Announcing Waiting Time in Emergency Departments

2019 ◽  
pp. 1-6
Author(s):  
Martin Lariviere ◽  
Sarang Deo
Keyword(s):  
Waiting Time ◽  
Emergency Departments ◽  
Waiting Times ◽  
Large Network ◽  
Regional Networks ◽  
Marketing Campaign ◽  
National Healthcare ◽  
Time Estimates ◽  
Patient Waiting Time ◽  
Patient Waiting

First National Healthcare (FNH) runs a large network of hospitals and has worked to systematically reduce waiting times in its emergency departments. One of FNH's regional networks has run a successful marketing campaign promoting its low ED waiting times that other regions want to emulate. The corporate quality manager must now determine whether to allow these campaigns to be rolled out and, if so, which waiting time estimates to use. Are the numbers currently being reported accurate? Is there a more accurate way of estimating patient waiting time that can be easily understood by consumers?

scholarly journals Factors Associated With Patient Waiting Time at a Medical Outpatient Clinic: A Case Study of University of Nairobi Health Services

2021 ◽  
Vol 6 (12) ◽  
pp. 915-918
Author(s):  
Rebecca Bisanju Wafula (BSCN, MSCHSM) ◽  
Dr. Richard Ayah (MBCHB, MSC, PHD)
Keyword(s):  
Health Services ◽  
Health Care Providers ◽  
Waiting Time ◽  
Outpatient Clinic ◽  
Health Workers ◽  
Waiting Times ◽  
Care Providers ◽  
Cross Sectional ◽  
Patient Waiting Time ◽  
Patient Waiting

Background: Long waiting time in outpatient clinics is a constant challenge for patients and the health care providers. Prolonged waiting times are associated with poor adherence to treatment, missed appointment and failure or delay in initiation of treatment and is a major factor towards the perception of the patient towards the care received. Objective: To determine the waiting time and associated factors among out patients attending staff clinic at University of Nairobi health services. Method: A cross-sectional study design was used and data collected from 384 ambulatory patients over a period of four weeks using an interviewer administered pretested structured exit questionnaire with a time-tracking section. Simple random sampling was used to select respondents in a walk- in outpatient clinic set up. Data was cleaned and analysed using Statistical Package for Social Sciences (SPSS) 20. Analysis of variance (ANOVA), and cross tabulation was used to establish associations between the independent variable and dependent variables. Results: In total 384 patients were tracked and interviewed. The average patient waiting time was 55.3mins.Most respondents (52%) suggested that improving availability of staff at their stations would help to reduce patient waiting time. In this study, gender (P=0.005) and availability of doctors (p=0.000) were found to affect patient waiting time with women waiting longer than the male patients. Conclusion: Majority of the patients spent about an hour at the facility to be served. Inadequate number of health workers was the main cause of long waiting time.

Reducing Patient Waiting Time at an Ambulatory Surgical Center

2011 ◽  
pp. 246-260
Author(s):  
David Ben-Arieh ◽  
Chih-Hang Wu
Keyword(s):  
Block Scheduling ◽  
Waiting Time ◽  
Ambulatory Surgery ◽  
For Profit ◽  
Time Estimates ◽  
Patient Waiting Time ◽  
Lower Variability ◽  
Patient Waiting

This chapter describes a methodology to reduce patient waiting time in a for-profit ambulatory surgical center. Patients in this facility are scheduled in advance for the various operations, and yet operations start late, last longer than expected creating undesired delays. Although this facility is limited to ambulatory surgery, it provides a large number of different surgeries, which are scheduled using “block” scheduling approach. The methodology presented generates a more accurate schedule by creating better time estimates for the operations and with lower variability. The effect of sequencing the surgeries, such that the ones with lower variability are performed earlier in the day, is also discussed.

scholarly journals Integral patient scheduling in outpatient clinics under demand uncertainty to minimize patient waiting times

2019 ◽  
Vol 26 (1) ◽  
pp. 435-448 ◽  
Author(s):  
Jyoti R Munavalli ◽  
Shyam Vasudeva Rao ◽  
Aravind Srinivasan ◽  
GG van Merode
Keyword(s):  
Real Time ◽  
Waiting Time ◽  
Outpatient Clinic ◽  
Demand Uncertainty ◽  
Waiting Times ◽  
Optimal Path ◽  
Outpatient Clinics ◽  
Patient Scheduling ◽  
Patient Waiting Time ◽  
Patient Waiting

This study addressed the problem of scheduling walk-in patients in real time. Outpatient clinics encounter uncertainty in patient demand. In addition, the disparate departments are locally (department-centric) organized, leading to prolonged waiting times for patients. The proposed integral patient scheduling model incorporates the status and information of all departments in the outpatient clinic along with all possible pathways to direct patients, on their arrival, to the optimal path. The developed hybrid ant agent algorithm identifies the optimal path to reduce the patient waiting time and cycle time (time from registration to exit). An outpatient clinic in Aravind Eye Hospital, Madurai, has a huge volume of walk-in patients and was selected for this study. The simulation study was performed for diverse scenarios followed by implementation study. The results indicate that integral patient scheduling reduced waiting time significantly. The path optimization in real time makes scheduling effective and efficient as it captures the changes in the outpatient clinic instantly.

Using lean techniques and discrete-event simulation for performance improvement in an outpatient clinic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kudret Demirli ◽  
Abdulqader Al Kaf ◽  
Mecit Can Emre Simsekler ◽  
Raja Jayaraman ◽  
Mumtaz Jamshed Khan ◽  
...  
Keyword(s):  
Health Care ◽  
Discrete Event Simulation ◽  
Waiting Time ◽  
Outpatient Clinic ◽  
Waiting Times ◽  
Discrete Event ◽  
Content Type ◽  
Event Simulation ◽  
Patient Waiting Time ◽  
Patient Waiting

Purpose Increased demand and the pressure to reduce health-care costs have led to longer waiting time for patients to make appointments and during the day of hospital visits. The purpose of this study is to identify opportunities to reduce waiting time using lean techniques and discrete-event simulation (DES). Design/methodology/approach A five-step procedure is proposed to facilitate the effective utilization of lean and DES to improve the performance of the Otolaryngology Head and Neck Surgery Outpatient Clinic at Cleveland Clinic Abu Dhabi. While lean techniques were applied to reduce the potential sources of waste by aligning processes, a DES model was developed to validate the proposed solutions and plan patient arrivals under dynamic conditions and different scenarios. Findings Aligning processes resulted in an efficient patient flow reducing both waiting times. DES played a complementary role in verifying lean solutions under dynamic conditions, helping to plan the patient arrivals and striking a balance between the waiting times. The proposed solutions offered flexibility to improve the clinic capacity from the current 176 patients up to 479 (without violating the 30 min waiting time policy) or to reduce the patient waiting time during the visit from the current 33 min to 4.5 min (without violating the capacity goal of 333 patients). Research limitations/implications Proposing and validating lean solutions require reliable data to be collected from the clinic and such a process could be laborious as data collection require patient and resource tracing without interfering with the regular functions of the clinic. Practical implications The work enables health-care managers to conveniently conduct a trade-off analysis and choose a suitable inter-arrival time – for every physician – that would satisfy their objectives between resource utilization (clinic capacity) and average patient waiting time. Social implications Successful implementation of lean requires a supportive and cooperative culture from all stakeholders involved. Originality/value This study presents an original and detailed application of lean techniques with DES to reduce patient waiting times. The adopted approach in this study could be generalized to other health-care settings with similar objectives.

Study of Patient Waiting Time in the Emergence Department: An Example of a Medical Center in New Taipei County, Taiwan

2014 ◽  
Vol 519-520 ◽  
pp. 1581-1584
Author(s):  
Chen Shie Ho ◽  
Min Li Yeh ◽  
Yu Sheng Liao
Keyword(s):  
Emergency Department ◽  
Waiting Time ◽  
Queuing Theory ◽  
Flow Model ◽  
Medical Center ◽  
Waiting Times ◽  
Literature Survey ◽  
Theory Analysis ◽  
Patient Waiting Time ◽  
Patient Waiting

Patients who receive care in an emergency department (ED) are usually unattended while waiting in queues. This study attempted to determine whether the application of queuing theory analysis might shorten the waiting times of patients admitted to emergency wards. After the literature survey phase, the flow model to evaluate the patient waiting time in the emergence department corresponding to the target hospital is presented, then the waiting time under some circumstance are simulated. By allocating the human and space resource dynamically, the waiting time can be reduced then patient satisfaction is improved.

scholarly journals Predicting Patient Waiting Time in the Queue System Using Deep Learning Algorithms in the Emergency Room

2021 ◽  
Vol 03 (01) ◽  
pp. 33-45
Author(s):  
Hassan Hijry ◽  
Richard Olawoyin
Keyword(s):  
Deep Learning ◽  
Emergency Room ◽  
Waiting Time ◽  
Waiting Times ◽  
Real Life ◽  
Healthcare Sector ◽  
Medical Attention ◽  
Queue System ◽  
Patient Waiting Time ◽  
Patient Waiting

Many hospitals consider the length of time waiting in queue to be a measure of emergency room (ER) overcrowding. Long waiting times plague many ER departments, hindering the ability to effectively provide medical attention to those in need and increasing overall costs. Advanced techniques such as machine learning and deep learning (DL) have played a central role in queuing system applications. This study aims to apply DL algorithms for historical queueing variables to predict patient waiting time in a system alongside, or in place of, queueing theory (QT). We applied four optimization algorithms, including SGD, Adam, RMSprop, and AdaGrad. The algorithms were compared to find the best model with the lowest mean absolute error (MAE). A traditional mathematical simulation was used for additional comparisons. The results showed that the DL model is applicable using the SGD algorithm by activating a lowest MAE of 10.80 minutes (24% error reduction) to predict patients' waiting times. This work presents a theoretical contribution of predicting patients’ waiting time with alternative techniques by achieving the highest performing model to better prioritize patients waiting in the queue. Also, this study offers a practical contribution by using real-life data from ERs. Furthermore, we proposed models to predict patients' waiting time with more accurate results than a traditional mathematical method. Our approach can be easily implemented for the queue system in the healthcare sector using electronic health records (EHR) data.

scholarly journals The Use of Information Technology to Short the Waiting Time for Examination of Road Care Patients at RSU Islam Klaten

2021 ◽  
Vol 04 (01) ◽  
Author(s):  
Owin Bambang Wijanarko ◽  
Keyword(s):  
Information Technology ◽  
Patient Satisfaction ◽  
Health Services ◽  
Waiting Time ◽  
Waiting Times ◽  
Value Added ◽  
Outpatient Services ◽  
Cross Sectional ◽  
Patient Waiting Time ◽  
Patient Waiting

Background: Outpatient services are a reflection of hospital services.As a form of health service facility that organizes health efforts, hospitals often experience difficulties in managing information for both internal and external needs. One form of application is through service systems by utilizing information technology through the use of computer-based on information systems.The Lean Hospital concept, which has been successfully implemented in several hospitals, is expected to eliminate waste and add value added activity which will ultimately increase patient satisfaction. Purpose: The purpose of this study was to calculate patient waiting time with the application of information technology in the outpatient polyclinic of RSU Islam Klaten. Research methods: This type of research uses a descriptive analytic method. This research meth-od used a cross sectional approach. The sample in this study amounted to 81 respondents with the sampling technique using purposive sampling. The analysis in research using the t-test. The re-search instruments used included literature studies, interviews and direct observation of medical record officers, nurses of polyclinic nurses, registration departments, and patients at RSU Islam Klaten. Result: There is a significant relationship between waiting time and patient satisfaction p = 0.001. Patients with long waiting times were more dissatisfied (60.0%), while fast waiting times were more very satisfied (73.9%). Conclusion: The success of health services is seen from the patient's waiting time and patient satisfaction. Waiting time is the time used by patients to get health services from the registration point to getting in the doctor's examination room. Overall information technology shortens patient waiting time in parts of registration-polyclinic and Pharmacy.

Relationship Between Waiting Time on Patient Satisfaction at Baloi Permai Batam Puskesmas Year 2021

2022 ◽  
Vol 2 (1) ◽  
pp. 73-80
Author(s):  
Riza Suci Ernaman Putri ◽  
Veggi Klawdina ◽  
Fani Farhansyah
Keyword(s):  
Patient Satisfaction ◽  
Waiting Time ◽  
Waiting Times ◽  
P Value ◽  
Chi Square ◽  
Outpatient Unit ◽  
Level Of Satisfaction ◽  
Patient Waiting Time ◽  
The Relationship ◽  
Patient Waiting

Background: Medical records are an important part in assisting the implementation of service delivery to patients in hospitals. This research aimsMethods: Quantitative with survey research, a quantitative approach is used to find out how effective the relationship between waiting time and patient satisfaction is at the Baloi Permai Health Center.Results: The results of the chi square statistical test showed that the p-value of 0.001 was less than 0.050, so it can be said that there is a significant relationship between waiting time and patient satisfaction. The odds ratio for the relationship between waiting time and patient satisfaction is 7.263 with 95% CI between 2.143- 24.614. Patients with long waiting times are 7,263 or 7 times more likely to have a low level of satisfaction compared to patients whose waiting times are not too long.Conclusions: Based on the results of the study, it can be concluded that there is an effect of patient waiting time on outpatient satisfaction. The staff of the Baloi Perma Batam outpatient unit should further improve services, especially for waiting time for outpatients. Based on the results of the study, it can be concluded that there is an effect of patient waiting time on outpatient satisfaction. The staff of the Baloi Perma Batam outpatient unit should further improve services, especially for waiting time for outpatients.

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