient groups.Variability in rapid response system (RRS) characteristics based on the admitted wards is unknown. We aimed to compare differences in the clinical characteristics of RRS activation between patients admitted to medical versus surgical services. We reviewed patients admitted to the hospital who were detected by the RRS from October 2012 to February 2014 at a tertiary care academic hospital. We compared the triggers for RRS activation, interventions performed, and outcomes of the 2 patient groups. The RRS was activated for 460 patients, and the activation rate was almost 2.3 times higher for surgical services than that for medical services (70% vs. 30%). The triggers for RRS activation significantly differed between patient groups (P = 0.001). They included abnormal values for the respiratory rate (23.2%) and blood gas analysis (20.3%), and low blood pressure (18.8%) in the medical group; and low blood pressure (32.0%), low oxygen saturation (20.8%), and an abnormal heart rate (17.7%) in the surgical group. Patients were more likely classified as do not resuscitate or required intensive care unit admission in the medical group compared to those in the surgical group (65.3% vs. 54.7%, P = 0.045). In multivariate analysis, whether the patient belongs to medical services was found to be an independent predictor of mortality after adjusting for the modified early warning score, Charlson comorbidity index, and intervention performed by the RRS team. Our data suggest that RRS triggers, interventions, and outcomes greatly differ between patient groups. Further research is needed to evaluate the efficacy of an RRS approach tailored to specific patient groups. Variability in rapid response system (RRS) characteristics based on the admitted wards is unknown. We aimed to compare differences in the clinical characteristics of RRS activation between patients admitted to medical versus surgical services. We reviewed patients admitted to the hospital who were detected by the RRS from October 2012 to February 2014 at a tertiary care academic hospital. We compared the triggers for RRS activation, interventions performed, and outcomes of the 2 patient groups. The RRS was activated for 460 patients, and the activation rate was almost 2.3 times higher for surgical services than that for medical services (70% vs. 30%). The triggers for RRS activation significantly differed between patient groups ( P = 0.001). They included abnormal values for the respiratory rate (23.2%) and blood gas analysis (20.3%), and low blood pressure (18.8%) in the medical group; and low blood pressure (32.0%), low oxygen saturation (20.8%), and an abnormal heart rate (17.7%) in the surgical group. Patients were more likely classified as do not resuscitate or required intensive care unit admission in the medical group compared to those in the surgical group (65.3% vs. 54.7%, P = 0.045). In multivariate analysis, whether the patient belongs to medical services was found to be an independent predictor of mortality after adjusting for the modified early warning score, Charlson comorbidity index, and intervention performed by the RRS team. Our data suggest that RRS triggers, interventions, and outcomes greatly differ between patient groups. Further research is needed to evaluate the efficacy of an RRS approach tailored to specific patient groups. Variability in rapid response system (RRS) characteristics based on the admitted wards is unknown. We aimed to compare differences in the clinical characteristics of RRS activation between patients admitted to medical versus surgical services. We reviewed patients admitted to the hospital who were detected by the RRS from October 2012 to February 2014 at a tertiary care academic hospital. We compared the triggers for RRS activation, interventions performed, and outcomes of the 2 patient groups. The RRS was activated for 460 patients, and the activation rate was almost 2.3 times higher for surgical services than that for medical services (70% vs. 30%). The triggers for RRS activation significantly differed between patient groups (P = 0.001). They included abnormal values for the respiratory rate (23.2%) and blood gas analysis (20.3%), and low blood pressure (18.8%) in the medical group; and low blood pressure (32.0%), low oxygen saturation (20.8%), and an abnormal heart rate (17.7%) in the surgical group. Patients were more likely classified as do not resuscitate or required intensive care unit admission in the medical group compared to those in the surgical group (65.3% vs. 54.7%, P = 0.045). In multivariate analysis, whether the patient belongs to medical services was found to be an independent predictor of mortality after adjusting for the modified early warning score, Charlson comorbidity index, and intervention performed by the RRS team. Our data suggest that RRS triggers, interventions, and outcomes greatly differ between patient groups. Further research is needed to evaluate the efficacy of an RRS approach tailored to specific patient groups. KCI Citation Count: 0 |
Author | Suh, Jung-Won Park, Sangheon Park, Jong Sun Kim, Kyuseok Lee, Dong Seon Song, Inae Lee, Eun Young Lee, Jae Hyuk Choi, Yun Young Min, Hyunju Hwan, You Yoon, Yeonyee E. Lee, Yeon Joo Kim, Jin Won Cho, Young-Jae |
AuthorAffiliation | 3 Department of Emergency Medicine, Seoul National University Bundang Hospital, Seongnam, Korea 5 Department of Anesthesiology, Sheikh Khalifa Specialty Hospital, Ras Al Khaimah, United Arab Emirates 2 Department of Anesthesiology, Seoul National University Bundang Hospital, Seongnam, Korea 4 Interdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Korea 1 Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Korea |
AuthorAffiliation_xml | – name: 3 Department of Emergency Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – name: 1 Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – name: 5 Department of Anesthesiology, Sheikh Khalifa Specialty Hospital, Ras Al Khaimah, United Arab Emirates – name: 4 Interdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – name: 2 Department of Anesthesiology, Seoul National University Bundang Hospital, Seongnam, Korea |
Author_xml | – sequence: 1 givenname: Yeon Joo orcidid: 0000-0001-7697-4272 surname: Lee fullname: Lee, Yeon Joo organization: Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Korea., Interdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – sequence: 2 givenname: Dong Seon orcidid: 0000-0002-4917-5990 surname: Lee fullname: Lee, Dong Seon organization: Interdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – sequence: 3 givenname: Hyunju orcidid: 0000-0002-5974-3779 surname: Min fullname: Min, Hyunju organization: Interdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – sequence: 4 givenname: Yun Young orcidid: 0000-0002-2813-4479 surname: Choi fullname: Choi, Yun Young organization: Interdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – sequence: 5 givenname: Eun Young orcidid: 0000-0001-6718-6952 surname: Lee fullname: Lee, Eun Young organization: Interdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – sequence: 6 givenname: Inae orcidid: 0000-0001-9961-7593 surname: Song fullname: Song, Inae organization: Department of Anesthesiology, Seoul National University Bundang Hospital, Seongnam, Korea., Interdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – sequence: 7 givenname: Yeonyee E. orcidid: 0000-0002-8479-9889 surname: Yoon fullname: Yoon, Yeonyee E. organization: Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – sequence: 8 givenname: Jin Won orcidid: 0000-0002-1357-7015 surname: Kim fullname: Kim, Jin Won organization: Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – sequence: 9 givenname: Jong Sun orcidid: 0000-0003-3707-3636 surname: Park fullname: Park, Jong Sun organization: Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – sequence: 10 givenname: Young-Jae orcidid: 0000-0001-6943-4462 surname: Cho fullname: Cho, Young-Jae organization: Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Korea., Interdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – sequence: 11 givenname: Jae Hyuk orcidid: 0000-0003-2429-4085 surname: Lee fullname: Lee, Jae Hyuk organization: Department of Emergency Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – sequence: 12 givenname: Jung-Won orcidid: 0000-0002-0397-6071 surname: Suh fullname: Suh, Jung-Won organization: Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – sequence: 13 givenname: You orcidid: 0000-0002-9507-7603 surname: Hwan fullname: Hwan, You organization: Department of Emergency Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – sequence: 14 givenname: Kyuseok orcidid: 0000-0002-7991-9428 surname: Kim fullname: Kim, Kyuseok organization: Department of Emergency Medicine, Seoul National University Bundang Hospital, Seongnam, Korea., Interdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Korea – sequence: 15 givenname: Sangheon orcidid: 0000-0001-8563-7681 surname: Park fullname: Park, Sangheon organization: Department of Anesthesiology, Seoul National University Bundang Hospital, Seongnam, Korea., Interdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Korea., Department of Anesthesiology, Sheikh Khalifa Specialty Hospital, Ras Al Khaimah, United Arab Emirates |
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CitedBy_id | crossref_primary_10_1186_s12913_023_10375_0 crossref_primary_10_1007_s00540_021_02900_4 crossref_primary_10_1016_j_iccn_2021_103136 crossref_primary_10_1097_CCM_0000000000004571 crossref_primary_10_1186_s12931_021_01824_7 crossref_primary_10_4174_astr_2023_104_1_43 crossref_primary_10_1016_j_aucc_2020_11_006 crossref_primary_10_4266_acc_2019_00668 crossref_primary_10_1371_journal_pone_0210951 crossref_primary_10_1016_j_resuscitation_2020_01_021 crossref_primary_10_1111_jocn_15408 |
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Keywords | Intensive Care Unit Tertiary Care Centers Hospital Mortality Patient Admission Hospital Rapid Response Team |
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Snippet | Variability in rapid response system (RRS) characteristics based on the admitted wards is unknown. We aimed to compare differences in the clinical... |
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SubjectTerms | Aged Blood Gas Analysis Blood Pressure Female Heart Rate Hospital Mortality Hospital Rapid Response Team Hospitals, University Humans Intensive Care Units Male Middle Aged Multivariate Analysis Odds Ratio Original Oxygen Consumption Patient Admission - statistics & numerical data Respiratory Rate Retrospective Studies Tertiary Care Centers 의학일반 |
Title | Differences in the Clinical Characteristics of Rapid Response System Activation in Patients Admitted to Medical or Surgical Services |
URI | https://www.ncbi.nlm.nih.gov/pubmed/28244298 https://www.proquest.com/docview/1872878593 https://pubmed.ncbi.nlm.nih.gov/PMC5334170 https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002211297 |
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