scholarly journals Assessing the usefulness of instant feedback and the Hawthorne effect: an audit of time indexes of EMS missions in Tehran

2021 ◽  
Vol 18 ◽  
Author(s):  
Peyman Saberian ◽  
Negin Mousaeinezhad ◽  
Parisa Hasani-Sharamin ◽  
Hasan Mohammadi ◽  
Mahnaz Jamshididana ◽  
...  
Keyword(s):  
Response Time ◽  
Delay Time ◽  
Time Response ◽  
Hawthorne Effect ◽  
Transfer Time ◽  
Activation Time ◽  
Intervention Phase ◽  
The Mean ◽  
Monitoring Phase ◽  
Feedback Phase

Introduction It has been well established that if a person is aware that they are being monitored their commitment and effort will be maximised (the Hawthorne effect), which then leads to efficiency increase and optimal workflow. Objective Our aim was to evaluate the efficacy of instant feedback and the Hawthorne effect of this intervention on pre-hospital time indexes during emergency medical service (EMS) missions. Methods This is a cross-sectional auditing study on the missions of the Tehran EMS Center (performed over a 12-month period) in three phases: pre-intervention, instant feedback, and monitoring without feedback. The measured time indexes were the different parts of mission times. To collect data, a pre-prepared checklist was set up. For the first phase, data were extracted from the database of the Tehran EMS Center. In the second and third phases, the data were entered into the relevant forms for each mission by the researcher and executive colleagues. Results The data of 229,847 missions were analysed. In the instant feedback phase, compared to the pre-intervention phase, the mean activation time, response time, scene time, transfer time and hospital delay time were decreased. When we compared the mean time indexes in the monitoring phase compared to the instant feedback phase, we saw that the average activation time, response time and transfer time were increased but they were still less than that in the pre-intervention phase. However, the scene time and hospital delay time were not changed compared to the instant feedback phase but were lower than that in the pre-intervention phase. Conclusion Auditing was effective in reducing the total time of missions and this effect was largely maintained in the monitoring phase under the Hawthorne effect.

scholarly journals Development of Perceptual Inhibition in Adolescents—a Critical Period?

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 457
Author(s):  
Isabel María Introzzi ◽  
María Marta Richard’s ◽  
Yesica Aydmune ◽  
Eliana Vanesa Zamora ◽  
Florencia Stelzer ◽  
...  
Keyword(s):  
Response Time ◽  
Executive Functions ◽  
Critical Period ◽  
Search Task ◽  
Probability Distributions ◽  
Linear Trajectory ◽  
Gaussian Functions ◽  
Mean Response Time ◽  
The Mean ◽  
One Year

Recent studies suggest that the developmental curves in adolescence, related to the development of executive functions, could be fitted to a non-linear trajectory of development with progressions and retrogressions. Therefore, the present study proposes to analyze the pattern of development in Perceptual Inhibition (PI), considering all stages of adolescence (early, middle, and late) in intervals of one year. To this aim, we worked with a sample of 275 participants between 10 and 25 years, who performed a joint visual and search task (to measure PI). We have fitted ex-Gaussian functions to the probability distributions of the mean response time across the sample and performed a covariance analysis (ANCOVA). The results showed that the 10- to 13-year-old groups performed similarly in the task and differ from the 14- to 19-year-old participants. We found significant differences between the older group and all the rest of the groups. We discuss the important changes that can be observed in relation to the nonlinear trajectory of development that would show the PI during adolescence.

scholarly journals P300 in Behcet's Patients without Neurological Manifestations

2001 ◽  
Vol 28 (1) ◽  
pp. 66-69 ◽  
Author(s):  
Hulusi Kececi ◽  
Melih Akyol
Keyword(s):  
Response Time ◽  
Behçet’S Disease ◽  
Motor Response ◽  
Behcet’S Disease ◽  
Behçet's Disease ◽  
P300 Latency ◽  
Behcet's Disease ◽  
Neurologic Involvement ◽  
The Mean ◽  
Normal Controls

ABSTRACT:Objective:Behcet's disease is the association of recurrent aphthous stomatitis with genital ulceration and eye disease. Neurologic involvement patterns include meningomyelitis, a brain stem syndrome, pyramidal and extrapyramidal abnormality and stroke. In the present study, subclinical involvement was investigated by using P300 in Behcet's patients without neurological manifestation.Methods:Fifteen patients and 15 healthy volunteers were accepted for the study. P300 from vertex (Cz) electrode sites of the 10-20 system using electrodes and motor response time were recorded.Results:Patients had significantly prolonged latencies of P300 as compared to normal controls (p=0.013) but no significant differences in amplitude (p=1.000). Patients showed a significantly delayed motor response time than controls (p=0.006). Nine patients (60 %) had P300 latency and eight patients (53.3 %) had motor response time values exceeding the mean of controls by two standard deviations.Conclusion:The findings suggest that the P300 measures and motor response time may reflect subclinical neurologic involvement in Behcet's disease.

scholarly journals SIMULASI WAKTU TUNGGU MAHASISWA DAN DOSEN DI LAYANAN AKADEMIK UNIVERSITAS BUNDA MULIA

2017 ◽  
Vol 10 (1) ◽  
Author(s):  
Rudy Santosa Sudirga
Keyword(s):  
Response Time ◽  
Waiting Time ◽  
Operations Management ◽  
Heavy Traffic ◽  
Simulation Models ◽  
Operation Performance ◽  
Service Operation ◽  
Mean And Variance ◽  
The Mean ◽  
Time In Service

<p>The Management of Academic Service continues to be a major challenge for many college, high school and college organizations in providing better services with fewer resources. The allocation of service staffs and response-time in service involve many challenging issues, because the mean and variance of the response-time in service can be increased dramatically with the intensity of heavy traffic. This study discusses how to use simulation models to improve response time in service operation. Performance at the Academic Service as a whole can be considered very good and is still idle due to utilization of Academic Service, which is still equal to an average of 17%, or it can be said that the workload is not too excessive and deemed to be able to serve the students and lecturers. The performance of Academic Sevice University Bunda Mulia can be considered excellent in terms of operations management, as indicated by the average waiting time, which is very short at only 9.10 seconds.<br />Keywords: Queueing System, Waiting Time, and Simulation</p>

Composite Graft Replacement of Digital Tips

1997 ◽  
Vol 22 (3) ◽  
pp. 346-352 ◽  
Author(s):  
N. S. MOIEMEN ◽  
D. ELLIOT
Keyword(s):  
Delay Time ◽  
Composite Graft ◽  
Graft Replacement ◽  
Mean Delay ◽  
Successful Group ◽  
The Mean

This study investigated the outcome of composite graft replacement of 50 amputated digital tips in 50 children over a period of 3 years and 6 months. Eleven of 18 tips (61%) which were replaced within 5 hours survived completely while none of 32 digital tips replaced after 5 hours survived completely. This difference was highly significant. The mean delay time between amputation and replacement in the successful group was 3.9 hours and in the others was 7.2 hours. This difference was also statistically significant. The implications of the findings of this series to the use of this treatment are discussed.

Cerebral Chronological Corollary Perusal for Blitzing Fire Paroxysm and Pipeline Attrition in Nigeria

2021 ◽  
Author(s):  
Daniel Ikechukwu Egu ◽  
Anthony John Ilozobhie
Keyword(s):  
Response Time ◽  
Data Gathering ◽  
Petroleum Products ◽  
Time Response ◽  
Response Model ◽  
Microsoft Excel ◽  
Cumulative Response ◽  
All Solutions ◽  
Industrial Disaster ◽  
Spread Sheet

Abstract Attrition and paroxysm of highly inflammable petroleum products in storage tanks, pipelines and/or haulage trucks is increasingly becoming a scourging socio-environmental quandary with a detrimental effect on the Nigerian economy. Non availability of a holistic response time analytic master plan is a major enigma while industrial disaster managers perhaps are the major culprits since they are mostly not time cognizant for spry and pragmatic delivery of service. The aim of this exposition is to ruminatively carry out cerebral chronological corollary perusal for blitzing fire paroxysms and pipeline attrition in Nigeria on Microsoft excel spread sheet. Comprehensive data validation was done for all models by substituting all solutions of matrix into the predicted time response model. Results of predicted time response model in minutes for case A gave; 101x1 + 79x2 + 59x3 + 45x4 + 24x5 = 358. The predicted time response model for case B gave 78x1 + 56x2 + 43x3 + 30x4 + 13x5 = 260. The predicted time response model for case C gave; 74x1 + 56x2 + 42x3 + 29x4 + 10x5 = 252. Results of these models shows that the average cumulative response time dropped from 3.58 minutes to 2.52 minutes from case A to case C while the coefficients all reduced in their values from model A to C. Improving the source of data gathering and computational processes is recommended for enhancement of this study.

Abstract P188: Transfer Time From Spoke ER Arrival to CSC Arrival in a Hub-Spoke Transfer Model of Thrombolysis for Acute Ischemic Stroke

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Vivien H Lee ◽  
Paul A Segerstrom ◽  
Ciarán J Powers ◽  
Sharon Heaton ◽  
Shahid M Nimjee ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Univariate Analysis ◽  
Transfer Model ◽  
Transfer Time ◽  
Intravenous Tissue Plasminogen Activator ◽  
The Mean ◽  
Comprehensive Stroke Center ◽  
Stroke Center ◽  
Er Status

Introduction: Acute ischemic stroke (AIS) patients who present to a spoke Emergency Room (ER) and require transfer to a comprehensive stroke center (CSC) hub face potential delays Methods: We performed a retrospective review of 269 suspected AIS patients who received intravenous tissue plasminogen activator (tPA) from July 2016 to October 2017 in our academic telestroke network. During this period, nearly all tPA patients were transferred to the CSC hub. Data was collected on patient demographics, National Institutes of Health Stroke Scale (NIHSS), door to needle time (DTN), and distance to CSC. ER-to-CSC was defined as the time from patient arrival at Spoke ER to arrival at CSC. Top volume ER status was assigned to the 4 Spoke ERs with the highest volume of tPA. Results: Among 269 AIS patients who received tPA at spoke ERs, the mean age was 65.4 years (range, 21 to 95), 49% were female, and 91.8% were white. The initial median NIHSS was 6 (range, 0 to 30) and the mean DTN was 73.1 minutes (range, 14 to 234). The mean distance from Spoke ER to CSC was 55.2 miles (range 5.8 to 125) and the mean ER-to-CSC was 2.6 hours (range 0.62 to 6.3) (Figure 1). In univariate analysis, the following factors were significantly associated with ER-to-CSC: distance (p < 0.0001), DTN (p < 0.0001), NIHSS (p 0.0007), and top volume ER status (p 0.0034). Patient sex, age, race, SBP, weight, initial NIHSS, daytime shift, and weekend status were not significantly associated with ER-to-CSC. Significant variables from the univariate analysis were included in multivariate linear regression model in which DTN (P < 0.0001), distance (P < 0.0001), and NIHSS (P 0.024) association with ER-to-CSC remained significant. Conclusions: In our series of AIS tPA patients transferred to CSC, the mean time from spoke ER arrival to CSC arrival was 2.6 hours. Factors associated with CSC arrival time include markers of ER performance (DTN), severity (NIHSS), and distance. Further study is warranted to improve transfer time in AIS.

Abstract 257: Cutting Down the Lag- an Assessment of the Delay in the House Staff’s Evaluation of an Admission

2020 ◽  
Vol 13 (Suppl_1) ◽  
Author(s):  
Jason G Kaplan ◽  
Arjun Kanwal ◽  
John Berquist ◽  
Samuel Eis ◽  
Rabia Zahid ◽  
...  
Keyword(s):  
Emergency Department ◽  
Response Time ◽  
Current System ◽  
Lag Time ◽  
P Value ◽  
Post Intervention ◽  
Emergency Department Admission ◽  
Admission Time ◽  
Evaluation Time ◽  
The Mean

Background: At this institution, a delay occurs between the time the emergency department admits a patient and the admitting service’s evaluation of the patient. Since the emergency department is run on paper charting, the current system, at night, involves the emergency department writing a name and a diagnosis in the emergency department’s admission book. The night residents’ job is to admit teaching patients to the teaching service. The current system requires the night resident to physically go to the emergency department and look in the admissions book to find out about a new admission. This lack of communication can cause a great delay in evaluation of a new admission, which can be problematic. The catalyst for this study was an adverse event where a stroke was missed in the emergency department and the patient was not evaluated by the admitting service for 15 hours falling well outside the tPA window. Decreasing the delay in thorough evaluation is crucial in proper treatment of many cardiovascular conditions, which are time sensitive and can potentially prevent a catastrophic outcome. Intervention: Residents on the admitting service will be first asked to document their evaluation time without intervention, which will be documented with the emergency department admission time to establish a baseline. In addition to the current system of manually checking the admissions book in the emergency department, the ward clerk will page the night staff when new admissions are written in the book. Residents on the admitting service will then document their evaluation time with this new intervention, along with the emergency department admission time. The goal of this new system is to decrease the time the patient is waiting to be evaluated by the admitting service. Results: The mean lag time pre-intervention (N=20) was 73 minutes with a range of 0-279 minutes. Post-intervention (N=25) the mean lag time was 82 minutes with a range of 5- 337 minutes. The P-value of this study was 0.707. Residents on the admitting service were very compliant with documenting their evaluation times. Admitting residents did note the pages were inconsistent and were often missed. The rate of pages successfully sent out was not documented. Conclusion: The lag time before and after intervention was not found to be statistically significant. Pages were inconsistently sent out but did not impact the internal validity of the study. Since the study tested if paging the on-call residents improved the delay in evaluation, the ability to reliably send the page is as important as the response time. The paging system in this study was used as an augmentation to the current system out of some trepidation that pages could be missed and thus negatively impacting the response time. Due to the statistically insignificant data, it can be concluded that the paging system made no impact on the response time patients were seen by the admitting residents.

Study of Industrial Model for Five-Input, Five-Stage Queueing Network

2016 ◽  
pp. 300-339
Author(s):  
Jitendra Kumar ◽  
Vikas Shinde
Keyword(s):  
Response Time ◽  
Textile Industry ◽  
Optimal Path ◽  
Queueing Network ◽  
Numerical Illustration ◽  
Mean Response Time ◽  
Final Destination ◽  
Optimal Capacity ◽  
Mean Waiting Time ◽  
The Mean

In this paper, we have developed an industrial model for textile industry with five-input, five-stage queueing network, wherein system receives orders from clients that are waiting to be served. The aim of this paper is to compute the optimal path that will provide the least response time for delivery of items to the final destination, through the five stages under queueing network. The mean number of items that can be delivered is minimum response time constitute the optimal capacity of the network. The last node in each stage of the network can be executed in the least possible response time. Various performance indices were carried out such as mean number of item in the system, mean number of item in queue, mean response time, mean waiting time. We have established the equivalent queueing network to analyze the various performance measures with numerical illustration and graph.

Response time of cardiac mitochondrial oxygen consumption to heart rate steps

1991 ◽  
Vol 260 (2) ◽  
pp. H613-H625 ◽  
Author(s):  
J. H. Van Beek ◽  
N. Westerhof
Keyword(s):  
Heart Rate ◽  
Response Time ◽  
Time Course ◽  
Mean Transit Time ◽  
Impulse Response Function ◽  
Heart Tissue ◽  
Experimental Information ◽  
O2 Consumption ◽  
Mean Response Time ◽  
The Mean

We investigated the time course of cardiac mitochondrial O2 consumption following steps in heart rate in 16 isolated rabbit hearts perfused with Tyrode solution. The time course was characterized by the mean response time, i.e., the first statistical moment (mean time) of the impulse response function. Like the mean transit time for an indicator, it provides an important characteristic of the response time course. The venous O2 content transients during steps in heart rate were measured and corrected for O2 diffusion and vascular transport using a mathematical model with experimental information derived from O2 washout following steps in arterial O2 concentration or perfusion flow. We deduce from these washout experiments that the effective O2 solubility in heart tissue is 86 +/- 13% (mean +/- SE) of solubility in water. The measured venous mean response time following a step in heart rate at 37 degrees C was 17.6 +/- 1.1 s. The mean response time of cardiac mitochondrial O2 consumption to changes in heart rate after correction for O2 transport was 7.7 +/- 0.7 s.

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