Emergency Department Waiting Times and Determinants of Prolonged Length of Stay in a Botswana Referral Hospital

Introduction: Emergency medicine is a critical component of quality public health service. In fact length of stay and waiting times in the Emergency department are key indicators of quality. The aim of this study was to determine waiting times and determinants of prolonged length of stay (LOS) in the Princess Marina Hospital Emergency Department. Methods: This was a retrospective observational study. It was done at Princess Marina, a referral hospital in Gaborone, Botswana. Triage forms of patients who presented between 19/11/ 2018 and 18/12/2018 were reviewed. Data from patient files was used to determine time duration from triage to being reviewed by a doctor, time duration from review by emergency doctor to patients’ disposition and the time duration from patient’s triage to disposition (length of stay). Prolonged length of stay was defined as duration > 6 hours. Results: A total of 1052 files repre- senting patients seen over a 1-month period were reviewed. 72.5% of the patients had a prolonged length of stay. The median emergency doctor waiting time was 4.5 hours (IQR 1.6 - 8.3 hours) and the maximum was 27.1 hours. The median length of stay in the emergency department was 9.6 hours (IQR 5.8 - 14.6 hours) and the maximum was 45.9 hours. Patient’s age (AOR 1.01), mental status (AOR 0.61), admission to internal medicine service (AOR 5.12) and pediatrics admissions (AOR 0.11) were significant predictors of prolonged length of stay in the emergency department. Conclusion: Princess Marina Hospital emergency department waiting times and length of stay are long. Age, normal mental status and internal medicine admission were independent predictors of prolonged stay (>6 hours). Admission to the pediatrics service was associated with shorter length of stay. There is a need for interventions to address the long waiting times and length of stay. Interventions should particularly focus on the identified predictors.

Waiting Times and Length of Stay of Trauma Patients in a Botswana Referral Hospital Emergency Department

Background: Mortality and morbidity due to trauma are a significant public health challenge. There is paucity of data on the waiting times and length of stay (LOS) of trauma patients in emergency departments in Botswana. The aim of this study was to determine the Emergency Department (ED) waiting times and LOS of trauma patients at Princess Marina Hospital in Gaborone, Botswana. Methods: This was a retrospective medical records review of waiting times (time from triage to review by ED medical officer) and LOS (time from triage to disposition from the emergency department). The waiting times for the different assigned acuities were assessed against the South African Triage System (SATS) standards. All trauma patients seen from 19/11/2018 to 18/12/2018 were included in the study. Prolonged length of stay was defined as duration > 6 hours. Categorical data was summarized with frequencies while numeric data was summarized with medians and interquartile ranges. Results: A total of 187 trauma patients’ files were analyzed. Of these, 72 (38.5%) were females. The median waiting time was 3.8 hours and the maximum was 19.2 hours. The median length of stay (LOS) was 8.8 hours with a maximum of 37.2 hours. Only 53 (28.3%) of the participants had a LOS of less than 6 hours. None of the emergent patients were seen immediately. Only 5 (4.0%) of the very urgent patients were seen within the target of 10 minutes. Finally, only 10 (20.4%) of urgent patients were seen within the target time of 1 hour. Conclusion: The waiting times and length of stay in Princess Marina Hospital were mostly above the recommended standards. Urgent interventions are needed to reduce waiting times and length of stay for trauma patients. More studies are needed to explore the sources of delay and investigate possible solutions to this public health challenge.

VIRTUAL WAITING TIMES IN PRIORITY-M/G/1 QUEUES WITH VACARIONS

In this paper exhaustive-service priority-M/G/1 queueing systems with multiple vacations, single vacation and setup times are studied under the nonpreemptive and preemptive resume priority disciplines. For each of the six models analysed, the Laplace-Stieltjes transform of the virtual waiting time Wk(t) at time t of class k is derived by the method of collective marks. A sufficient condition for , where U has the standard normal distribution, is also given.

Waiting times and stopping probabilities for patterns in Markov chains

Suppose that C is a finite collection of patterns. Observe a Markov chain until one of the patterns in C occurs as a run. This time is denoted by τ. In this paper, we aim to give an easy way to calculate the mean waiting time E(τ) and the stopping probabilities P(τ = τA)with A ∈ C, where τA is the waiting time until the pattern A appears as a run.

Predictive-reactive Strategy for Flowshop Rescheduling Problem:Minimizing the Total Weighted Waiting Times and Instability

Due to the fourth revolution experiencing,referred to as Industry 4.0,many production firms are devoted to integrating new technological tools to their manufacturing process.One of them,is rescheduling the tasks on the machines responding to disruptions.While,for static scheduling,the efficiency criteria measure the performance of scheduling systems,in dynamic environments,the stability criteria are also used to assess the impact of jobs deviation.In this paper,a new performance measure is investigated for a flowshop rescheduling problem.This one considers simultaneously the total weighted waiting time as the efficiency criterion,and the total weighted completion time deviation as the stability criterion.This fusion could be a very helpful and significant measure for real life industrial systems.Two disruption types are considered:jobs arrival and jobs cancellation.Thus,a Mixed Integer Linear Programming(MILP)model is developed,as well as an iterative predictive-reactive strategy for dealing with the online part.At last,two heuristic methods are proposed and discussed,in terms of solution quality and computing time.

Mean waiting time approximation for a real time polling system

This paper considers a novel polling system with two classes of message which can experience an up-per bounded time before being served. The station serves these two classes with mixed service discipline, one class with exhaustive service discipline, and the other with gated service discipline. Using iterative method, we have developed an approximation method to obtain the mean waiting time for each message class. The performance of approximation has been compared with the simulation results. The expression for the upper bound of waiting time is given too.

SOME NEW RESULTS ON WAITING TIME AND BUSY TIME IN M/G/1 QUEUE

This paper considers an M/G/1 queue with Poisson rate lambda > 0 and service time distribution G(t) which is supposed to have finite mean 1/mu. The following questions are first studied: (a) The closed bounds of the probability that waiting time is more than a fixed value; (b)The total busy time of the server, which including the distribution, probability that are more than a fixed value during a given time interval (0, t], and the expected value. Some new and important results are obtained by theories of the classes of life distributions and renewal process.

Reaction Subdiffusion with Random Waiting Time Depending on the Preceding Jump Length

To describe the energy-dependent characteristics of the reaction-subdiffusion process, we analyze the simple reaction A--→B under subdiffsion with waiting time depending on the preceding jump length, and derive the corresponding master equations in the Fourier Laplace space for the distribution of A and B particles in a continuous time random walk scheme. Moreover, the generalizations of the reaction-diffusion equation for the Gaussian jump length with the probability density function of waiting time being quadratically dependent on the preceding jump length are obtained by applying the derived master equations.

Risk Factors for Mortality of Patients Waiting for Elective Coronary Artery Bypass Graft Surgery

Background: Insufficient capacity for cardiac surgery results in extensive waiting time for patients requiring coronary artery bypass grafting (CABG). Previous studies have reported a consequence of an increased risk of mortality while waiting for CABG. Identification of risk factors for mortality is important in patients waiting for CABG. Objectives: To assess mortality rates and identify risk factors for mortality of patients waiting for CABG. Methods: This retrospective cohort study was done on patients waiting for elective CABG in dr. Kariadi General Hospital from January 2018 to December 2020. Identification of risk factors associated with mortality was done on patients who were waiting for CABG using logistic regression methods. Results: There were 162 patients fulfilling the criteria, with a mean waiting time for surgery of 9.8 months. While waiting for CABG surgery, 32 (19.7%) patients died of any cause. Independent risk factors for death while waiting for CABG included left ventricular ejection fraction ≤ 45% (OR 4.75;95% CI 1.76 - 12.78;p = 0.002), left main disease (OR 4.12;95% CI 1.50 - 11.27;p = 0.006), serum creatinine ≥ 1.5 mg/dl (OR 3.71;95% CI 1.41 - 9.74;p = 0.008), and a number of coronary artery disease risk factors ≥ 3 (OR 3.34;95% CI 1.24 - 8.99;p = 0.017). Conclusions: Long waiting time for CABG is associated with a high mortality rate which is influenced by left ventricular ejection fraction ≤ 45%, left main disease, serum creatinine ≥ 1.5 mg/dl, and a number of coronary arteries disease risk factors ≥ 3.

Stochastic Model of Waiting Time: A Case of Two Selected Banks in the Sekondi-Takoradi Metropolis

Queue is an act of joining a line to be served and it is part of our everyday human involvement. The objectives of the study focused on using a mathematical model to determine the waiting time of two selected banks as well as compare the average waiting time between the banks. The study uncovered the extent of usage of queuing models in achieving customer satisfaction as well as permitting to make better decisions relating to potential waiting times for customers. The study adopted a case study and observational research with the source of data being primary. Purposive sampling technique was used to select the two banks under study with the target population comprising of all the customers who intended to transact businesses with the banks within the period of 11 am to 12 pm. The sample sizes for the first, second and third day of the first bank are twenty-eight (28), seventeen (17) and twenty (20) respectively with three servers on each day whereas that for the first, second and third day of the second bank is twenty (20), nine (9) and seventeen (17) with two servers on each day. A multiple server (M/M/s) Model was adopted, and Tora Software was the statistical tool used for the analysis. Findings of the study revealed that the second bank had a higher utilization factor than the first bank. Also, the number of customers in the banking hall of the second bank was higher than that of the first bank during the entire period of observation. Finally, it takes customers of the first bank lesser minutes to complete their transaction than the second bank. In conclusion, the three days observations revealed different banking situations faced by customers in both banks which had effect on waiting time of customer service. The waiting time of customer service has effect on the number of customers in the queue and system, the probability associated with the emptiness of the system and the utilization factor. Based on the results, the study recommended, inter alia, that the management of the second bank should adopt a three-server (M/M/3) model.

LSTM Based Spectrum Prediction for Real-Time Spectrum Access for IoT Applications

In the Internet of Things(IoT)scenario,many devices will communi-cate in the presence of the cellular network;the chances of availability of spec-trum will be very scary given the presence of large numbers of mobile users and large amounts of applications.Spectrum prediction is very encouraging for high traffic next-generation wireless networks,where devices/machines which are part of the Cognitive Radio Network(CRN)can predict the spectrum state prior to transmission to save their limited energy by avoiding unnecessarily sen-sing radio spectrum.Long short-term memory(LSTM)is employed to simulta-neously predict the Radio Spectrum State(RSS)for two-time slots,thereby allowing the secondary node to use the prediction result to transmit its information to achieve lower waiting time hence,enhanced performance capacity.A frame-work of spectral transmission based on the LSTM prediction is formulated,named as positive prediction and sensing-based spectrum access.The proposed scheme provides an average maximum waiting time gain of 2.88 ms.The proposed scheme provides 0.096 bps more capacity than a conventional energy detector.

Probability Distributions Arising in Connection with the Inspection Paradox for the Poisson Process

The Inspection Paradox refers to the fact that in a Renewal Process, the length of the interarrival period which contains a fixed time is stochastically larger than the length of a typical interarrival period. To provide a more complete understanding of this phenomenon, conditioning arguments are used to obtain the distributions and moments of the lengths of the interarrival periods other than the one containing this fixed time for the case of the time-homogeneous Poisson Process. Distributions of the waiting times for events that occur both before and after this fixed time are derived. This provides a fairly complete probabilistic analysis of the Inspection Paradox.

Probability Distributions Arising in Connection with the Inspection Paradox for Bernoulli Trials

In renewal theory, the Inspection Paradox refers to the fact that an interarrival period in a renewal process which contains a fixed inspection time tends to be longer than one for the corresponding uninspected process. We focus on the paradox for Bernoulli trials. Probability distributions and moments for the lengths of the interarrival periods are derived for the inspected process, and we compare them to those for the uninspected case.

Glasgow coma scale and APACHE-II scores affect the liver transplantation outcomes in patients with acute liver failure

BACKGROUND:The timing and selection of patients for liver transplantation in acute liver failure are great challenges.This study aimed to investigate the effect of Glasgow coma scale(GCS)and APACHE-II scores on liver transplantation outcomes in patients with acute liver failure.METHOD:A total of 25 patients with acute liver failure were retrospectively analyzed according to age,etiology,time to transplantation,coma scores,complications and mortality.RESULTS:Eighteen patients received transplants from live donors and 7 had cadaveric whole liver transplants.The mean duration of follow-up after liver transplantation was 39.86±40.23 months.Seven patients died within the perioperative period and the 1-,3-,5-year survival rates of the patients were72%,72%and 60%,respectively.The parameters evaluated for the perioperative deaths versus alive were as follows:the mean age of the patients was 33.71 vs 28 years,MELD score was 40 vs32.66,GCS was 5.57 vs 10.16,APACHE-II score was 23 vs 18.11,serum sodium level was 138.57 vs 138.44 mmol/L,mean waiting time before the operation was 12 vs 5.16 days.Low GCS,high APACHE-II score and longer waiting time before the operation(P【0.01)were found as statistically significant factors for perioperative mortality.CONCLUSION:Lower GCS and higher APACHE-II scores are related to poor outcomes in patients with acute liver failure after liver transplantation.

A DISCRETE TIME TWO-LEVEL MIXED SERVICE PARALLEL POLLING MODEL

We present a discrete time single-server two-level mixed service polling systems with two queue types, one center queue and N normal queues. Two-level means the center queue will be successive served after each normal queue. In the first level, server visits between the center queue and the normal queue. In the second level, normal queues are polled by a cyclic order. Mixed service means the service discipline are exhaustive for center queue, and parallel 1-limited for normal queues. We propose an imbedded Markov chain framework to drive the closed-form expressions for the mean cycle time, mean queue length, and mean waiting time. Numerical examples demonstrate that theoretical and simulation results are identical the new system efficiently differentiates priorities.

Lean techniques for the improvement of patients' flow in emergency department

BACKGROUND: Emergency departments(EDs) face problems with overcrowding, access block, cost containment, and increasing demand from patients. In order to resolve these problems, there is rising interest to an approach called "lean" management. This study aims to(1) evaluate the current patient flow in ED,(2) to identify and eliminate the non-valued added process, and(3) to modify the existing process.METHODS: It was a quantitative, pre- and post-lean design study with a series of lean management work implemented to improve the admission and blood result waiting time. These included structured re-design process, priority admission triage(PAT) program, enhanced communication with medical department, and use of new high sensitivity troponin-T(hsTnT) blood test. Triage waiting time, consultation waiting time, blood result time, admission waiting time, total processing time and ED length of stay were compared.RESULTS: Among all the processes carried out in ED, the most time consuming processes were to wait for an admission bed(38.24 minutes; SD 66.35) and blood testing result(mean 52.73 minutes, SD 24.03). The triage waiting time and end waiting time for consultation were significantly decreased. The admission waiting time of emergency medical ward(EMW) was significantly decreased from 54.76 minutes to 24.45 minutes after implementation of PAT program(P<0.05).CONCLUSION: The application of lean management can improve the patient flow in ED. Acquiescence to the principle of lean is crucial to enhance high quality emergency care and patient satisfaction.

An efficient priority service model with two-level-polling scheme

This paper considers an efficient priority service model with two-level-polling scheme which the message packets conform to the discrete-time Geom/G/1 queue with multiple vacations and bulk arrival. By the embedded Markov chain theory and the probability generating function method, we set up the mathematics functions and give closed form expressions for obtaining the mean cyclic period （MCP）, the mean queue length （MQL） and the mean waiting time （MWT） characteristics, the analytical results are also verified through extensive computer simulations. The performance analysis reveals that this priority polling scheme can gives better efficiency as well as impartiality in terms of system characteristics, and it can be used for differentiating priority service to guarantee better QoS and system stability in design and improvement of MAC protocol.

Effect and satisfaction of outpatient services by precision valuation reservation registration

BACKGROUND Due to improvements in living standards,people are now paying more attention to their health.In China,more patients choose to go to large or well-known hospitals,which leads to constant crowding of outpatient clinics in these hospitals.AIM To establish precision valuation reservation registration aimed at shortening waiting time,improving patient experience and promoting the satisfaction of outpatients and medical staff.METHODS On the basis of the implementation of a conventional appointment system,more reasonable time intervals were set for different doctors by evaluating the actual capacity of each doctor to receive patients,and appointment times were made more accurate through intervention.The change in consultation waiting time of patients was then compared.Correlations between the consultation waiting time of patients and the satisfaction of patients or satisfaction of medical staff were analyzed.RESULTS After precision valuation reservation registration,the average consultation waiting time of patients reduced from 18.47 min to 10.11 min(t=8.90,P<0.001).The satisfaction score of patients increased from 91.33 to 96.27(t=-8.62,P<0.001),and the satisfaction score of medical staff increased from 90.51 to 96.04(t=-10.50,P<0.001).The consultation waiting time of patients was negatively correlated with their satisfaction scores(γ=-0.89,P<0.001).The consultation waiting time of patients was also negatively correlated with medical staff satisfaction scores(γ=-0.96,P<0.001).CONCLUSION Precision valuation reservation registration significantly shortened outpatient waiting times and improve the satisfaction of not only patients but also medical staff.This approach played an important role in improving outpatient services,provided a model that is supported by relevant evidence and could continuously improve the quality of management.Precision valuation reservation registration is worth promoting and applying in the clinic.

An Adjustable Variant of Round Robin Algorithm Based on Clustering Technique

CPU scheduling is the basic task within any time-shared operating system.One of the main goals of the researchers interested in CPU scheduling is minimizing time cost.Comparing between CPU scheduling algorithms is subject to some scheduling criteria(e.g.,turnaround time,waiting time and number of context switches(NCS)).Scheduling policy is divided into preemptive and non-preemptive.Round Robin(RR)algorithm is the most common preemptive scheduling algorithm used in the time-shared operating systems.In this paper,the authors proposed a modified version of the RR algorithm,called dynamic time slice(DTS),to combine the advantageous of the low scheduling overhead of the RR and favor short process for the sake of minimizing time cost.Each process has a weight proportional to the weights of all processes.The process’s weight determines its time slice within the current period.The authors benefit from the clustering technique in grouping the processes that are similar in their attributes(e.g.,CPU service time,weight,allowed time slice(ATS),proportional burst time(PBT)and NCS).Each process in a cluster is assigned the average of the processes’time slices in this cluster.A comparative study of six popular scheduling algorithms and the proposed approach on nine groups of processes vary in their attributes was performed and the evaluation was measured in terms of waiting and turnaround times,and NCS.The experiments showed that the proposed algorithm gives better results.

Study of Asymmetric Polling System with Two Message Classes

A novel mixed polling system with multiple stations is considered. Each station produces two classes of messages served with different disciplines. The real time message served with exhaustive service discipline and the unreal time message served with gated service discipline. Using an iterative method, the exact mean waiting times for both message classes are derived. The influence of the gate location of the message class served by the gated service discipline on the mean waiting time is also analyzed. The analytical results are verified with simulation method and agree well with simulation results.