Enhancing outpatient appointment scheduling system performance when patient no-show percent and lateness rates are high

2018 ◽  
Vol 31 (4) ◽  
pp. 309-326 ◽  
Author(s):  
Mahmoud Barghash ◽  
Hanan Saleet
Keyword(s):  
Waiting Time ◽  
Waiting Times ◽  
Multiple Objectives ◽  
Outpatient Clinics ◽  
Arrival Process ◽  
Content Type ◽  
Scheduling System ◽  
Modeling Procedure ◽  
Basic Interval ◽  
Patient Arrival

Purpose High lateness and no-show percentages pose great challenges on the patient scheduling process. Usually this is addressed by optimizing the time between patients in the scheduling process and the percent of extra patients scheduled to account for absent patients. However, since the patient no-show and lateness is highly stochastic we might end up with many patients showing up on time which leads to crowded clinics and high waiting times. The clinic might end up as well with low utilization of the doctor time. The purpose of this paper is to study the effect of scheduled overload percentages and the patient interval on the waiting time, overtime, and the utilization. Design/methodology/approach Actual data collection and statistical modeling are used to model the distribution for common dentist procedures. Simulation and validation are used to model the treatment process. Then algorithm development is used to model and generate the patient arrival process. The simulation is run for various values of basic interval scheduled time between arrivals for the patients. Further, 3D graphical illustration for the objectives is prepared for the analysis. Findings This work initially reports on the statistical distribution for the common procedures in dentist clinics. This can be used for developing a scheduling system and for validating the scheduling algorithms developed. This work also suggest a model for generating patient arrivals in simulation. It was found that the overtime increases excessively when coupling both high basic interval and high overloading percentage. It was also found that: to obtain low overtime we must reduce the basic interval. Waiting time increases when reducing the basic scheduled appointment interval and increase the scheduled overload percentage. Also doctors’ utilization is increased when the basic interval is reduced. Research limitations/implications This work was done at a local clinic and this might limit the value of the modeled procedure times. Practical implications This work presents a statistical model for the various procedures and a detailed technique to model the operations of the clinics and the patient arrival time which might assist researches and developers in developing their own model. This work presents a procedure for troubleshooting scheduling problems in outpatient clinics. For example, a clinic suffering from high patient waiting time is directly instructed to slightly increase their basic scheduled interval between patients or slightly reduce the overloading percentage. Social implications This work is targeting an extremely important constituent of the health-care system which is the outpatient clinics. It is also targeting multiple objectives namely waiting times, utilization overtime, which in turn is related to the economics and doctor utilization. Originality/value This work presents a detailed modeling procedure for the outpatient clinics under high lateness and no-show and addresses the modeling procedure for the patient arrivals. This 3D graphical charting for the objectives includes a study of the multiple objectives that are of high concern to outpatient clinic scheduling interested parties in one paper.

493 Evaluation of Patient Waiting Times for Plain Radiographs Whilst Attending Outpatient Clinics in A Tertiary Orthopaedic Centre

2021 ◽  
Vol 108 (Supplement_2) ◽  
Author(s):  
Z Hayat ◽  
E Kinene ◽  
S Molloy
Keyword(s):  
Waiting Time ◽  
Waiting Times ◽  
Time Frame ◽  
Outpatient Clinics ◽  
Contributing Factors ◽  
Time Data ◽  
Work Related ◽  
Mean Waiting Time ◽  
Appointment Time ◽  
Related Stress

Abstract Introduction Reduction of waiting times is key to delivering high quality, efficient health care. Delays experienced by patients requiring radiographs in orthopaedic outpatient clinics are well recognised. Method To establish current patient and staff satisfaction, questionnaires were circulated over a two-week period. Waiting time data was retrospectively collected including appointment time, arrival time and the time at which radiographs were taken. Results 84% (n = 16) of radiographers believed patients would be dissatisfied. However, of the 296 patients questioned, 56% (n = 165) were satisfied. Most patients (89%) felt the waiting time should be under 30 minutes. Only 36% were seen in this time frame. There was moderate negative correlation (R=-0.5); higher waiting times led to increased dissatisfaction. Mean waiting time was 00:37 and the maximum 02:48. Key contributing factors included volume of patients, staff shortages (73.7%), equipment shortages (57.9%) and incorrectly filled request forms. Eight (42.1%) had felt unwell from work related stress. Conclusions A concerted effort is needed to improve staff and patient opinion. There is scope for change post COVID. Additional training and exploring ways to avoid overburdening the department would benefit. Numerous patients were open to different days or alternative sites. Funding requirements make updating equipment, expanding the department and recruiting more staff challenging.

Enhancing patient flow in emergency department (ED) using lean strategies–an integrated voice of customer and voice of process perspective

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ali Alowad ◽  
Premaratne Samaranayake ◽  
Kazi Ahsan ◽  
Hisham Alidrisi ◽  
Azharul Karim
Keyword(s):  
Waiting Time ◽  
Emergency Services ◽  
Single Case ◽  
Patient Flow ◽  
Waiting Times ◽  
Small Sample ◽  
Content Type ◽  
Lean Tools ◽  
And Performance ◽  
Voice Of Customer

PurposeThe purpose of this paper is to systematically investigate the patient flow and waiting time problems in hospital emergency departments (EDs) from an integrated voice of customer (VOC) and voice of process (VOP) perspective and to propose a new lean framework for ED process.Design/methodology/approachA survey was conducted to better understand patients' perceptions of ED services, lean tools such as process mapping and A3 problem-solving sheets were used to identify hidden process wastes and root-cause analysis was performed to determine the reasons of long waiting time in ED.FindingsThe results indicate that long waiting times in ED are major concerns for patients and affect the quality of ED services. It was revealed that limited bed capacity, unavailability of necessary staff, layout of ED, lack of understanding among patients about the nature of emergency services are main causes of delay. Addressing these issues using lean tools, integrated with the VOC and VOP perspectives can lead to improved patient flow, higher patient satisfaction and improvement in ED capacity. A future value stream map is proposed to streamline the ED activities and minimize waiting times.Research limitations/implicationsThe research involves a relatively small sample from a single case study. The proposed approach will enable the ED administrators to avoid the ED overcrowding and streamline the entire ED process.Originality/valueThis research identified ED quality issues from the integration of VOC and VOP perspective and suggested appropriate lean tools to overcome these problems. This process improvement approach will enable the ED administrators to improve productivity and performance of hospitals.

scholarly journals Student Flow Scheduling System for Student Affairs By Using Queuing Theory

2020 ◽  
pp. 583-591
Author(s):  
Soe Moe Aye ◽  
Aye Aye Thant ◽  
Soe Soe Nwe
Keyword(s):  
Computer Simulation ◽  
Student Affairs ◽  
Student Satisfaction ◽  
Waiting Time ◽  
Queuing Theory ◽  
Waiting Times ◽  
Scheduling System ◽  
Queuing Analysis ◽  
Actual Operation ◽  
Student Flow

This Student registration at University involved students being registered in Student Affairs Department and make a deposit in Finance Department within the University, where they would present a form which had previously been filled in by the student. Students often wait for minutes, hours, half day or days to receive registration service for which they were waiting. Delays in the registration may result in difficulties of scheduling at speciality units and decrease in student satisfaction. This system examines the wide-spread problem of extended waiting times for registration. This system implements as student flow scheduling system and can help staff of student affairs department to reduce student congestion in department. This system uses Queuing analysis and Computer Simulation in Operation Research (OR) field. OR is a scientific approach to analyse problem and reduce waiting time. Simulation is the use of a system model that has the mapped characteristics of existence in order to produce the essence of actual operation. This system presents stand-alone application to help student registration using queuing analysis and computer simulation whose are finding appropriate waiting time for student affairs department.

Improving process quality for pediatric emergency department

2014 ◽  
Vol 27 (4) ◽  
pp. 336-346 ◽  
Author(s):  
Byungjoon B.J. Kim ◽  
Theodore R. Delbridge ◽  
Dawn B. Kendrick
Keyword(s):  
Flow Control ◽  
Waiting Time ◽  
Pediatric Patients ◽  
Waiting Times ◽  
Discrete Event ◽  
Process Quality ◽  
Content Type ◽  
Arrival Times ◽  
Number Of Patients ◽  
Control Management

Purpose – Overcrowding in emergency departments (EDs) leads to longer waiting times and results in higher number of patients leaving the ED without being seen by a physician. EDs need to improve quality for patients’ waiting time and length of stay (LoS) from the perspective of process and flow control management. The paper aims to discuss these issues. Design/methodology/approach – The retrospective case study was performed using the computerized ED patient time logs from arrival to discharge between July 1, 2009 and June 30, 2010. Patients were divided into two groups either adult or pediatric with a cutoff age of 18. Patients’ characteristics were measured by arrival time periods, waiting times before being seen by a physician, total LoS and acuity levels. A discrete event simulation was applied to the comparison of quality performance measures. Findings – Statistically significant differences were found between the two groups in terms of arrival times, acuity levels, waiting time stratified for various arrival times and acuity levels. The process quality for pediatric patients could be improved by redesign of patient flow management and medical resource. Research limitations/implications – The results are limited to a case of one community and ED. This study did not analyze the characteristic of leaving the ED without being seen by a physician. Practical implications – Separation of pediatric patients from adult patients in an ED can reduce the waiting time before being seen by a physician and the total staying time in the ED for pediatric patients. It can also lessen the chances for pediatric patients to leave the ED without being seen by a physician. Originality/value – A process and flow control management scheme based on patient group characteristics may improve service quality and lead to a better patient satisfaction in ED.

scholarly journals Prevalence and factors associated with missed hospital appointments: a retrospective review of multiple clinics at Royal Hospital, Sultanate of Oman

BMJ Open ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. e046596
Author(s):  
Ahmed Alawadhi ◽  
Victoria Palin ◽  
Tjeerd van Staa
Keyword(s):  
Waiting Time ◽  
Conditional Logistic Regression ◽  
Waiting Times ◽  
Outpatient Clinics ◽  
Secondary Outcome ◽  
Missed Appointments ◽  
Tertiary Referral Hospital ◽  
Cross Sectional ◽  
Royal Hospital ◽  
Lack Of Information

ObjectivesMissed hospital appointments pose a major challenge for healthcare systems. There is a lack of information about drivers of missed hospital appointments in non-Western countries and extent of variability between different types of clinics. The aim was to evaluate the rate and predictors of missed hospital appointments and variability in drivers between multiple outpatient clinics.SettingOutpatient clinics in the Royal hospital (tertiary referral hospital in Oman) between 2014 and 2018.ParticipantsAll patients with a scheduled outpatient clinic appointment (N=7 69 118).Study designRetrospective cross-sectional analysis.Primary and secondary outcome measuresA missed appointment was defined as a patient who did not show up for the scheduled hospital appointment without notifying or asking for the appointment to be cancelled or rescheduled. The outcomes were the rate and predictors of missed hospital appointments overall and variations by clinic. Conditional logistic regression compared patients who attended and those who missed their appointment.ResultsThe overall rate of missed hospital appointments was 22.3%, which varied between clinics (14.0% for Oncology and 30.3% for Urology). Important predictors were age, sex, service costs, patient’s residence distance from hospital, waiting time and appointment day and season. Substantive variability between clinics in ORs for a missed appointment was present for predictors such as service costs and waiting time. Patients aged 81–90 in the Diabetes and Endocrine clinic had an adjusted OR of 0.53 for missed appointments (95% CI 0.37 to 0.74) while those in Obstetrics and Gynaecology had OR of 1.70 (95% CI 1.11 to 2.59). Adjusted ORs for longer waiting times (>120 days) were 2.22 (95% CI 2.10 to 2.34) in Urology but 1.26 (95% CI 1.18 to 1.36) in Oncology.ConclusionPredictors of a missed appointment varied between clinics in their effects. Interventions to reduce the rate of missed appointments should consider these factors and be tailored to clinic.

Appointment system design with interruptions and physician lateness

2013 ◽  
Vol 33 (4) ◽  
pp. 394-414 ◽  
Author(s):  
Kenneth J. Klassen ◽  
Reena Yoogalingam
Keyword(s):  
Design Methodology ◽  
Simulation Optimization ◽  
Waiting Times ◽  
Outpatient Clinics ◽  
Content Type ◽  
Time Variance ◽  
Physician Time ◽  
Appointment System ◽  
High Level ◽  
Practical Implications

PurposePhysician lateness and service interruptions are a significant problem in many health care environments but have received little attention in the literature. The purpose of this paper is to design appointment systems that reduce waiting times of the patient while maintaining utilization of the physician at a high level.Design/methodology/approachEmpirical data from time studies and surveys of medical professionals from multiple outpatient clinics are used to motivate the study. Simulation optimization is used to simultaneously account for uncertainty and to determine (near) optimal scheduling solutions.FindingsAs lateness increases, it is shown that, in general, appointment slots should be shorter and pushed later in the session. Conversely, as interruptions rise, appointments in the middle of the session should be longer. These findings are fairly consistent over a variety of environmental conditions, including clinic sizes, service time variance, and costs of physician time compared to patients' time.Practical implicationsThis paper demonstrates that the dome/plateau‐dome scheduling patterns that have been found in prior studies work well under many of the new factors modeled here. This is encouraging because it suggests that a generalizable pattern is emerging in the literature for the range of environments studied in these papers and this research provides guidance as to how to adjust the pattern to account for the factors studied here. In addition, it is shown that some environments will perform better with a different pattern, which the authors denote a “descending step” pattern.Originality/valueThis paper differs from most prior studies in that the complexity of environmental variables and stochastic elements of the model are simultaneously accounted for by the simulation optimization algorithm. The (very few) prior papers that have used simulation optimization have not addressed the factors studied here.

scholarly journals Determinants of hospital waiting time for outpatient care in India: how demographic characteristics, hospital ownership, and ambulance arrival affect waiting tim

2018 ◽  
Vol 5 (7) ◽  
pp. 2692
Author(s):  
Shyamkumar Sriram ◽  
Rakchanok Noochpoung
Keyword(s):  
Waiting Time ◽  
Waiting Times ◽  
Wait Time ◽  
Study Data ◽  
Outpatient Clinics ◽  
Related Factors ◽  
Factors Affecting ◽  
Logistic Regression Models ◽  
For Profit ◽  
Hospital Revenue

Background: Waiting time in hospital outpatient clinics affects patient satisfaction, access to care, health outcomes, trust, willingness to return and hospital revenue. Only a few studies have explored length and variability of waiting times among patients. This study is an attempt to understand factors affecting waiting time experienced by patients in outpatient clinics.Methods: For this study, data were collected in 2012 from 830 patients seeking care from outpatient clinics located in 30 randomly selected hospitals in the district of Nellore, India. Linear regression and logistic regression models have been used to identify the effect of various determinants on hospital waiting times.Results: The average waiting time in government hospitals was 20.3 minutes compared to 15.5 minutes in private hospitals and 39.71 minutes in voluntary hospitals. Waiting time of men was about six minutes lower than women. After controlling for other patient related and hospital related factors, median wait time was 19% lower for male patients compared to females. Length of waiting declines with patient's age. Patients arriving by ambulance waited 64% less that patients not arriving by ambulance but this pattern was not valid for public hospitals.Conclusions: Significant gender bias was present in all facility-types implying that policy and legal interventions would be required. For-profit hospitals had lower waiting time of patients to ensure higher demand for their services by the economically better-off sections of the population. The results highlight the importance of lowering the waiting time in public sector hospitals, especially for patients arriving in ambulances.

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.

Implementing Lean Six Sigma in a Kuwaiti private hospital

2019 ◽  
Vol 32 (2) ◽  
pp. 431-446 ◽  
Author(s):  
Yazan Al-Zain ◽  
Lawrence Al-Fandi ◽  
Mazen Arafeh ◽  
Samar Salim ◽  
Shouq Al-Quraini ◽  
...  
Keyword(s):  
Waiting Time ◽  
Six Sigma ◽  
Private Hospital ◽  
Cost Benefit Analysis ◽  
Waiting Times ◽  
Lean Six Sigma ◽  
Pareto Chart ◽  
Content Type ◽  
Sigma Level ◽  
Project Objectives

Purpose The purpose of this paper is to use Lean Six Sigma (LSS) to reduce patient waiting time in a Kuwaiti private hospital obstetrics and gynaecology clinic. Approach The define, measure, analyse, improve and control methodology was used. The “define” stage involved identifying patients’ needs, system capabilities and project objectives. The “measure” stage assessed the system’s current state through data collection on waiting times. Dunnett’s test, control charts and process capability analysis were used to ensure data accuracy. In the “analyse” stage, an Ishikawa diagram and Pareto chart were constructed, showing that overbooking appointments, doctors’ unscheduled breaks and doctors not arriving on time were the root causes of the problem. The “improve” stage used an Arena simulation model to represent current and improved system status. The proposed solutions were implemented and monitored in the “control” stage. Findings A sigma-level improvement of 300 per cent (0.5–2.0) was realized for appointment patients on Saturdays, with a 67 per cent reduction in waiting time. For walk-ins, the sigma level improved by 288 per cent (0.8–3.1), with a 55 per cent reduction in waiting time. For weekday appointments, the sigma level improved by 111 per cent (0.9–1.9), with a 63 per cent reduction in waiting time. For walk-ins, the sigma level improved by 69 per cent (1.6–2.7), with a 46 per cent reduction in waiting time. A cost–benefit analysis estimated the present project value at $656,459, leading to a total of $5,820,319 in savings by 2025. Originality/value This paper fulfils the need for process improvement, increasing patients’ satisfaction and hospitals’ profitability using LSS.

scholarly journals The Waiting-Time Distribution for the GI/G/1 Queue under the D-Policy

1992 ◽  
Vol 6 (3) ◽  
pp. 287-308 ◽  
Author(s):  
Jingwen Li ◽  
Shun-Chen Niu
Keyword(s):  
Waiting Time ◽  
Time Distribution ◽  
Busy Period ◽  
Waiting Times ◽  
Optimization Models ◽  
Arrival Process ◽  
Waiting Time Distribution ◽  
Service Times

We study a generalization of the GI/G/l queue in which the server is turned off at the end of each busy period and is reactivated only when the sum of the service times of all waiting customers exceeds a given threshold of size D. Using the concept of a “randomly selected” arriving customer, we obtain as our main result a relation that expresses the waiting-time distribution of customers in this model in terms of characteristics associated with a corresponding standard GI/G/1 queue, obtained by setting D = 0. If either the arrival process is Poisson or the service times are exponentially distributed, then this representation of the waiting-time distribution can be specialized to yield explicit, transform-free formulas; we also derive, in both of these cases, the expected customer waiting times. Our results are potentially useful, for example, for studying optimization models in which the threshold D can be controlled.

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