| Literature DB >> 35776738 |
Mohammad Rababa1, Dania Bani Hamad1, Audai A Hayajneh1.
Abstract
BACKGROUND: Early assessment and management of patients with sepsis can significantly reduce its high mortality rates and improve patient outcomes and quality of life.Entities:
Mesh:
Year: 2022 PMID: 35776738 PMCID: PMC9249173 DOI: 10.1371/journal.pone.0270711
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.752
The construction of review questions according to PICOS framework.
| Item | Description |
|---|---|
| Participants | patients aged 19 years and older who were admitted to critical care settings with sepsis, septic shock, or septicemia |
| Intervention | Training/educational interventions (e.g., regular lectures, simulations, algorithms, decision support tools, and sepsis protocol) |
| Comparison | No restriction was applied on the number or type of comparison group as the impact of the intervention could be determined. Comparison groups could include no intervention, standard protocol, and other types of intervention which was educational |
| Outcome | The primary outcomes of interest in this review were the effective assessment and prompt management of sepsis and nurses’ knowledge, attitudes, practice, perceived barriers, and enablers related to sepsis assessment and management. sepsis assessment and management could be assessed using either patient or nurse objective measures. Sepsis assessment and management were quantified as mean times required for sepsis recognition and treatment initiation, sepsis protocol adherence, and decline in mortality rate in-hospital sepsis-related complications. nurses’ knowledge, attitudes, and practice related to sepsis could be assessed using either nurse-reported tools or performance-based tests, while nurses’ perceived barriers and enablers could be assessed using nurse-reported tools. |
| Study Design | Experimental, quasi-experimental, description. Cross-sectional, observational, prospective, qualitative, and mixed methods |
Fig 1PRISMA flow chart.
Summary of the reviewed studies.
| Study | Aim of the study | Design | LOE | Setting/Sample | Main findings | Strengths/Weaknesses |
|---|---|---|---|---|---|---|
| Delaney et al. (2015) | To determine the impact of an educational program on nurses’ assessment & management of sepsis | Quasi-experimental | III | 82 ER nurses/ USA | There was a significant improvement in nurses’ knowledge & competency related to the early recognition & management of sepsis after the educational program. | |
| Breen and Rees (2018) | To identify the barriers to the implementation of sepsis protocols | Cross-sectional | VI | 108 nurses in ACS/UK | Nurses’ poor knowledge & poor ability to recognize sepsis during observation round were the main barriers to prompt sepsis management | |
| Roney et al. (2020) | To evaluate the implementation of MEW-S in ACS | Quasi-experimental | III | 139 nurses in ACS/ USA | Implementation of MEW-S led to a significant improvement in sepsis assessment & management, thus decreasing mortality rate by 24% | |
| N. Roberts et al.(2017) | To identify the barriers to and facilitators of the implementation of the Sepsis Six at a case study hospital | Mixed method | VI | 13 ER nurses /USA | The main barriers were insufficient audit & feedback, poor teamwork & communication, & insufficient training & resources. Main facilitators were good confidence in knowledge & skills & positive beliefs towards sepsis bundles | |
| van den Hengel et al. (2016) | To examine the factors influencing the knowledge & recognition of SIRS criteria & sepsis by ER nurses | Prospective -observational | IV | 216 ER nurses from 11 hospitals/ Netherlands | ER nurses aged over 50 had significantly lower scores in knowledge related to sepsis criteria than did younger nurses. Nurses working in hospitals with 3 level ICUs had more knowledge than did nurses working in hospitals with levels 1&2 ICUs. The educational program improved nurses’ knowledge of sepsis. | |
| Long et al. (2018) | To gain insight into clinical decision support systems-based alert and nurses’ perceptions | Cross-sectional | VI | 43 ER nurses/USA | Using clinical decision support systems-based alert improved nurses’ decision-making related to sepsis, thus leading to better outcomes | |
| Jacobs (2020) | To determine if implementing the NDS protocol reduces ACT readmission among patients with sepsis | Quasi-experimental | III | 238 patients with sepsis/ USA | Readmission rate among patients assessed & treated by NDS & who received early-goal directed therapy was reduced from 36.28% to 25% after 8 weeks. Nurses’ compliance with the intervention protocol was improved. | |
| Amland et al. (2015) | To examine the diagnostic accuracy of two-stage clinical decision support systems for the early recognition & management of sepsis | Observational cohort study | IV | 417 patients with sepsis/ USA | Nurses completed 75% of assessment and screening within one hour of notification. The decision support system led to the early identification and timely, quality, and safe sepsis care | |
| Delawder and Hulton (2020) | To test the effectiveness of sepsis bundle guidelines in the early assessment & treatment of sepsis. | Quasi-experimental | III | 214 ER patients /USA | There was an improvement in the time to implement sepsis guidelines, except for antibiotic administration & blood culture collection. Mortality rate decreased from 12.45% to 4.55% but no differences in mortality rate based on age or gender | |
| Manaktala & Claypool (2017) | To evaluate the impact of a computerized surveillance algorithm & decision support system on sepsis mortality rates | Quasi-experimental | III | 58 patients in Huntsville hospital (tertiary care teaching hospital/ USA) | The system was sensitive & specific for sepsis identification & management & improved decision-making related to sepsis management. Mortality rate was reduced by 53% & readmission rate was reduced, with no effect on patient length of stay | |
| Harley et al. (2019) | To explore and understand ER nurses’ knowledge of sepsis & identify gaps in clinical practice related to sepsis management. | Qualitative | VI | 14 ER nurses/ Australia | Nurses had poor knowledge, attitudes, & practices related to sepsis assessment & management. Barriers to sepsis management included high number & severity of sepsis conditions, nurses’ poor knowledge of sepsis, heavy workloads, & inexperienced ER doctors | |
| Yousefi et al. (2012) | To review the effect of an educational program on nurses’ knowledge, attitudes, & practices related to the identification & management of sepsis | Quasi-experimental | III | 64 ICU nurses/ Iran | Nurses’ knowledge, attitudes, & practices were improved after the intervention | |
| Nucera et al. (2018) | To assess knowledge and attitudes related to sepsis among ICU and non-ICU nurses and physicians | Quasi- experimental | III | 11 different wards (ICU and non-ICU) in Italy | Nurses’ attitudes towards blood culture technique were poor & their knowledge of blood culture procedures & sepsis risks was good (>75%). Nurses had poor knowledge (<50%) of methods for the early identification, diagnosis, & management of sepsis. Their knowledge of sepsis improved after the intervention educational program | |
| Rahman et al. (2019) | To explore nurses’ knowledge & attitudes related to the early identification & management of sepsis | Cross-sectional | VI | 120 ER in Malaysia | Nurses had poor knowledge of & neutral attitudes towards sepsis. | |
| Storozuk et al., (2019) | To assess ER nurses’ knowledge of sepsis & their perspectives towards caring for patients with sepsis | Cross-sectional | VI | 758 ER nurses/ Canada | Most nurses had poor knowledge of sepsis & SIRS definition, general knowledge, & treatment. Nurses were aware of the need to update their knowledge related to the early identification & timely management of sepsis to reduce complications | |
| Gyang et al. (2015) | To evaluate the use of NDS for early sepsis identification | Observational pilot | IV | 245 patients with sepsis in intermediate care settings/ USA | The NDS had 95% sensitivity and 92% specificity. | |
| El Khuri et al. (2019) | To assess the effect of EGDT in the ER on mortality rates related to sepsis and septic shock | Retrospective cohort | IV | 290 patients with sepsis from one large tertiary hospital in Lebanon | There were no differences between the two groups in time & duration of vasopressor, antibiotics, and length of stay. The implementation of EGDT in the ER decreased the mortality rate from 47.6% to 31.7%. The most common cause of infection leading to sepsis was LRTI. | |
| Vanderzwan et al. (2020) | To apply a multimodel nursing pedagogy with medium fidelity simulation senarios for the early identification & management of sepsis | Quasi-experimental | III | All critical care nurses in an academic medical center/ USA | Nurses’ knowledge & competency related to the early identification & management of sepsis improved after simulation | |
| R. J. Roberts et al. (2017) | To evaluate nurses’ knowledge, attitudes, & perceptions related to antibiotic innitiation for patients with sepsis | Cross-sectional | VI | 122 critical care nurses/ USA | Nurses had good knowledge related to defining septic shock & were aware of Aware of when to administer antibiotics. Lack of awareness of the importance of antibiotics initiation, lack of IV access, & the need for multiple medications rather than antibiotics were major barriers to sepsis management | |
| McKinley et al. (2011) | To compare between paper protocols & computerized protocols for standarizing sepsis decision-making | Quasi- experimental | III | 948 ICU nurses in an academic tertiery hospital in the USA | The computerized protocol led to quicker antibiotic administration, blood culture collection, and lactate level checking as compared to the paper-based protocol. The computerize protocol had 97% sensitivity & 97% specificity to the standardized & rapid implementation of evidence-based treatment guidelines of sepsis | |
| Drahnak et al. (2016) | To assess the impact of an educational program on nurses’ knowledge, perceptions, & attitudes related to sepsis | Quasi-experimental | III | 680 ICU & ER nurses/ Pennsylvania, USA | Knowledge of sepsis was improved after the educational program. There was significant improvement in nurses’ ability to identify patients with sepsis | |
| Proffitt and Hooper (2020) | To assess nurses’ perceptions towards the implementation of the 106 q-sofa assessment tool for sepsis | Quasi-experimental | III | 14 ER nurses/ USA | The use of this tool led nurses to become more autonomous in making decisions related to sepsis, thus leading to prompt management of sepsis. Nurses perceived the lack of time to be a barrier to the implementation of the evidence-based treatment guidelines | |
| Rajan and Rodzevik (2021) | To explore the differences between ER nurses receiving an educational program on the early identification & management of sepsis & nurses not receiving the program | Quasi- experimental | III | 22 ER nurses/ USA | Using sepsis standing orders combined with the educational program contributed to the early identification of sepsis and better quality of care provided. | |
| Oliver (2018) | To assess the impact of EGDT on the early detection of sepsis in an ED | Quasi-experimental | III | 63 patients with sepsis /USA | Revealed no significant differences in lactate measurement and blood culture collection but a decrease in time until antibiotic administration | |
| Burney et al. (2012) | To identify the barriers related to sepsis treatment | Descriptive-cross sectional | VI | 101 ER nurses/ USA | Shortage of nurses, unavailability of ICU beds and limited physical space in were the most reported barriers to sepsis treatment | |
| Edwards & Jones (2021) | To examine nurses’ levels of knowledge, attitude, and skills related to sepsis management | Descriptive-cross sectional | VI | 98 acute medical-surgical nurses/ UK | Nurses incorrectly answered the questions related to knowledge of sepsis and demonstrated positive attitudes. | |
| Steinmo el al. (2015) | To explore the effect of using behavioral science tools to modify the existing quality improvement guidelines for “Sepsis Six” implementation | Qualitative | VI | 19 ER nurses, 12 ER doctors, 2 midwives and 1 healthcare assistant/ UK | Using behavioral science tools was feasible to modify the existing quality improvement guidelines for “Sepsis Six” implementation. The tools are compatible with the currently used pragmatic approach. | |
| Giuliano et al. (2005) | to examine nurses’ understanding of clinical practice related to assessment of sepsis as well as their knowledge of diagnostic criteria for sepsis | Descriptive-cross sectional | VI | 517 nurses& 100 physicians/ USA | The majority of participants routinely use the findings of PAP, Bp, O2 Sat, and ECG to assess and manage sepsis | |
| Ferguson et al. (2019) | To assess the effectiveness of QI initiative in improving the early assessment and management of sepsis | Retrospective cohort | IV | 106,220 patients with sepsis from a medical center in Seatle/USA | The implementation of QI improved ER sepsis bundle adherence by 33.2%, decreased sepsis-related RRT calls by 1.35% & in-hospital sepsis-related mortality rate by 4.1% (p<0.001) | |
| Giuliano et al. (2010) | To examine the difference in mean times required for sepsis recognition and treatment initiation between nurses exposed to 2 different monitor displays in response to simulated case scenarios of sepsis | Quasi-experimental | III | 75 critical care nurses/ USA | mean times required for sepsis recognition and treatment initiation were shorter nurses exposed to EBM. | |
| Kabil et al. (2021) | To explore ER nurses’ experiences of initiating early goal-directed fluid resuscitation in patients with sepsis | Qualitative | VI | 10 ER nurses/ Australia | participating nurses identified different factors limiting the prompt initiation of early goal-directed fluid resuscitation, some challenges to the clinical practice of sepsis, and solutions to these challenges. Most nurses suggested incorporating nurse-initiated early goal-directed fluid resuscitation for patients with sepsis. |
USA: United States of America; UK; United Kingdom; ACS: acute care settings; ER: emergency room; ICU: intensive care units; SIRS: Systematic Inflammatory Response Syndrome; KAP: knowledge, attitudes, and practice; qSOFA: Quick Sequential Organ Failure Assessment; EGDT; Early Goal-Directed Therapy; NDS: Nurse Driven Sepsis Screening tool; SIRS: Sepsis Inflammatory Response; MEW-S: Modified Early Warning Score; LRTI: Lower respiratory tract infection; IQ: Quality Improvement; EBM: Enhanced Bedside Monitor; RRT: rapid response team.
Knowledge, attitudes, and practices related to sepsis assessment and management.
| Study | Knowledge (Mean Score, interpretation) | Attitudes (Mean Score, interpretation) | Practices (Mean Score, interpretation) |
|---|---|---|---|
| Van den Hengel et al. (2016) | 15.9±3.21, above average | N/A | N/A |
| Rahman et al. (2018) | MNR, Moderate | N/A | |
| Storozuk et al. (2019) | N/A | N/A | |
| Harley et al. (2019) | MNR, Poor | N/A | N/A |
| Nucera et al. (2018) | MNR, Good | N/A | |
| R.J. Roberts et al. (2017) | MNR, Good | N/A, positive | MNR, good |
| Yousefi et al. (2012) | 64.5±5.21, MNR | 73±4.51, MNR | 81±4.31, MNR |
| Edwards & Jones (2021) | 40.8%, Poor | 25±2.97, positive | N/A |
| Giuliano et al. (2005) | MNR | N/A | N/A |
*A range of the score reported
¥ a percentage of correct answers reported; MNR: Measured but not reported; N/A: Not Applicable
The barriers to and facilitators of sepsis assessment and management.
| Barriers | ||
|---|---|---|
| Patient-related barriers | Nurse-related barriers | System-related barriers |
| • Complexity and atypical presentation of the early symptoms of sepsis | • Nurses’ poor level of education and clinical experience | • Lack of written sepsis treatment protocols or guidelines adopted as hospital policies |
|
| ||
| Nurse-related | System-related | |
| • Nurses’ improved confidence in caring for patients with sepsis | • Enhanced consistency in sepsis treatment | |
A summary of the measurement tools and their psychometric properties.
| Study | Name of the tool | Measured variable(s) | Description of the tool | # of items | Total score | Validity | Reliability | Piloted |
|---|---|---|---|---|---|---|---|---|
| Van den Hengel et al. (2016) | Self-developed questionnaire | Knowledge of sepsis and SIRS criteria | General information about sepsis, SIRS, protocol, treatments, & case studies | 35 | 29 | Validated by expert panel | 0.53 | No |
| Oliver (2018) | Self-developed questionnaire | knowledge & practices related to antibiotic administration for sepsis | Information about sepsis management protocol & barriers to rapid antibiotic administration | NR | NR | NR | NR | Yes |
| Rahman et al. (2019) | Self-developed questionnaire | Knowledge & attitudes towards sepsis | Questions on the indicators of SIRS, sepsis criteria, case scenarios, and attitudes towards the early identification and management of sepsis | 39 | 39 | Face & content validity were assessed | 0.86 | Yes |
| Storozuk et al. (2019) | Self-developed questionnaire | Knowledge of sepsis | Questions about the signs & symptoms of sepsis, sepsis criteria, definition of sepsis, at- risk patients, & treatment | 225 | NR | NR | NR | Yes |
| Harley et al. (2019) | Self-developed questionnaire | Knowledge of sepsis | Questions on sepsis, sepsis criteria, SIRS, q SOFA, nursing role, & barriers to the early identification of sepsis | 22 | NR | Qualitative content analysis | N/A | No |
| Nucera et al. (2018) | Self-developed questionnaire | Knowledge & attitudes towards sepsis | Questions on the riskiest sepsis procedures, knowledge about the early identification of sepsis, & attitudes towards blood culture collection techniques | 26 | NR | NR | 0.88 | Yes |
| Edwards & Jones (2021) | Self-developed questionnaire | Knowledge, skills & attitudes towards sepsis | Closed & open-ended questions on nurses’ opinions and experiences regarding sepsis | 24 | NR | NR | NR | Yes |
| Yousefi et al. (2012) | KAP | Knowledge, attitudes, & practices related to sepsis | Questions about knowledge, attitudes, & practices related to sepsis | 46 | NR | Content validity was assessed | 77–90.7 | No |
| Giuliano et al. (2005) | Self-developed questionnaire | Knowledge of diagnostics criteria for sepsis | Questions about the physiologic parameters routinely used to assess for sepsis | 20 | NR | NR | Not measured | No |
SIRS: Systematic Inflammatory Response Syndrome; KAP: knowledge, attitudes, and practice; NR: not reported; qSOFA: Quick Sequential Organ Failure Assessment
* Cronbach’s Alpha
Sepsis education programs and simulations.
| Study | Intervention/Control | Assessment Times | Measured Variable(s) | Differences in Posttest Scores Between Groups |
|---|---|---|---|---|
| Delaney et al. (2015) | Post intervention | +0.22 | ||
| Yousefi et al. (2012) | I: received one PPT session (8 hour) about sepsis care, treatment, prevention, principles, nosocomial infections, and guidelines integrated with pamphlets. Assessed nurses’ knowledge, attitudes, and practices three times (pre-intervention, immediately post intervention, and three weeks post intervention). | Pre-intervention, immediately post intervention, & three weeks post intervention. | ||
| Drahnak (2016) | *I: received one session (30 minutes) with a voice-over slide presentation & role-play case study focusing on the pathophysiology of sepsis, risk factors for sepsis, SSC guidelines, case studies, and assessment of sepsis, integrated with HER | Before the educational program | Knowledge | +56.22 |
| Rajan et al. (2021) | I: received a structured educational session (15 minutes) focused on SIRS criteria, sepsis criteria, policy, sepsis screening tools, and sepsis standing order. | Post intervention | Time for sepsis identification | -33 minutes |
| Vanderzwan et al. (2020) | *I: received medium fidility simulation for 15 minutes. Nurses also received educational session about CLMS. | LMS & one week post simulation | Knowledge retention & | outcomes improved after simulation |
| Giuliano et al. (2010) | I: exposed to EBM display which is a continuous visual display of combinations of recent data trends & parameters to promote early recognition of sepsis in response to a computer-simulated scenarioC: exposed to SBM display of 5 parameters including BP, ECG, PAP, CO, and O2 Sat which need to be intereprted by clinicans to meaningful data in response to a computer-simulated scenario • All partciapnts received educational program on sepsis assessment and management based on SSC guidelines | Immediately Pre-intervention & post intervention | Response time to the different monitor displays | Similar responses |
*one group only; MNR: Measured but not reported, IHI bundles: Institute for Healthcare Improvement; HLCC; Health literacy and culture competency; EGDT; Early Goal Directed Therapy; SST: Staging sepsis Team; CLM: computerized Learning Management Systems; HER: Electronic Health Record; I: Intervention; C: Control; EBM: Enhanced Bedside Monitor; SBM: Standard Bedside Monitor; CDSS: Clinical Decision Support System
Sepsis decision-making support and screening tools and treatment protocols.
| Study | Decision tool/sepsis protocol or tool | Description of the tool or protocol | Main effects on patient outcomes |
|---|---|---|---|
| Manaktala et al. (2017) | Sepsis Survilence Algorithim | The screening tool assesses sepsis clinical parameters (physical exam & lab test) & sends alam signals to nurses about positive findings. | Sepsis mortality rate was reduced by 53% & 30 day readmission was reduced from 19.08% to 13.21%. The tool sensitivity & specificity were 95% and 82%, respectively. |
| Amland et al. (2015) | Sepsis alert (Binary alarm system) | The tool consists of two steps. The first step is the detection of actual or potential sepsis, and the second is screening & stratification conducted within 15 minutes | 89% of septic patients were detected by the alert system, & screening and stratification was completed for 75% of the cases within an hour from notification. The tool sensitivity was 94%. |
| Long et al. (2018) | User interface alert | User interface alert was designed for medical systems to a provide computer support system for decision-making related to sepsis | The tool enhanced reliability & specificty of patient data for detecting sepsis & provided an effective clinical decision support system for nurses to innititate sepsis assessment & management |
| Delawder et al. (2019) | Sepsis alert algorithim | Sepsis alert algorithim was designed to initiate full screening of sepsis when the nurse receives an electronic notification. This alert depends on the SIRS criteria & SSC guidelines | The alert algorithm can improve the time taken to implement sepsis guidelines except for antibiotics administration & blood culture collection. Mortality rate was decreased from 12.45% to 4.55%. |
| Proffitt et al. (2020) | qSOFA | It includes 2 parts, the first part being the assessment of potential infection & the second part being the assessment of Q-SOFA score, which is calculated based on GCS, systolic BP & RR. | The use of qSOFA led nurses to become more autonomous in making decisions related to sepsis management. The median time from ER admission to triage evaluation was reduced by 9 minutes. |
| McKinley et al. (2011) | TMH | If the patient had MAP<65 mmHg, LL >4 mmol/L, or U.O <0.5 mg/kg/hr, diagnostic tests, broad spectrum antibiotics, & fluid were initiated, and the lactate test was repeated after 4 hours. If the patient met two or more of the previous criteria, central venous line application would be added to the management plan | Time taken to initiate antibiotic administration, blood culture collection, & lactate level assessment & nurses’ compliance to sepsis treatment guidelines were improved, and the mortality rate declined with the use of TMH. The sensitivity & specificity of the TMH were 97%. |
| Oliver et al. (2018) | EGDT & NDS | The protocols are based on the SSC guidelines, and focus on blood culture, lactate measurement, and antibiotic administration | No significant differences in lactate measurement & blood culture collection were identified, but the time taken for antibiotic administration was improved. |
| Roney et al. (2020) | MEW-S | This tool was used for the early identification of at-risk patients based on the early signs of status deterioration according to body temperature, BP, RR, LOC, WBC, U.O & L.L. | MEW-S facilitated the early identification of sepsis & provision of timely management. The mortality rate declined by 24%. |
| Jacobs et al. (2020) | NDS | This tool was developed based on the SSC guidelines & had 4 steps: (1) measure lactate level, (2) take blood culture, (3) provide broad spectrum antibiotics, (4) administer 30 ml/kg crystalloid fluid if hypotensive & LL > 4 mmol/L, & (5) measure bilirubin, creatinine, GCS, MAP, RR, PT, PTT & platelets account. | The readmission rate was reduced from 36.28% to 25% 8 weeks after the NDS protocol, and compliance to the sepsis intervention protocol improved but with no effect on mortality rate. |
| Gyang et al. (2015) | NDS | Developed based on the SSC guidelines: (1) if the patient met >2 of the SIRS criteria>>> suspected sepsis; (2) if the patient screened >2 SIRS criteria >>> confirmed sepsis and presence of infection; (3) document findings in EHR & call physician | The tool sensitivity and specificity were 95.5% and 91.9%, respectively. |
| El-khuri et al. (2019) | EGDT | Developed based on the SSC guidelines depending on the following measurements: SIRS criteria, vital signs, U.O, O2 level, cardiac index, & continuous monitoring | There were no differences between the two groups in time and duration of vasopressor, antibiotic administration, or length of stay. However, the mortality rate was decreased from 47.6% to 31.7% with the implementation of EGDT. |
| Ferguson et al. (2019) | QI | Developed based on the SSC guidelines with few modifications: (1) administer 2 L of fluid instead of 30 ml/kg (2) apply it on patients with suspected infection, and (3) with 2 or more SIRS criteria | ER sepsis bundle adherence was improved by 33.2%, sepsis-related RRT calls was decreased by 1.35% & in-hospital sepsis-related mortality rate by was decreased 4.1% (p<0.001) |
qSOFA: Quick Sequential Organ Failure Assessment; TMH: The Methodist Hospital; NDS: Nurse Driven Sepsis Screening tool; EGDT: Early Goal-Directed Therapy; SSC: Surviving Sepsis Campaign; SIRS: Sepsis Inflammatory Response; HER: Electronic Health Records; UO: Urine Output; O2: oxygen; Map: Mean Arterial Pressure; GCS: Glasgow Coma Scale; RR: Respiratory Rate; PT: Prothrombin Time; PTT: Partial Thromboplastin Time; LL: Lactate level; QI: Quality Improvement; RRT: rapid response team.