Rapid Response System Activation Research Articles

Sepsis Bundle Compliance and Mortality according to Body Temperature of Patients with Sepsis in General Wards Identified Using the Rapid Response System

Purpose : This study aimed to investigate the difference in compliance with the sepsis bundle and mortality rates according to the body temperature of patients with sepsis in general wards identified using a rapid response system (RRS). Methods : A retrospective observational study of 1,083 patients with sepsis in general wards identified using the RRS from July 2018 to December 2022 was performed at a tertiary care hospital in South Korea. The patients were classified into hypothermia (＜36℃), normothermia (36-38℃), and hyperthermia (＞38℃) groups according to their body temperature at the time of RRS activation. Results : A total of 1,083 sepsis patients were analyzed, comprising 17 cases of hypothermia, 624 cases of normothermia, and 442 cases of hyperthermia. There were statistically significant differences among the body temperature groups in the rate of compliance with the sepsis bundle within 1 h (hypothermia: 64.7% vs. normothermia: 49.5% vs. hyperthermia: 60.4%, <i>p</i> =.010), the rate of compliance with the overall sepsis bundle, including lactate re-measurement (64.7% vs. 49.5% vs. 60.4%, <i>p</i> =.001), and the rate of blood culture testing (94.1% vs. 85.9% vs. 92.8%, <i>p</i> =.002). The 28-day mortality rates in the hypothermia, normothermia, and hyperthermia groups were 29.4%, 32.4%, and 16.5%, respectively (<i>p</i> ＜.001). Conclusion : There were statistically significant differences in compliance with the sepsis bundle and mortality rates according to body temperature. Patients with sepsis and normothermia showed lower compliance with the sepsis bundle and higher mortality rates. Therefore, it is recommended to develop strategies for the early recognition of patients with sepsis and normothermia and to improve compliance with the sepsis bundle.

Characteristics and outcomes of patients screened by the rapid response team and transferred to intensive care unit in South Korea

The rapid response system (RRS) is associated with a reduction in in-hospital mortality. This study aimed to determine the characteristics and outcomes of patients transferred to the intensive care unit (ICU) by a rapid response team (RRT). This retrospective, multicenter cohort study included patients from nine hospitals in South Korea. Adult patients who were admitted to the general ward (GW) and required RRS activation were included. Patients with do-not-resuscitate orders and without lactate level or Sequential Organ Failure Assessment score were excluded. A total of 8228 patients were enrolled, 3379 were transferred to the ICU. The most common reasons for RRT activation were respiratory distress, sepsis and septic shock. The number of patients who underwent interventions, the length of hospital stays, 28-day mortality, and in-hospital mortality were higher in the ICU group than in the GW group. Factors that could affect both 28-day and in-hospital mortality included the severity score, low PaO2/FiO2 ratio, higher lactate and C-reactive protein levels, and hospitalization time prior to RRT activation. Patients admitted to the ICU after RRT activation generally face more challenging clinical situations, which may affect their survival outcomes.

Acute Care Nurses' Partnership With Patients to Recognise and Respond to Changes in Patients' Clinical States: AQualitative Study.

To explore and describe acute care nurses' partnership with patients to recognise and respond to changes in patients' clinical states. Acute care nurses' decisions to partner with patients to recognise deterioration in clinical states and to respond by activating a rapid response system improves patient outcomes. Acutely unwell patients can also experience clinical changes that include improvement and deterioration that does not trigger rapid response system activation over the course of hospitalisation from illness and treatment. How acute care nurses partner with patients in response to improvement and deterioration not triggering a rapid response system is not well-understood. An exploratory, descriptive study underpinned by Tanner's Clinical Judgement Model. Using purposive and quota sampling, 20 nurses with direct patient care responsibilities on one medical and one surgical ward in a large Australian hospital were recruited. Nonparticipant observations followed by semistructured interviews were conducted between January and May of 2021. Nurse-patient interactions were observed for 4 h, and verbally described and recorded. Semistructured interviews were recorded and explored nurses' reasoning behind decisions observed. Reflexive thematic analysis was used to analyse the data. Three themes were identified from the data: nurses checking in for changes; nurses forming judgements; and nurses partnering with patients to respond. Acute care nurses promoted subjective assessment based on patients' safety risks. Patients' participation in response to changes was prioritised based on acute care nurses' judgement of safety. Patients receive significant safety benefits when acute care nurses partner with patients in response to their experience of improvement and deterioration during acute illness. Further research should evaluate the sensitivity of subjective cues in patient assessment. Partnership with patients in assessment and management of improvement and deterioration improves the quality and safety of patient care. Assessment frameworks should equally prioritise the use of objective and subjective cues. Nursing education should promote the safety benefits of patient partnerships in responding to patient changes. Equator checklist COREQ. Data collected included description of patients' interactions with study participants.

Machine learning algorithm for predicting 30-day mortality in patients receiving rapid response system activation: A retrospective nationwide cohort study

This study investigated the accuracy of a machine learning algorithm for predicting mortality in patients receiving rapid response system (RRS) activation. This retrospective cohort study used data from the In-Hospital Emergency Registry in Japan, which collects nationwide data on patients receiving RRS activation. The missing values in the dataset were replaced using multiple imputations (mode imputation, BayseRidge sklearn. linear model, and K-nearest neighbor model), and the enrolled patients were randomly assigned to the training and test cohorts. We established prediction models for 30-day mortality using the following four types of machine learning classifiers: Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting, random forest, and neural network. Fifty-two variables (patient characteristics, details of RRS activation, reasons for RRS initiation, and hospital capacity) were used to construct the prediction algorithm. The primary outcome was the accuracy of the prediction model for 30-day mortality. Overall, the data from 4,997 patients across 34 hospitals were analyzed. The machine learning algorithms using LightGBM demonstrated the highest predictive value for 30-day mortality (area under the receiver operating characteristic curve, 0.860 [95 % confidence interval, 0.825–0.895]). The SHapley Additive exPlanations summary plot indicated that hospital capacity, site of incidence, code status, and abnormal vital signs within 24 h were important variables in the prediction model for 30-day mortality.

Risk Factors for Deterioration Events in the Pediatric Acute Care Setting.

Rapid response system (RRS) activations resulting in emergency transfers (ETs) and codes outside the ICU are associated with increased mortality and length of stay. We aimed to evaluate the patient and care team characteristics of RRS activations resulting in ETs and codes outside the ICU (together classified as "deterioration events") versus those that did not result in a deterioration event. For each RRS activation at our institution from 2019 to 2021, data were gathered on patient demographics and medical diagnoses, care team and treatment factors, and ICU transfer. Descriptive statistics, bivariate analyses, and multivariable logistic regression using a backward elimination model selection method were performed to assess potential risk factors for deterioration events. Over the 3-year period, 1765 RRS activations were identified. Fifty-three (3%) activations were deemed acute care codes, 64 (4%) were noncode ETs, 921 (52%) resulted in nonemergent transfers to an ICU, and 727 (41%) patients remained in an acute care unit. In a multivariable model, any complex chronic condition (adjusted odds ratio, 6.26; 95% confidence interval, 2.83-16.60) and hematology/oncology service (adjusted odds ratio, 2.19; 95% confidence interval, 1.28-3.74) were independent risk factors for a deterioration event. Patients with medical complexity and patients on the hematology/oncology service had a higher risk of deterioration events than other patients with RRS activations. Further analyzing how our hospital evaluates and treats these specific patient populations is critical as we develop targeted interventions to reduce deterioration events.

A cross-sectional study on the nurses’ attitude towards rapid response system activation for clinically deteriorated patients

A cross-sectional study on the nurses’ attitude towards rapid response system activation for clinically deteriorated patients

The Hospitalist-Oncologist co-ManagemEnt (HOME) system improves hospitalization outcomes of patients with cancer

BackgroundThe hospitalist system has been introduced to improve the quality and safety of inpatient care. As its effectiveness has been confirmed in previous studies, the hospitalist system is spreading in various fields. However, few studies have investigated the feasibility and value of hospitalist-led care of patients with cancer in terms of quality and safety measures. This study aimed to evaluate the efficacy of the Hospitalist-Oncologist co-ManagemEnt (HOME) system.MethodsBetween January 1, 2019, and January 31, 2021, we analyzed 591 admissions before and 1068 admissions after the introduction of HOME system on January 1, 2020. We compared the length of stay and the types and frequencies of safety events between the conventional system and the HOME system, retrospectively. We also investigate rapid response system activation, cardiopulmonary resuscitation, unplanned intensive care unit transfer, all-cause in-hospital mortality, and 30-day re-admission or emergency department visits.ResultsThe average length of stay (15.9 days vs. 12.9 days, P < 0.001), frequency of safety events (5.6% vs. 2.8%, P = 0.006), rapid response system activation (7.3% vs. 2.2%, P < 0.001) were significantly reduced after the HOME system introduction. However, there was no statistical difference in frequencies of cardiopulomonary resuscitation and intensive care unit transfer, all-cause in-hospital morality, 30-day unplanned re-admission or emergency department visits.ConclusionsThe study suggests that the HOME system provides higher quality of care and safer environment compared to conventional oncologist-led team-based care, and the efficiency of the medical delivery system could be increased by reducing the hospitalization period without increase in 30-day unplanned re-admission.

NURSE-LED proactive rounding and automatic early-warning score systems to prevent resuscitation incidences among Adults in ward-based Hospitalised patients

ObjectivesIn this study, we investigated the impact of critical care outreach implemented to overcome the problem of rapid response system (RRS) activation. The aim was to evaluate the impact of nurse-led proactive rounding on the rate of adverse events in a hospital setting using an automatic early-warning score system, without a call-activated team. MethodsThis observational study was conducted at a university hospital in Japan. Beginning in September 2019, critical care outreach via nurse-led proactive rounding of the general ward was conducted, using an automatic early-warning score system. We retrospectively assessed the computerised records of all inpatient days (N = 497,284) of adult inpatients admitted to the hospital from September 2017 to 2020. We compared the adverse event occurrences before and after implementation of the critical care outreach program. The main outcome measures were: unexpected death in the general ward, code blue (an in-hospital resuscitation request code directed towards all staff via broadcast) for non-intensive care unit inpatients and unexpected intensive care unit admissions from the general ward. The secondary outcome was the proportion of patients who received respiratory rate measurement. ResultsThe incidence rate ratios of the occurrence of unexpected deaths (0.19, 95% confidence interval: 0.04–0.57) and code blue in the general ward (0.15, 95% confidence interval: 0.025–0.50) decreased. There was no change in unexpected intensive care unit admissions from the general ward (1.25, confidence interval: 0.84–1.82). The proportion of patients who received respiratory rate measurement increased (10.2% vs 16.2%). ConclusionOur results suggest that in RRSs, drastic control of the failure of the mechanism to activate a response team may produce positive outcomes. Proactive rounding that bypasses the mechanism to activate a response team component of RRSs may relieve ward nurses of activation failure responsibility and help them overcome the hierarchical hospital structure.

Automated rapid response system activation-Impact on nurses' attitudes and perceptions towards recognising and responding to clinical deterioration: Mixed-methods study.

To explore general ward nurses' attitudes and perceptions towards recognising and responding to clinical deterioration in a hospital with automated rapid response system activation. There is growing interest in deploying automated clinical deterioration notification systems to reduce delayed or failed recognition and response to clinical deterioration of ward patients. However, little is known about its impact on ward nurses' perspectives and work patterns. A mixed-methods study. Online survey of 168 registered nurses and individual interviews with 10 registered nurses in one acute hospital in Singapore. The study adhered to the STROBE checklist for cross-sectional studies and the COREQ guidelines for qualitative studies. Many nurses (38.1%) rarely performed patient assessments or observations other than vital signs assessment to assess for early signs of clinical deterioration. About 30% were worried about being criticised for calling the primary team doctors. Four themes emerged from the qualitative analysis: automated rapid response system activation as a safety net, being more cautious with vital signs monitoring, the NEWS2 alone is inadequate, and ward nurses as the 'middleman' between the intensive care unit outreach nurse and primary team doctors. Although nurses value the automated rapid response system activation as a safety net to minimise delays in accessing urgent critical care resources, it does not address the sociocultural barriers inherent in escalation of care. Although the automated system led nurses to be more cautious with vital signs monitoring, it does not encourage them to perform comprehensive patient assessments to detect early signs of deterioration. Nurse education on assessing for clinical deterioration should focus on the use of broader patient assessment skills other than vital signs. Sociocultural barriers to escalation of care remain a key issue that needs to be addressed by hospital management. No patients, service users, care-givers or members of the public were involved in the study.

Effect of Diurnal Variation of Heart Rate and Respiratory Rate on Activation of Rapid Response System and Clinical Outcome in Hospitalized Children.

Heart rate and respiratory rate display circadian variation. Pediatric single-parameter rapid response system is activated when heart rate or respiratory rate deviate from age-specific criteria, though activation criteria do not differentiate between daytime and nighttime, and unnecessary activation has been reported due to nighttime bradycardia. We evaluated the relationship between rapid response system activation and the patient’s clinical outcome by separately applying the criteria to daytime and nighttime in patients < 18. The observation period was divided into daytime and nighttime (8:00−20:00, and 20:00 to 8:00), according to which measured heart rate and respiratory rate were divided and rapid response system activation criteria were applied. We classified lower nighttime than daytime values into the ‘decreased group’, and the higher ones into the ‘increased group’, to analyze their effect on cardiopulmonary resuscitation occurrence or intensive care unit transfer. Nighttime heart rate and respiratory rate were lower than the daytime ones in both groups (both p values < 0.001), with no significant association with cardiopulmonary resuscitation occurrence or intensive care unit transfer in either group. Heart rate and respiratory rate tend to be lower at nighttime; however, their effect on the patient’s clinical outcome is not significant.

Incidence and factors associated with newly implemented do-not-attempt-resuscitation orders among deteriorating patients after rapid response system activation: A retrospective observational study using a Japanese multicenter database.

The rapid response system (RRS) was initially aimed to improve patient outcomes. Recently, some studies have implicated that RRS might facilitate do-not-attempt-resuscitation (DNAR) orders among patients, their families, and healthcare providers. This study aimed to examine the incidence and factors independently associated with DNAR orders newly implemented after RRS activation among deteriorating patients. This observational study assessed patients who required RRS activation between 2012 and 2021 in Japan. We investigated patients' characteristics and the incidence of new DNAR orders after RRS activation. Furthermore, we used multivariable hierarchical logistic regression models to explore independent predictors of new DNAR orders. We identified 7904 patients (median age, 72 years; 59% male) who required RRS activation at 29 facilities. Of the 7066 patients without pre-existing DNAR orders before RRS activation, 394 (5.6%) had new DNAR orders. Multivariable hierarchical logistic regression analyses revealed that new DNAR orders were associated with age category (adjusted odds ratio [aOR], 1.56; 95% confidence interval, 1.12-2.17 [65-74 years old reference to 20-64 years old], aOR, 2.56; 1.92-3.42 [75-89 years old], and aOR, 6.58; 4.17-10.4 [90 years old]), malignancy (aOR, 1.82; 1.42-2.32), postoperative status (aOR, 0.45; 0.30-0.71), and National Early Warning Score 2 (aOR, 1.07; 1.02-1.12 [per 1 score]). The incidence of new DNAR orders was one in 18 patients after RRS activation. The factors associated with new DNAR orders were age, malignancy, postoperative status, and National Early Warning Score 2.

Predictors of in-hospital Mortality After Rapid Response System Activation in a Newly Established Tertiary Hospital

Predictors of in-hospital Mortality After Rapid Response System Activation in a Newly Established Tertiary Hospital

Chest pain in patients recovering from noncardiac surgery: A retrospective analysis

Study objectiveChest pain is relatively common postoperatively. Myocardial infarction (MI) is one cause of chest pain after surgery, but chest pain also results from less severe conditions. Because of its potential severity, chest pain usually prompts the activation of Rapid Response Systems (RRS). While chest pain is a cardinal symptom of myocardial ischemia in the non-surgical setting, the significance and relevance of chest pain after noncardiac surgery remains unclear. DesignWe conducted a retrospective analysis of noncardiac surgical inpatients for whom postoperative chest pain triggered our multidisciplinary RRS. SettingSurgical wards at Cleveland Clinic, Cleveland, OH. PatientsPostsurgical patients after noncardiac surgery in whom the RSS system was activated for chest pain. InterventionsRRS specified interventions like ECG readings, troponin measurements, transfer to ICU. MeasurementsOur primary outcome was MI. Secondary outcomes included the proportion of patients who had an ECG performed, troponin measurements, echocardiography, cardiac catheterization, and were admitted to the Intensive Care Unit (ICU). Main results5850 surgical patients experienced postoperative chest pain and triggered an RRS activation between 2009 and 2019. A total of 3110 patients had troponin T measured within 6 h after RRS activation, and 538 of them (17%) had elevated troponin, meeting the Fourth Universal Definition criteria for MI. Additionally, 2 patients had ST-segment elevation infarction (STEMI) without troponin measurement. Among the 540 patients with MI, only 19 (3.5%) were diagnosed with a STEMI by ECG, 388 (72%) had echocardiography, 43 patients (8%) had cardiac catheterization, 8 patients (1.5%) required emergent cardiac surgery, and 424 (79%) were admitted to an ICU. ConclusionChest pain is a serious clinical sign, often indicating a postoperative myocardial infarction, and therefore should be taken seriously. Troponin screening should be routinely considered in postsurgical patients who report chest pain.

Medication-related Medical Emergency Team activations: a case review study of frequency and preventability

ObjectivesDespite recognition of clinical deterioration and medication-related harm as patient safety risks, the frequency of medication-related Rapid Response System activations is undefined. We aimed to estimate the incidence and preventability...

P023 Impact of a colour-code monitoring plan on Rapid Response System activation: a before and after analysis study

P023 Impact of a colour-code monitoring plan on Rapid Response System activation: a before and after analysis study

Impact of the Proactive Rounding Team on Rapid Response System During COVID-19 Pandemic: A Retrospective Study From an Italian Medical Center.

Objective: During the coronavirus disease 2019 (COVID-19) pandemic a proactive rounding (PR) team was introduced in our clinical practice in order to recognize the clinical deterioration of the patient as soon as possible. This study aimed to evaluate the impact of the PR team on the rapid response system (RRS) workload with particular regard to the activity carried out, the mode of intervention, and the outcome of patients.Methods: In this retrospective study, the first period before the activation of the PR team (March 1, 2019, to February 29, 2020) and the second period after its activation (March 1, 2020, to March 1, 2021) were compared.Results: A total of 406 inpatient RRS activations were collected. The medical emergency team (MET) dose was 13 and 12.2 activations/1000 admitted patients per year while the incidence of unexpected cardiac arrests was 3.8 and 2.6 events/1000 admitted patients per year (p=0.10). MET response time was longer in the second period (3.5±1.6 minutes vs 4.5±2.6 minutes p<0.01). We recorded more RRS activations for medical patients than surgical ones; MET was activated more frequently by physicians than nurses and for less severe criteria. Patients admitted to the intensive care unit had lower Simplified Acute Physiology Score II (SAPS II) scores.Conclusions: The PR team introduced during the COVID-19 pandemic did not increase the RRS workload. In addition, it allowed an earlier activation of the MET, especially by physicians.

Effect of implementing decision support to activate a rapid response system by automated screening of verified vital sign data: A retrospective database study

AimActivating a rapid response system (RRS) at general wards requires memorizing trigger criteria, identifying deterioration, and timely notification of abnormalities. We aimed to assess the effect of decision support (DS)-linked RRS activation on management and outcomes. MethodsWe retrospectively analyzed general ward RRS activation cases from 2013 to 2017 and the incidence of cardiopulmonary resuscitations (CPR) from 2013 to 2020. A DS-alerting mechanism was added to the conventional RRS activation process in 2017, with an alert window appearing whenever the system automatically detected any verified abnormal vital sign entry, alerting the nurse to take further action. Logistic and linear regression analyses were used to compare outcomes. ResultsWe analyzed 27,747 activations and 64,592 DS alerts. RRS activations increased from 3.5 to 30.3 per 1,000 patient-days (P < 0.001) after DS implementation. The first DS activations occurred earlier than conventional ones (−2.9 days, 95% confidence interval = −3.6 to −2.1 days). After adjustment with inverse probability of treatment weighting, main (conventional vs DS-linked activations after implementation) and sensitivity analyses showed that DS activation cases had a lower risk of CPR and in-hospital mortality. Cases with more DS alerts before RRS activation had a higher risk of CPR (P trend = 0.017) and in-hospital mortality (P trend < 0.001). The incidence of CPR at the general ward decreased. ConclusionImplementing a DS mechanism with an automated screening of verified abnormal vital signs linked to RRS activations at general wards was associated with improved practice and timeliness of hospital-wide RRS activations and reduced in-hospital resuscitations and mortality.

Trends of in-hospital cardiac arrests in a single tertiary hospital with a mature rapid response system.

Most studies on rapid response system (RRS) have simply focused on its role and effectiveness in reducing in-hospital cardiac arrests (IHCAs) or hospital mortality, regardless of the predictability of IHCA. This study aimed to identify the characteristics of IHCAs including predictability of the IHCAs as our RRS matures for 10 years, to determine the best measure for RRS evaluation. Data on all consecutive adult patients who experienced IHCA and received cardiopulmonary resuscitation in general wards between January 2010 and December 2019 were reviewed. IHCAs were classified into three groups: preventable IHCA (P-IHCA), non-preventable IHCA (NP-IHCA), and inevitable IHCA (I-IHCA). The annual changes of three groups of IHCAs were analyzed with Poisson regression models. Of a total of 800 IHCA patients, 149 (18.6%) had P-IHCA, 465 (58.1%) had NP-IHCA, and 186 (23.2%) had I-IHCA. The number of the RRS activations increased significantly from 1,164 in 2010 to 1,560 in 2019 (P = 0.009), and in-hospital mortality rate was significantly decreased from 9.20/1,000 patients in 2010 to 7.23/1000 patients in 2019 (P = 0.009). The trend for the overall IHCA rate was stable, from 0.77/1,000 patients in 2010 to 1.06/1,000 patients in 2019 (P = 0.929). However, while the incidence of NP-IHCA (P = 0.927) and I-IHCA (P = 0.421) was relatively unchanged over time, the incidence of P-IHCA decreased from 0.19/1,000 patients in 2010 to 0.12/1,000 patients in 2019 (P = 0.025). The incidence of P-IHCA could be a quality metric to measure the clinical outcomes of RRS implementation and maturation than overall IHCAs.

Characteristics of In-Hospital Patients with Congenital Heart Disease Requiring Rapid Response System Activations: A Japanese Database Study

Objectives: This study aimed to study the characteristics of in-hospital deterioration in patients with congenital heart disease who required rapid response system activation and identify risk factors associated with 1-month mortality. Methods: We retrospectively analysed data from a Japanese rapid response system registry with 35 participating hospitals. We included consecutive patients with congenital heart disease who required rapid response system activation between January 2014 and March 2018. Logistic regression analyses were performed to examine the associations between 1-month mortality and other patient-specific variables. Results: Among 9,607 patients for whom the rapid response system was activated, only 82 (0.9%) had congenital heart disease. Only few patients with congenital heart disease were being treated at the cardiology and cardiovascular surgery departments (12.3% and 9.9%, respectively). Moreover, the incidences of rapid-response events after intensive care unit discharge or surgery were low (6.8% and 12.2%, respectively). The most common reason for rapid response system activation was respiratory dysfunction (desaturation: 35.4%, tachypnoea: 25.6%, and new dyspnoea: 19.5%). Rapid response system interventions and intensive care unit transfers were required for 65.9% and 20.7% of patients, respectively. The mortality rate was 1.2% at the end of the rapid response system intervention and 11.0% after 1 month. Moreover, decreased respiratory rate and decreased heart rate at rapid response system activation were associated with increased 1-month mortality. The adjusted odds ratio was 1.10 (95% confidence interval 1.02–1.19) and 1.02 (95% confidence interval, 1.00–1.04 for respiratory rate and heart rate, respectively. Conclusions: Rapid response systems were rarely activated after cardiac surgery and intensive care unit discharge, which were situations with a high risk of sudden deterioration in patients with congenital heart disease. Therefore, encouraging the use of the rapid response system in these departments will enable intervention by a third, specialised team for in-hospital emergencies and help provide comprehensive medical care to patients. Furthermore, 1-month mortality was associated with vital signs at rapid response system activation. These findings may guide treatment selection for patients with congenital heart disease showing deterioration.

Effect of a Wireless Vital Sign Monitoring System on the Rapid Response System in the General Ward

While wireless vital sign monitoring is expected to reduce the vital sign measurement time (thus reducing the nursing workload), its impact on the rapid response system is unclear. This study compared the time from vital sign measurement to recording and rapid response system activation between wireless and conventional vital sign monitoring in the general ward, to investigate the impact of wireless vital sign monitoring system on the rapid response system. The study divided 249 patients (age > 18 years; female: 47, male: 202) admitted to the general ward into non-wireless (n = 101) and wireless (n = 148) groups. Intervals from vital sign measurement to recording and from vital sign measurement to rapid response system activation were recorded. Effects of wireless system implementation for vital sign measurement on the nursing workload were surveyed in 30 nurses. The interval from vital sign measurement to recording was significantly shorter in the wireless group than in the non-wireless group (4.3 ± 2.9 vs. 44.7 ± 14.4 min, P < 0.001). The interval from vital sign measurement to rapid response system activation was also significantly lesser in the wireless group than in the non-wireless group (27.5 ± 12.9 vs. 41.8 ± 19.6 min, P = 0.029). The nursing workload related to vital sign measurement significantly decreased from 3 ± 0.87 to 2.4 ± 9.7 (P = 0.021) with wireless system implementation. Wireless vital sign monitoring significantly reduced the time to rapid response system activation by shortening the time required to measure the vital signs. It also significantly reduced the nursing workload.