Advanced units: quality measures in urgency and emergency care

Viola, Dan Carai Maia; Cordioli, Eduardo; Pedrotti, Carlos Henrique Sartorato; Iervolino, Mauro; Neto, Antonio da Silva Bastos; Almeida, Luis Roberto Natel de; Neves, Henrique Sutton de Sousa; Lottenberg, Claudio Luiz

doi:10.1590/s1679-45082014gs2894

Cited by 5 publications

(4 citation statements)

References 14 publications

(36 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is a private secondary service, working non-stop with urgent and emergency care of adults and children. In 2013, it managed 64,891 patient consults, or an average of 5400 per month [ 11 ]. Before this training, a single in situ simulation scenario was conducted in 2013, resulting in the detection of four LST [ 12 ].…”

Section: Methodsmentioning

confidence: 99%

Detecting latent safety threats in an interprofessional training that combines in situ simulation with task training in an emergency department

Couto

Barreto²,

Marcon³

et al. 2018

Adv Simul

View full text Add to dashboard Cite

BackgroundDuring in situ simulation, interprofessional care teams practice in an area where clinical care occurs. This study aimed to detect latent safety threats (LST) in a training program, which combined in situ simulation scenarios with just-in-time and just-in-place self-directed task training in an emergency department. We hypothesized this simulation-based training in actual care areas allows the detection of at least one LST per simulation scenario.MethodsThis prospective observational study (April 2015–March 2016) involved 135 physicians, nurses, and nurse technicians. Training themes selected were arrhythmia, respiratory insufficiency, shock, and cardiopulmonary resuscitation. Simulation weeks occurred every 3 months, with three 10-min scheduled in situ simulation scenarios alternating for each theme daily. The scenarios were followed by co-debriefing by two facilitators (a physician and a nurse). LST were identified by facilitators using a debriefing checklist. Additionally, a room was set up with task-trainers related to each theme.ResultsThe number participants in scenarios was 114 (84% of the population) and in task-training, 101. The number of scenario cancelations was nine, making the final total number to 49 of 58 proposed. Fifty-six LST were observed, with an average of 1.1 per scenario. LST were divided into four categories: equipment (n = 23, 41.1%), teamwork (n = 12, 21.4%), medication (n = 11, 19.6%), and others (n = 10, 17.9%). There was a higher proportion in equipment-related LST (p < 0.01).ConclusionsThe training allowed a high rate of detecting LST regardless of theme. Equipment-related LST were more frequently found.Electronic supplementary materialThe online version of this article (10.1186/s41077-018-0083-4) contains supplementary material, which is available to authorized users.

show abstract

Section: Methodsmentioning

confidence: 99%

Detecting latent safety threats in an interprofessional training that combines in situ simulation with task training in an emergency department

Couto

Barreto²,

Marcon³

et al. 2018

Adv Simul

View full text Add to dashboard Cite

show abstract

“…Patients who are categorized as level one require urgent care, while those as level two or three can be treated within a 15-minute window. Those with not-so-urgent needs belong to level four or five and can be addressed within 30 minutes [6].…”

Section: Introductionmentioning

confidence: 99%

Accuracy of Emergency Room Triage Using Emergency Severity Index (ESI): Independent Predictor of Under and Over Triage

Rashid¹,

Ullah²,

Ahmed³

et al. 2021

Cureus

View full text Add to dashboard Cite

IntroductionPatient saturation in emergency care departments is a significant issue that impacts the healthcare system globally. This study was purposed to evaluate the accuracy of the ER triage using the Emergency Severity Index (ESI). MethodologyA prospective observational study was performed at Hayatabad Medical Complex, Peshawar, from October 2020 to March 2021. Data from one of the second largest hospitals in Khyber Pakhtunkhwa were acquired to carry out this study. All data from our emergency department have been retrieved and recorded using appropriate procedures and software. Triage accuracy has been established by comparing proposed resource consumption (acuity level 3-5) to the actual resources utilized in these hospitals as the amount of an agreement between standard guidelines and local observations. In terms of resource expenditure, we also assessed the interconnection between acuity level and extent of accuracy. SPSS version 21 (

show abstract

“…Patients classified as level 1 need immediate medical care, patients classified as level 2 and 3 need care within 15 minutes, and those classified as level 4 and 5 need care within 30 minutes. ( 8 )…”

Section: Introductionmentioning

confidence: 99%

“…Priority is defined based on a flowchart with assessment of resources needed for adequate care, and by assuring that patients have access to resources in the right time. ( 8 )…”

Section: Introductionmentioning

confidence: 99%

Emergency Severity Index: accuracy in risk classification

Silva

Emi

Leão

et al. 2017

Einstein (São Paulo)

View full text Add to dashboard Cite

ObjectiveTo verify agreement between estimative of predicted resources using the adapted Emergency Severity Index and the real amount of resources used by patients. To analyze the variables number of years since graduation, years of work experience and years of experience in emergency services especially with accurate anticipation of resources need.MethodsThis retrospective analytical study with a quantitative approach included 538 medical records of patients assisted by 11 triage nurses. Data collected were related to assistances carried out from December 2012 to February 2013.ResultsThere was no significant association between the adequacy of the number of resources used, based on Emergency Severity Index score, number of years since graduation, year of work experience or years of experience in emergency services. Kappa agreement coefficient (0.34) showed that agreement was low between predicted and real used number of resources.ConclusionNurses’ accuracy index to predict resources for patients care from emergency room using the adapted Emergency Severity Index was lower than results reported in the studies in the literature that used the original scale. There was low agreement of diagnostic exams predicted by nurses and those really performed. There was no association among correct prediction of resources needed, number of years since graduation, years of experience in emergency services and years of work experience in the unit where the study was done.

show abstract

Advanced units: quality measures in urgency and emergency care

Cited by 5 publications

References 14 publications

Detecting latent safety threats in an interprofessional training that combines in situ simulation with task training in an emergency department

Detecting latent safety threats in an interprofessional training that combines in situ simulation with task training in an emergency department

Accuracy of Emergency Room Triage Using Emergency Severity Index (ESI): Independent Predictor of Under and Over Triage

Emergency Severity Index: accuracy in risk classification

Contact Info

Product

Resources

About