scholarly journals RADIOGRAPHIC IMPLICATIONS OF THE SURGICAL WAITING LIST FOR THE TREATMENT OF SPINAL DEFORMITY

2018 ◽  
Vol 17 (1) ◽  
pp. 19-22
Author(s):  
LEONARDO YUKIO JORGE ASANO ◽  
MARINA ROSA FILÉZIO ◽  
MATEUS PIPPA DEFINO ◽  
VINÍCIUS ALVES DE ANDRADE ◽  
ANDRÉ EVARISTO MARCONDES CESAR ◽  
...  
Keyword(s):  
Surgical Planning ◽  
Negative Impact ◽  
Waiting Times ◽  
Waiting List ◽  
Surgical Morbidity ◽  
Level Of Evidence ◽  
Mean Waiting Time ◽  
Significant Negative Impact ◽  
Double Approach ◽  
The Mean

ABSTRACT Objective: The aim of this study was to evaluate the implications of long waiting times on surgery lists for the treatment of patients with scoliosis. Methods: Radiographs of 87 patients with scoliosis who had been on the waiting list for surgery for more than six months were selected. Two surgeons answered questionnaires analyzing the radiographs when entering the waiting list and the current images of each patient. Results: Data from 87 patients were analyzed. The mean waiting time for surgery was 21.7 months (ranging from seven to 32 months). The average progression of the Cobb angle in the curvature was 21.1 degrees. Delayed surgery implied changes in surgical planning, such as greater need of instrumentation, osteotomies, and double approach. Conclusions: Long waiting lists have a significant negative impact on surgical morbidity of patients with scoliosis, since they increase the complexity of the surgery. Level of evidence: IV. Type of study: Descriptive study.

HOW TO REPORT AND MONITOR THE PERFORMANCE OF WAITING LIST MANAGEMENT

2002 ◽  
Vol 18 (3) ◽  
pp. 611-618
Author(s):  
Markus Torkki ◽  
Miika Linna ◽  
Seppo Seitsalo ◽  
Pekka Paavolainen
Keyword(s):  
Hallux Valgus ◽  
Waiting Time ◽  
Varicose Vein ◽  
Elective Surgery ◽  
Waiting Times ◽  
Waiting List ◽  
Mean Waiting Time ◽  
Number Of Patients ◽  
Potential Problems ◽  
Queue Discipline

Objectives: Potential problems concerning waiting list management are often monitored using mean waiting times based on empirical samples. However, the appropriateness of mean waiting time as an indicator of access can be questioned if a waiting list is not managed well, e.g., if the queue discipline is violated. This study was performed to find out about the queue discipline in waiting lists for elective surgery to reveal potential discrepancies in waiting list management. Methods: There were 1,774 waiting list patients for hallux valgus or varicose vein surgery or sterilization. The waiting time distributions of patients receiving surgery and of patients still waiting for an operation are presented in column charts. The charts are compared with two model charts. One model chart presents a high queue discipline (first in—first out) and another a poor queue discipline (random) queue. Results: There were significant differences in waiting list management across hospitals and patient categories. Examples of a poor queue discipline were found in queues for hallux valgus and varicose vein operations. Conclusions: A routine waiting list reporting should be used to guarantee the quality of waiting list management and to pinpoint potential problems in access. It is important to monitor not only the number of patients in the waiting list but also the queue discipline and the balance between demand and supply of surgical services. The purpose for this type of reporting is to ensure that the priority setting made at health policy level also works in practise.

Fatigue Assessment of Mooring Chain Considering the Effects Of Mean Load and Corrosion

2021 ◽  
Author(s):  
Erling N. Lone ◽  
Thomas Sauder ◽  
Kjell Larsen ◽  
Bernt J. Leira
Keyword(s):  
Negative Impact ◽  
Fatigue Tests ◽  
Design Practice ◽  
Extended Formulation ◽  
Considerable Influence ◽  
Corrosion Condition ◽  
Capacity Model ◽  
Significant Negative Impact ◽  
The Mean ◽  
Mooring Chain

Abstract Results from full scale fatigue tests of offshore mooring chains performed in recent years have revealed considerable influence of both mean load and corrosion condition on the fatigue capacity. It has been shown that a reduction of the mean load gives an increase in fatigue life, whereas the corrosion experienced by used chains have a significant negative impact. Neither of these effects are properly addressed by current S-N design curves or design practice. This paper suggests an extended S-N curve formulation, that includes the effects of mean load and corrosion condition. The parameters of the extended formulation are estimated empirically from mooring chain test data that includes new and used chains, with various mean loads and with different degrees of corrosion. The fitted capacity model is then used for fatigue calculation for the mooring system of a semi-submersible, showing the importance of using realistic mean loads and mooring chain corrosion in fatigue assessments.

Prioritisation of catheterised patients for elective bladder outflow obstruction surgery in the current coronavirus disease 2019 era to reduce catheter-associated morbidity

2020 ◽  
pp. 205141582096403
Author(s):  
Angela Kit Ying Lam ◽  
Kathie Wong ◽  
Tharani Nitkunan
Keyword(s):  
Median Time ◽  
Waiting Times ◽  
Waiting List ◽  
Transurethral Resection Of Prostate ◽  
Outflow Obstruction ◽  
Level Of Evidence ◽  
Bladder Outflow Obstruction ◽  
Patient Demographics ◽  
Accident And Emergency ◽  
Included Patient

Objectives: This study aimed to audit the waiting times for a transurethral resection of prostate (TURP) at our institution, and to evaluate the extent of catheter-associated morbidity in this population. Methods: This was a retrospective closed-loop audit, with cycle one between 1 January 2018 and 31 December 2018 and cycle two between 1 October 2019 and 29 February 2020. Data collected included patient demographics, catheter status, catheter-associated presentations to accident and emergency (A&E), admissions and waiting times for TURP. The waiting-list form now has a catheter box, and a goal of 30 days from waitlisting to operation was set for those catheterised. Results: In cycle 1, 36% of the 181 patients were catheterised, and waited a median of 119 days (interquartile range (IQR) 59–163 days) for their TURP, while those not catheterised waited a median of 118 days (IQR 57.75–188.25 days). Catheterised patients presented to A&E 93 times, resulting in 13 admissions, compared to two presentations and zero admissions for those not catheterised. The median time from catheter insertion to first A&E attendance was 20 days (IQR 2–101 days). In cycle 2, 33% of the 55 patients were catheterised, with the median waiting-list time falling to 32 days (IQR 22–46 days) in those catheterised and 33 days (IQR 20–49 days) in those not catheterised. All 11 A&E attendances were from catheterised patients, with no admissions. The median time from insertion to first A&E attendance was nine days (IQR 4–40 days). Eighty-eight per cent of the waiting-list forms had appropriately ticked the catheter box. Conclusion: Our study shows that catheterised patients awaiting a TURP are more likely to have complications necessitating A&E attendance. Prioritisation of these patients on the waiting list for bladder outflow obstruction surgery may help to reduce catheter-associated morbidity. Level of evidence: Level 2c.

scholarly journals Some reflections on the Renewal-theory paradox in queueing theory

1998 ◽  
Vol 11 (3) ◽  
pp. 355-368 ◽  
Author(s):  
Robert B. Cooper ◽  
Shun-Chen Niu ◽  
Mandyam M. Srinivasan
Keyword(s):  
Waiting Time ◽  
Queueing Theory ◽  
Waiting Times ◽  
Renewal Theory ◽  
Vacation Models ◽  
Polling Models ◽  
Mean Waiting Time ◽  
The Mean ◽  
Expository Paper ◽  
Set Up

The classical renewal-theory (waiting time, or inspection) paradox states that the length of the renewal interval that covers a randomly-selected time epoch tends to be longer than an ordinary renewal interval. This paradox manifests itself in numerous interesting ways in queueing theory, a prime example being the celebrated Pollaczek-Khintchine formula for the mean waiting time in the M/G/1 queue. In this expository paper, we give intuitive arguments that “explain” why the renewal-theory paradox is ubiquitous in queueing theory, and why it sometimes produces anomalous results. In particular, we use these intuitive arguments to explain decomposition in vacation models, and to derive formulas that describe some recently-discovered counterintuitive results for polling models, such as the reduction of waiting times as a consequence of forcing the server to set up even when no work is waiting.

On the stochastic ordering of waiting times for patterns in sequences of random digits

1984 ◽  
Vol 21 (4) ◽  
pp. 730-737 ◽  
Author(s):  
Gunnar Blom
Keyword(s):  
Waiting Time ◽  
Waiting Times ◽  
Stochastic Ordering ◽  
Mean Waiting Time ◽  
Coin Tossing ◽  
The Mean

Random digits are collected one at a time until a pattern with given digits is obtained. Blom (1982) and others have determined the mean waiting time for such a pattern. It is proved that when a given pattern has larger mean waiting time than another pattern, then the waiting time for the former is stochastically larger than that for the latter. An application is given to a coin-tossing game.

scholarly journals MEASURING ACCESSIBILITY: A BIG DATA PERSPECTIVE ON UBER SERVICE WAITING TIMES

2019 ◽  
Vol 59 (6) ◽  
pp. 402-414 ◽  
Author(s):  
ANDRÉ INSARDI ◽  
RODOLFO OLIVEIRA LORENZO
Keyword(s):  
Waiting Times ◽  
Multiple Linear Regression Model ◽  
Transport Infrastructure ◽  
Specific Reference ◽  
Time Data ◽  
Mean Waiting Time ◽  
Stepwise Method ◽  
Spatial Autoregressive ◽  
The Mean ◽  
Physical Variables

ABSTRACT This study aims to relate information about the waiting times of ride-sourcing services, with specific reference to Uber, using socioeconomic variables from São Paulo, Brazil. The intention is to explore the possibility of using this measure as an accessibility proxy. A database was created with the mean waiting time data per district, which was aggregated to a set of socioeconomic and transport infrastructure variables. From this database, a multiple linear regression model was built. In addition, the stepwise method selected the most significant variables. Moran's I test confirmed the spatial distribution pattern of the measures, motivating the use of a spatial autoregressive model. The results indicate that physical variables, such as area and population density, are important to explain this relation. However, the mileage of district bus lines and the non-white resident rate were also significant. Besides, the spatial component indicates a possible relation to accessibility.

THEORETICAL ANALYSIS OF MEAN WAITING TIME FOR MESSAGE DELIVERY IN LATTICE AD HOC NETWORKS

2010 ◽  
Vol 19 (08) ◽  
pp. 1711-1741
Author(s):  
AKIRA OTSUKA ◽  
KEISUKE NAKANO ◽  
KAZUYUKI MIYAKITA
Keyword(s):  
Ad Hoc Networks ◽  
Waiting Time ◽  
Ad Hoc ◽  
Waiting Times ◽  
Traffic Patterns ◽  
Mobile Nodes ◽  
Approximate Methods ◽  
Mean Waiting Time ◽  
The Mean ◽  
Hoc Networks

In ad hoc networks, the analysis of connectivity performance is crucial. The waiting time to deliver message M from source S to destination D is a measure of connectivity that reflects the effects of mobility, and some approximate methods have been proposed to theoretically analyze the mean waiting time in one-dimensional ad hoc networks that consist of mobile nodes moving along a street. In this paper, we extend these approximate methods to analyze the mean waiting time in two-dimensional networks with a lattice structure with various flows of mobile nodes. We discuss how the mean waiting times behave in such complicated street networks and how to approximate two kinds of mean waiting times. We show that our approximate methods can successfully compute the mean waiting times for even traffic patterns and roughly estimate them for uneven traffic patterns in two-dimensional lattice networks. In these analyses, we consider two shadowing models to investigate how shadowing affects the waiting time. We also discuss the effect of different positions of S on the mean waiting time.

Tackling a long waiting list in a child and adolescent mental health service

2006 ◽  
Vol 23 (3) ◽  
pp. 103-106 ◽  
Author(s):  
Gordon Lynch ◽  
Elma Hedderman
Keyword(s):  
Waiting Time ◽  
Creative Thinking ◽  
Negative Impact ◽  
Waiting List ◽  
Time Range ◽  
Triage System ◽  
Team Members ◽  
Mean Waiting Time ◽  
Adolescent Mental Health Service ◽  
One Year

AbstractObjective: Long waiting lists have a negative impact on client satisfaction, staff moral and referrer's opinion of the service. The aim of this project was to decrease a waiting list from a maximum wait of more than one year to a wait of no more than six weeks.Method: We introduced three simultaneous initiatives to decrease a long waiting list; (i) an individually led triage system (ii) setting-up an attention deficit hyperactivity disorder (ADHD) specialist team and (iii) division of the residual waiting list between team members. These initiatives were introduced and analysed over a ten month period. The study period ran from 1/3/2004 to 31/12/2004.Results: The waiting time to first appointment was significantly reduced. At the beginning of the study there were 62 people waiting to be seen and each had waited an average of 122 days with a waiting time range of 0-449 days. At the end of the study, there were 19 people waiting with a mean waiting time of 19 days and a range of 0-168 days.Conclusions: The single most powerful intervention was the triage system. The ADHD clinic allowed referrals to be streamlined in a very structured and efficient way. The division of the residual waiting list was not as onerous as it first appeared. The service saw more referrals then ever during the study period. Referrers and families appreciated being seen more quickly. By removing the burden of the waiting list from staff the potential for creative thinking around further development of the service increased.

scholarly journals Managing Queues with Heterogeneous Servers

2011 ◽  
Vol 48 (2) ◽  
pp. 435-452 ◽  
Author(s):  
Jung Hyun Kim ◽  
Hyun-Soo Ahn ◽  
Rhonda Righter
Keyword(s):  
Waiting Time ◽  
Waiting Times ◽  
Structural Result ◽  
Batch Arrivals ◽  
Optimal Thresholds ◽  
Mean Waiting Time ◽  
Server Problem ◽  
The Mean ◽  
The Impact ◽  
Intuitive Proof

We consider several versions of the job assignment problem for an M/M/m queue with servers of different speeds. When there are two classes of customers, primary and secondary, the number of secondary customers is infinite, and idling is not permitted, we develop an intuitive proof that the optimal policy that minimizes the mean waiting time has a threshold structure. That is, for each server, there is a server-dependent threshold such that a primary customer will be assigned to that server if and only if the queue length of primary customers meets or exceeds the threshold. Our key argument can be generalized to extend the structural result to models with impatient customers, discounted waiting time, batch arrivals and services, geometrically distributed service times, and a random environment. We show how to compute the optimal thresholds, and study the impact of heterogeneity in server speeds on mean waiting times. We also apply the same machinery to the classical slow-server problem without secondary customers, and obtain more general results for the two-server case and strengthen existing results for more than two servers.

Abstract WP431: Comparing EMS and Emergency Department Last Known Well Times in Ohio

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Mussa Zatreh ◽  
Melissa Richardson
Keyword(s):  
Emergency Department ◽  
Negative Impact ◽  
Improve Patient Care ◽  
Accurate Information ◽  
Hospital Size ◽  
Patient Demographics ◽  
Significant Negative Impact ◽  
The Mean ◽  
The Difference ◽  
Revascularization Therapy

Introduction: During the hyperacute phase of acute stroke management, time the patient was last known well (LKW) is a critical data element. Hospital Emergency Department (ED) personnel rely on accurate information reported by Emergency Medical Services (EMS) prior to arrival, which triggers the intensity of resources organized to determine patient eligibility for revascularization therapy. Over-triage can cause “alarm fatigue”, provider burnout, and/or overutilization of valuable resources. Conversely, under triage may cause a delay in, or lack of, revascularization therapy, which can have significant negative impact on the patient’s outcome. A review of the literature revealed contradictory data about the accuracy of LKW as reported by EMS. Purpose: The purpose of this project is to determine frequency and magnitude of discrepancies between LKW as reported by EMS and ED. The data was analyzed for trends that may influence discrepancies, such as hospital size, location, and patient demographics. Methods: Data on 2,092 patients from 49 hospitals was analyzed from Get With The Guidelines®-Stroke. The difference in the LKW (ΔLKW) was calculated based on source of documentation from EMS or ED. Three datasets were created based on the magnitude of the ΔLKW. For each dataset, the mean, median and patient demographics such as mean age, race, and stroke type were calculated. Results: Of 2,092 patients, 951 (45%) showed an exact match between LKW as reported by EMS and ED (ΔLKW=0), whereas 1,141 patients (55%) showed a discrepancy in the LKW (ΔLKW>0). Discrepancies were not influenced by hospital location or size. Of the overall population, 54% were male, 18% were black, and 73% were diagnosed with an ischemic stroke. The mean age was 72 years. Further collaboration is needed between EMS and ED personnel to improve the accuracy of LKW, and thereby improve patient care and provider efficiency.

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