scholarly journals Time from triage to initial physician assessment: A 5-year retrospective analysis

2019 ◽  
Vol 15 (3) ◽  
Author(s):  
Mor Saban ◽  
Nadav Armoni ◽  
Heli Patito ◽  
Tal Shachar ◽  
Aziz Darawsha ◽  
...  
Keyword(s):  
Waiting Times ◽  
Tertiary Hospital ◽  
Time Lags ◽  
Physician Assessment ◽  
Evaluation Time ◽  
Patient Arrival ◽  
Emergency Department Triage ◽  
Urgency Rating ◽  
Physician Adherence ◽  
Triage Classification

The aim of the study is to examine whether physicians adhere to the urgency classification as determined by the Canadian Triage and Acuity Scale. A retrospective-archive study was conducted in a tertiary hospital from January 2011 to December 2015. For each patient, we examined the relation between the urgency rating set by the triage nurse and the waiting time for the physician. Additionally, we explored the relationships between waiting times for physicians and several subgroups: patient arrival time, season of the year, assigned care area, and first consultant to examine the patient, using Analysis of Variance (ANOVA) analysis. There were 392,687 unique visits during the study period. The distribution of the classification was heterogeneous: 7,133 (1.8%) patients were classified as Priority (P) P1; 17,318 as P2 (4.4%); 148,657 as P3 (37.8%); 113,502 as P4 (28.9%); and 106,077 as P5 (27%). Median and interquartile ranges for time from triage until physician assessment, by triage group, were: P1, 0.7 minutes (0.2-24); P2, 35 minutes (13-76); P3, 44 minutes (21-88); P4, 45 minutes (20-87); and P5, 46 minutes (22-88). Percentages of visits that met the evaluation time goals, by triage classification, were: P1, 61%; P2, 27%; P3, 37%; P4, 61%; and P5, 85%. ANOVA test for the four subgroups revealed statistically significant differences (P<.001). In conclusion, the standard goals for time to physician evaluation are not being met, and there is little difference in time to evaluation between the P3, P4, and P5 classifications. Initiation of system-wide changes in physician workflow and awareness may improve physician adherence to triage classification, shorten time lags, and improve patient evaluation. Further research may allow for better understanding of the factors influencing triage adherence and reinforce teamwork among Emergency Department triage nurses and physicians.

scholarly journals Assessment of patients waiting and service times in the ophthalmology clinic of a public tertiary hospital in Nigeria

2020 ◽  
Vol 54 (4) ◽  
pp. 231-237
Author(s):  
Lateefat B. Olokoba ◽  
Kabir A. Durowade ◽  
Feyi G. Adepoju ◽  
Abdulfatai B. Olokoba
Keyword(s):  
Waiting Time ◽  
Waiting Times ◽  
Sampling Technique ◽  
Tertiary Hospital ◽  
Cross Sectional Study ◽  
Ethical Review ◽  
Cross Sectional ◽  
Arrival Times ◽  
The Mean ◽  
Service Times

Introduction: Long waiting time in the out-patient clinic is a major cause of dissatisfaction in Eye care services. This study aimed to assess patients’ waiting and service times in the out-patient Ophthalmology clinic of UITH. Methods: This was a descriptive cross-sectional study conducted in March and April 2019. A multi-staged sampling technique was used. A timing chart was used to record the time in and out of each service station. An experience based exit survey form was used to assess patients’ experience at the clinic. The frequency and mean of variables were generated. Student t-test and Pearson’s correlation were used to establish the association and relationship between the total clinic, service, waiting, and clinic arrival times. Ethical approval was granted by the Ethical Review Board of the UITH. Result: Two hundred and twenty-six patients were sampled. The mean total waiting time was 180.3± 84.3 minutes, while the mean total service time was 63.3±52.0 minutes. Patient’s average total clinic time was 243.7±93.6 minutes. Patients’ total clinic time was determined by the patients’ clinic status and clinic arrival time. Majority of the patients (46.5%) described the time spent in the clinic as long but more than half (53.0%) expressed satisfaction at the total time spent at the clinic. Conclusion: Patients’ clinic and waiting times were long, however, patients expressed satisfaction with the clinic times.

Patient arrival pattern and waiting time analysis for a tertiary hospital radiology department

2019 ◽  
Vol 25 (3) ◽  
pp. 136-143
Author(s):  
Felicitas Ugochinyere Idigo ◽  
Kenneth Kalu Agwu ◽  
Obinna Emmanuel Onwujekwe ◽  
Mark Chukwudi Okeji ◽  
Angel-Mary Chukwunyelu Anakwue
Keyword(s):  
Waiting Time ◽  
Tertiary Hospital ◽  
Radiology Department ◽  
Time Analysis ◽  
Patient Arrival ◽  
Arrival Pattern

scholarly journals Discrete event simulation for problem solving in the context of an emergency department

2020 ◽  
Vol 11 (5) ◽  
pp. 1515
Author(s):  
Letícia Ali Figueiredo Ferreira ◽  
Igor Leão dos Santos ◽  
Ana Carla De Souza Gomes dos Santos ◽  
Augusto Da Cunha Reis
Keyword(s):  
Length Of Stay ◽  
Discrete Event Simulation ◽  
Waiting Times ◽  
Discrete Event ◽  
Saturation Point ◽  
Event Simulation ◽  
Emergency Care System ◽  
Patient Arrival ◽  
The Subject

Emergency departments (ED) are responsible for the immediate care and stabilization of patients in critical health conditions. Several factors have caused overcrowding in the emergency care system, but the variability of patient arrival and the triage process requires special attention. The criticality of these components and their configuration directly impact the waiting times, length of stay and quality of service, being the subject of several studies. So, this paper aims to understand by means of Discrete Event Simulation how ED works with the variation of patient arrival and how this variation highlights the bottlenecks of the triage process. Varying the patient arriving interval between 0.1 and 7.6 in a 4-hour scenario,  the system saturation point was established in β = 1.1. Besides, with the variation in the number of triages points, a considerable decrease in the total length of stay spent and the waiting times were noticed, mainly when there was two triage points operating simultaneously.

scholarly journals Exploring emergency department visits: factors influencing individuals’ decisions, knowledge of triage systems and waiting times, and experiences during visits to a tertiary hospital in Saudi Arabia

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Nawaf Alhabdan ◽  
Faisal Alhusain ◽  
Abdulkareem Alharbi ◽  
Muatassem Alsadhan ◽  
Moath Hakami ◽  
...  
Keyword(s):  
Primary Care ◽  
Emergency Department ◽  
Primary Care Physicians ◽  
Waiting Times ◽  
Tertiary Hospital ◽  
Cross Sectional Study ◽  
Care Physician ◽  
Emergency Department Visits ◽  
Cross Sectional ◽  
Validated Questionnaire

Abstract Background In recent years, there has been an increased utilization of emergency departments (EDs) in many countries. Additionally, it is reported that there are major delays in delivering care to ED patients. Longer waiting times are associated with poor patient satisfaction, whereas an understanding of the triage process increases satisfaction. This study aimed to assess ED visitor’s awareness of the triage procedure and their preferences regarding delayed communication. Methods Cross-sectional study of King Abdulaziz Medical City – Emergency Department visitors using a previously validated questionnaire (Seibert 2014) which was translated to Arabic, piloted, and then used for this study. Results A total of 334 questionnaires were returned. The mean age of respondents was 33 years. Regarding primary care physicians, only 16% of respondents said that they have one. About 21% of those tried to communicate with them before coming to the ED. Even though only 11% of respondents knew exactly what triage is, 51% were able to correctly explain why some patients are seen before others. Statistical analysis did not show any factors that are associated with increased knowledge of triage. Most respondents (75%) want to hear updates regarding delays with 69% of them preferring to be updated every 30 min. Conclusions This study showed that the majority of patients do not know what triage means and that most of them want to know how the ED works. Moreover, a lot of respondents said that they do not have a primary care physician. These results support increasing patient awareness by education and involving them if any delay happens.

Impact of a Two-step Emergency Department Triage Model with START, then CTAS, on Patient Flow During a Simulated Mass-casualty Incident

2015 ◽  
Vol 30 (4) ◽  
pp. 390-396 ◽  
Author(s):  
James S. Lee ◽  
Jeffrey M. Franc
Keyword(s):  
Emergency Department ◽  
Patient Flow ◽  
Mass Casualty Incident ◽  
Mass Casualty ◽  
Mean Difference ◽  
Time Intervals ◽  
Simulation Exercise ◽  
Physician Assessment ◽  
Emergency Department Triage ◽  
The Difference

AbstractIntroductionA high influx of patients during a mass-casualty incident (MCI) may disrupt patient flow in an already overcrowded emergency department (ED) that is functioning beyond its operating capacity. This pilot study examined the impact of a two-step ED triage model using Simple Triage and Rapid Treatment (START) for pre-triage, followed by triage with the Canadian Triage and Acuity Scale (CTAS), on patient flow during a MCI simulation exercise.Hypothesis/ProblemIt was hypothesized that there would be no difference in time intervals nor patient volumes at each patient-flow milestone.MethodsPhysicians and nurses participated in a computer-based tabletop disaster simulation exercise. Physicians were randomized into the intervention group using START, then CTAS, or the control group using START alone. Patient-flow milestones including time intervals and patient volumes from ED arrival to triage, ED arrival to bed assignment, ED arrival to physician assessment, and ED arrival to disposition decision were compared. Triage accuracy was compared for secondary purposes.ResultsThere were no significant differences in the time interval from ED arrival to triage (mean difference 108 seconds; 95% CI, -353 to 596 seconds; P=1.0), ED arrival to bed assignment (mean difference 362 seconds; 95% CI, -1,269 to 545 seconds; P=1.0), ED arrival to physician assessment (mean difference 31 seconds; 95% CI, -1,104 to 348 seconds; P=0.92), and ED arrival to disposition decision (mean difference 175 seconds; 95% CI, -1,650 to 1,300 seconds; P=1.0) between the two groups. There were no significant differences in the volume of patients to be triaged (32% vs 34%; 95% CI for the difference -16% to 21%; P=1.0), assigned a bed (16% vs 21%; 95% CI for the difference -11% to 20%; P=1.0), assessed by a physician (20% vs 22%; 95% CI for the difference -14% to 19%; P=1.0), and with a disposition decision (20% vs 9%; 95% CI for the difference -25% to 4%; P=.34) between the two groups. The accuracy of triage was similar in both groups (57% vs 70%; 95% CI for the difference -15% to 41%; P=.46).ConclusionExperienced triage nurses were able to apply CTAS effectively during a MCI simulation exercise. A two-step ED triage model using START, then CTAS, had similar patient flow and triage accuracy when compared to START alone.LeeJS, FrancJM. Impact of a two-step emergency department triage model with START, then CTAS, on patient flow during a simulated mass-casualty incident. Prehosp Disaster Med. 2015;30(4):1–7.

scholarly journals Patient waiting time Analysis at Service Points in the Ultrasound Unit of a Nigerian Teaching Hospital

2020 ◽  
Vol 34 (1) ◽  
pp. 29-36
Author(s):  
F U Idigo ◽  
N I Chijioke ◽  
A C Anakwue ◽  
U B Nwogu
Keyword(s):  
Teaching Hospital ◽  
Waiting Time ◽  
Waiting Times ◽  
Healthcare Facility ◽  
Tertiary Hospital ◽  
Radiology Department ◽  
System Efficiency ◽  
Cross Sectional ◽  
Mean Waiting Time ◽  
Significant Difference

Background: Quality of service, as perceived by patients in any healthcare facility is to a great extent, dependent on the waiting time. Reducing patients' waiting time increases patients' satisfaction and improves system efficiency. Purpose: To measure and analyze the waiting time of patients at the service points in the ultrasound unit of a Nigerian tertiary hospital and to determine the mean examination time for the different ultrasound investigations carried out. Methods: This prospective cross-sectional study was carried out in the ultrasound unit of the Radiology department at the University of Nigeria Teaching Hospital (UNTH) Ituku/Ozalla, Enugu. The waiting and examination times of patients were measured directly through observation of system operations. The waiting time at the various service points identified as costing, update, payment and examination were recorded. Mean, range and standard deviation of waiting and service times formed the descriptive statistics for the. For inferential statistics, ANOVA test was carried out to test for significance in the different service point waiting times, and the different examination times for the different investigations. Results: Mean waiting time was 3 hours 31 seconds and average exam time was 26 minutes 31 seconds. Analysis of variance on the service point where patients wait the most showed that the point after making the payment was the most significant. There was no significant difference found in the amount of time spent on different examinations (P < 0.05). Conclusion: Timely delivery of services is of optimum importance, considering the need for patient-centred service. With the information provided on the waiting time at the different service points in a typical teaching hospital ultrasound unit, departmental managers will be guided in the planning of the departmental operations, to enhance patient satisfaction and system efficiency.

scholarly journals Does the Canadian Emergency Department Triage and Acuity Scale identify non-urgent patients who can be triaged away from the emergency department?

CJEM ◽  
2004 ◽  
Vol 6 (05) ◽  
pp. 337-342 ◽  
Author(s):  
Les Vertesi
Keyword(s):  
Emergency Department ◽  
Waiting Times ◽  
Significant Proportion ◽  
Hospital Treatment ◽  
Primary Care Settings ◽  
Urgent Patient ◽  
Emergency Department Triage ◽  
Ed Visits ◽  
Potential Impact ◽  
Retrospective Database

ABSTRACTIntroduction:Non-urgent visits comprise a significant proportion of visits to most emergency departments (EDs). Given the severe overcrowding issues faced by many EDs, the use of theCanadian Emergency Department Triage and Acuity Scale(CTAS) to identify patients who could be managed elsewhere seems to be an obvious way to reduce the pressure on the ED and “solve” the overcrowding problem.Objective:To quantify the resource implications, in terms of stretcher use and waiting times, related to non-urgent patient visits and to estimate the potential impact on ED flow of redirecting these patients to alternate primary care settings.Methods:Retrospective database audit in an urban referral hospital ED. For this study, patients triaged as either CTAS Levels IV or V were considered “non-urgent.”Results:Non-urgent patients comprised 30% of ED visits, but less than 5% of all those needing stretchers, along with their associated nursing resources. The longer waits consisted almost entirely of waits for available stretchers and would therefore have remained essentially unaffected. In spite of being labelled “non-urgent” by CTAS criteria, 7.3% of all patients requiring admission came from this group.Conclusions:Non-urgent patients consume a small fraction of the ED stretchers and acute-care resources; therefore, strategies aimed at diverting non-urgent patients are unlikely to improve access for more urgent patients. Using the CTAS to identify patients for diversion away from the ED is measurably unsafe and will lead to inappropriate refusal of care for many patients requiring hospital treatment.

Exploring the Predictors of Emergency Department Triage Acuity Assignment in Patients With Sepsis

2018 ◽  
Vol 50 (2) ◽  
pp. 81-88
Author(s):  
Leon Petruniak ◽  
Maher El-Masri ◽  
Susan Fox-Wasylyshyn
Keyword(s):  
Emergency Department ◽  
Confidence Interval ◽  
Odds Ratio ◽  
Medical Attention ◽  
Emergency Rooms ◽  
Related Factors ◽  
Delayed Treatment ◽  
Emergency Department Triage ◽  
Triage Classification

Background and purpose Evidence suggests that septic patients, who require prompt medical attention, may be undertriaged, resulting in delayed treatment. The purpose of this study was to examine patient and contextual variables that contribute to high- versus low-acuity triage classification of patients with sepsis. Methods Data were abstracted from the medical records of 154 adult patients with sepsis admitted to hospital through a Canadian Emergency Department. Logistic regression was used to explore the predictors of triage classification. Results Language barriers or chronic cognitive impairment (odds ratio 5.7; 95% confidence interval 2.15, 15.01), acute confusion (odds ratio 3.4; confidence interval 1.3, 8.2), unwell appearance (odds ratio 3.4; 95% confidence interval 1.7, 7.0), and hypotension (odds ratio 0.98; confidence interval 0.96, 1.0) were predictive of higher acuity classification. Temperature, heart rate, respiratory rate, and contextual factors were not related to triage classification. Conclusions Several patient-related factors were related to triage classification. However, the finding that temperature and heart and respiratory rates were not related to triage classification was troubling. Our findings point to a need for enhanced education for triage nurses regarding the physiological indices of sepsis. The sensitivity of the Canadian Triage Assessment Scale, used in Canadian Emergency Rooms, also needs to be examined.

scholarly journals The Effect of Patient Arrival Time on Overall Wait Time and Utilization of Physician and Examination Room Resources in the Outpatient Urology Clinic

2008 ◽  
Vol 2008 ◽  
pp. 1-3 ◽  
Author(s):  
Onisuru T. Okotie ◽  
Neel Patel ◽  
Chris M. Gonzalez
Keyword(s):  
Waiting Times ◽  
Wait Time ◽  
Process Improvements ◽  
Clinic Efficiency ◽  
Exam Room ◽  
Physician Utilization ◽  
Patient Arrival ◽  
Improve Patient ◽  
Examination Room ◽  
Urology Clinic

Introduction and objective. We examined patient waiting times, physician utilization, and exam room utilization in order to identify process improvements that may improve patient satisfaction.Methods. Time patient arrived to clinic, time patient was placed in the exam room, time the physician arrived in the exam room, and time physician discharged the patient from the exam room were prospectively recorded for 226 outpatient visits.Results. Overall, 63.2% of patients were on time for their scheduled appointment with 14.8% patient “no-shows.” On-time patients were found to have a longer wait time once in the exam room for the physician than those that were late ( minutes versus minutes, ); however, those patients spent a significantly longer time with the physician ( minutes versus minutes, ). Exam room utilization was lower for late patients (28.9% versus 44.7%, ) with physician utilization lower in clinics with 3 or more late patients when compared to clinics with 2 or fewer (59.7% versus 68.7%, ).Conclusions. Late patients had significantly less time with the physician than on-time patients. Late patients also decreased the overall efficiency of the clinic; therefore, measures to reduce late patients are vital to improve clinic efficiency.

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