Managing a mixed-registration-type appointment system in outpatient clinics

Characteristics of Walk-In Patients and Related Factors in a Dental University Hospital

This study aimed to identify the characteristics of walk-in patients who visited a dental university hospital more than once (returning patient). The factors affecting walk-in visits were analyzed in relation to demographic, appointment, and treatment characteristics among 146,567 cases treated between 1 March 2019 and 29 February 2020. Multiple logistic regression was used to assess factors influencing walk-in visits. The walk-in rate was 14.1%. The likelihood of walk-in visits was higher in men, patients aged 20–39 years, patients residing in Seoul, and hospital employees or their family members. Walk-in visits were more likely to take place from 8:00 to 9:59 and on Saturdays and Mondays. The walk-in odds ratios differed depending on the treatment department and diagnosis. Return patients had higher odds of walk-in visits for treatments not covered by insurance. The probability of being a walk-in patient was lower among patients who also received treatment in other departments on the same day than among those who did not. These results indicate that each examined factor has a predictable pattern. The findings also suggest a relatively high percentage of walk-in cases in dental university hospitals and that walk-in patients differ in their characteristics from patients with appointments.

A discrete event simulation to evaluate impact of radiology process changes on emergency department computed tomography access

BACKGROUND

Hospitals face the challenge of managing demand for limited computed tomography (CT) resources from multiple patient types while ensuring timely access.

METHODS

A discrete event simulation model was created to evaluate CT access time for emergency department (ED) patients at a large academic medical center with six unique CT machines that serve unscheduled emergency, semi-scheduled inpatient, and scheduled outpatient demand. Three operational interventions were tested: adding additional patient transporters, using an alternative creatinine lab, and adding a registered nurse dedicated to monitoring CT patients in the ED.

RESULTS

All interventions improved access times. Adding one or two transporters improved ED access times by up to 9.8 minutes (Mann-Whitney (MW) CI: [-11.0,-8.7]) and 10.3 minutes (MW CI [-11.5, -9.2]). The alternative creatinine and RN interventions provided 3-minute (MW CI: [-4.0, -2.0]) and 8.5-minute (MW CI: [-9.7, -8.3]) improvements.

CONCLUSIONS

Adding one transporter provided the greatest combination of reduced delay and ability to implement. The projected simulation improvements have been realized in practice.

An intelligent real-time scheduler for out-patient clinics: A multi-agent system model

Scheduling of resources and patients are crucial in outpatient clinics, particularly when the patient demand is high and patient arrivals are random. Generally, outpatient clinic systems are push systems where scheduling is based on average demand prediction and is considered for long term (monthly or bimonthly). Often, planning and actual scenario vary due to uncertainty and variability in demand and this mismatch results in prolonged waiting times and under-utilization of resources. In this article, we model an outpatient clinics as a multi-agent system and propose an intelligent real-time scheduler that schedules patients and resources based on the actual status of departments. Two algorithms are implemented: one for resource scheduling that is based on predictive demand and the other is patient scheduling which performs path optimization depending on the actual status of departments. In order to match resources with stochastic demand, a coordination mechanism is developed that reschedules the resources in the outpatient clinics in real time through auction-bidding procedures. First, a simulation study of intelligent real-time scheduler is carried out followed by implementation of the same in an outpatient clinic of Aravind Eye Hospital, Madurai, India. This hospital has huge patient demand and the patient arrivals are random. The results show that the intelligent real-time scheduler improved the performance measures like waiting time, cycle time, and utilization significantly compared to scheduling of resources and patients in isolation. By scheduling resources and patients, based on system status and demand, the outpatient clinic system becomes a pull system. This scheduler transforms outpatient clinics from open loop system to closed-loop system.

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

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 the Integration of Discrete Event and Agent-Based Simulation to Enhance Outpatient Service Quality in an Orthopedic Department

Many hospitals are currently paying more attention to patient satisfaction since it is an important service quality index. Many Asian countries' healthcare systems have a mixed-type registration, accepting both walk-in patients and scheduled patients. This complex registration system causes a long patient waiting time in outpatient clinics. Different approaches have been proposed to reduce the waiting time. This study uses the integration of discrete event simulation (DES) and agent-based simulation (ABS) to improve patient waiting time and is the first attempt to apply this approach to solve this key problem faced by orthopedic departments. From the data collected, patient behaviors are modeled and incorporated into a massive agent-based simulation. The proposed approach is an aid for analyzing and modifying orthopedic department processes, allows us to consider far more details, and provides more reliable results. After applying the proposed approach, the total waiting time of the orthopedic department fell from 1246.39 minutes to 847.21 minutes. Thus, using the correct simulation model significantly reduces patient waiting time in an orthopedic department.

Factors determining perceptions of fairness in access to hospital outpatient departments in Taiwan

Objectives To investigate the effects of four factors on perceptions of fairness in access to outpatient services: proportions of walk-in versus scheduled registration, consultation queues, regulations for late patients and particular categories of patients getting better access. Methods A total of 124 young adults were asked to consider nine different scenarios and report their views of the fairness of each one. Results As regards the balance of types of patients, 60% walk-in registration was seen as fair to both walk-in and scheduled patients. The fairness to both types of patients was higher in the queue with a 1:1 ratio of walk-in to scheduled patients. The policy that a late patient should wait for three on-time patients to be seen was considered to be fair to both on-time and late patients. Immediate consultation for some particular categories of patient (e.g. the elderly) was fair, but for other categories was unfair (e.g. paying an addition amount). Conclusions Fairness in outpatient care is based on equality and need principles. Shorter waiting time does not mean patients view the system as fairer.

RFID-based information visibility for hospital operations: exploring its positive effects using discrete event simulation

Long queues and wait times often occur at hospitals and affect smooth delivery of health services. To improve hospital operations, prior studies have developed scheduling techniques to minimize patient wait times. However, these studies lack in demonstrating how such techniques respond to real-time information needs of hospitals and efficiently manage wait times. This article presents a multi-method study on the positive impact of providing real-time scheduling information to patients using the RFID technology. Using a simulation methodology, we present a generic scenario, which can be mapped to real-life situations, where patients can select the order of laboratory services. The study shows that information visibility offered by RFID technology results in decreased wait times and improves resource utilization. We also discuss the applicability of the results based on field interviews granted by hospital clinicians and administrators on the perceived barriers and benefits of an RFID system.

Questionnaire survey about use of an online appointment booking system in one large tertiary public hospital outpatient service center in China

Background

As a part of nationwide healthcare reforms, the Chinese government launched web-based appointment systems (WAS) to provide a solution to problems around outpatient appointments and services. These have been in place in all Chinese public tertiary hospitals since 2009.

Methods

Questionnaires were collected from both patients and doctors in one large tertiary public hospital in Shanghai, China.Data were analyzed to measure their satisfaction and views about the WAS.

Results

The 1000 outpatients randomly selected for the survey were least satisfied about the waiting time to see a doctor. Even though the WAS provided a much more convenient booking method, only 17% of patients used it. Of the 197 doctors surveyed, over 90% thought it was necessary to provide alternative forms of appointment booking systems for outpatients. However, about 80% of those doctors who were not associated professors would like to provide an ‘on-the-spot’ appointment option, which would lead to longer waits for patients.

Conclusions

Patients were least satisfied about the waiting times. To effectively reduce appointment-waiting times is therefore an urgent issue. Despite the benefits of using the WAS, most patients still registered via the usual method of queuing, suggesting that hospitals and health service providers should promote and encourage the use of the WAS. Furthermore, Chinese health providers need to help doctors to take others’ opinions or feedback into consideration when treating patients to minimize the gap between patients’ and doctors’ opinions. These findings may provide useful information for both practitioners and regulators, and improve recognition of this efficient and useful booking system, which may have far-reaching and positive implications for China’s ongoing reforms.

Using queuing theory and simulation model to optimize hospital pharmacy performance

BACKGROUND

Hospital pharmacy is responsible for controlling and monitoring the medication use process and ensures the timely access to safe, effective and economical use of drugs and medicines for patients and hospital staff.

OBJECTIVES

This study aimed to optimize the management of studied outpatient pharmacy by developing suitable queuing theory and simulation technique.

PATIENTS AND METHODS

A descriptive-analytical study conducted in a military hospital in Iran, Tehran in 2013. A sample of 220 patients referred to the outpatient pharmacy of the hospital in two shifts, morning and evening, was selected to collect the necessary data to determine the arrival rate, service rate, and other data needed to calculate the patients flow and queuing network performance variables. After the initial analysis of collected data using the software SPSS 18, the pharmacy queuing network performance indicators were calculated for both shifts. Then, based on collected data and to provide appropriate solutions, the queuing system of current situation for both shifts was modeled and simulated using the software ARENA 12 and 4 scenarios were explored.

RESULTS

Results showed that the queue characteristics of the studied pharmacy during the situation analysis were very undesirable in both morning and evening shifts. The average numbers of patients in the pharmacy were 19.21 and 14.66 in the morning and evening, respectively. The average times spent in the system by clients were 39 minutes in the morning and 35 minutes in the evening. The system utilization in the morning and evening were, respectively, 25% and 21%. The simulation results showed that reducing the staff in the morning from 2 to 1 in the receiving prescriptions stage didn't change the queue performance indicators. Increasing one staff in filling prescription drugs could cause a decrease of 10 persons in the average queue length and 18 minutes and 14 seconds in the average waiting time. On the other hand, simulation results showed that in the evening, decreasing the staff from 2 to 1 in the delivery of prescription drugs, changed the queue performance indicators very little. Increasing a staff to fill prescription drugs could cause a decrease of 5 persons in the average queue length and 8 minutes and 44 seconds in the average waiting time.

CONCLUSIONS

The patients' waiting times and the number of patients waiting to receive services in both shifts could be reduced by using multitasking persons and reallocating them to the time-consuming stage of filling prescriptions, using queuing theory and simulation techniques.

Reducing outpatient waiting time: a simulation modeling approach

Objectives

The objective of this study was to provide a model for reducing outpatient waiting time by using simulation.

Materials and Methods

A simulation model was constructed by using the data of arrival time, service time and flow of 357 patients referred to orthopedic clinic of a general teaching hospital in Tehran. The simulation model was validated before constructing different scenarios.

Results

In this study 10 scenarios were presented for reducing outpatient waiting time. Patients waiting time was divided into three levels regarding their physicians. These waiting times for all scenarios were computed by simulation model. According to the final scores the 9th scenario was selected as the best way for reducing outpatient's waiting time.

Conclusions

Using the simulation as a decision making tool helps us to decide how we can reduce outpatient's waiting time. Comparison of outputs of this scenario and the based- case scenario in simulation model shows that combining physician's work time changing with patient's admission time changing (scenario 9) would reduce patient waiting time about 73.09%. Due to dynamic and complex nature of healthcare systems, the application of simulation for the planning, modeling and analysis of these systems has lagged behind traditional manufacturing practices. Rapid growth in health care system expenditures, technology and competition has increased the complexity of health care systems. Simulation is a useful tool for decision making in complex and probable systems.

A generic discrete-event simulation model for outpatient clinics in a large public hospital

The orthopedic outpatient department (OPD) ward in a large Thai public hospital is modeled using Discrete-Event Stochastic (DES) simulation. Key Performance Indicators (KPIs) are used to measure effects across various clinical operations during different shifts throughout the day. By considering various KPIs such as wait times to see doctors, percentage of patients who can see a doctor within a target time frame, and the time that the last patient completes their doctor consultation, bottlenecks are identified and resource-critical clinics can be prioritized. The simulation model quantifies the chronic, high patient congestion that is prevalent amongst Thai public hospitals with very high patient-to-doctor ratios. Our model can be applied across five different OPD wards by modifying the model parameters. Throughout this work, we show how DES models can be used as decision-support tools for hospital management.

An optimization based on simulation approach to the patient admission scheduling problem: diagnostic imaging department case study

The growing influx of patients in healthcare providers is the result of an aging population and emerging self-consciousness about health. In order to guarantee the welfare of all the healthcare stakeholders, it is mandatory to implement methodologies that optimize the healthcare providers' efficiency while increasing patient throughput and reducing patient's total waiting time. This paper presents a case study of a conventional radiology workflow analysis in a Portuguese healthcare provider. Modeling tools were applied to define the existing workflow. Re-engineered workflows were analyzed using the developed simulation tool. The integration of modeling and simulation tools allowed the identification of system bottlenecks. The new workflow of an imaging department entails a reduction of 41 % of the total completion time.

Use of hospital appointment registration systems in China: a survey study

BACKGROUND

Hospitals have expressed no knowledge of patients' opinions regarding diversified appointment registration systems, despite efforts to develop novel appointment registration systems that assist patients and increase hospital efficiency. Therefore, the aim of this study was to investigate the use of diversified appointment registration systems and explore the factors influencing patients' registration system choices.

METHODS

A survey study using a questionnaire was conducted in West China Hospital in February 2012. Outpatients were randomly selected from different hospital departments and the questionnaire was distributed and collected on-site.

RESULTS

Data from 1,009 patients were available for analysis. Of these, 63.4% used appointment systems to register while others chose a traditional queuing method to register. 114 telephone (30.4%) and on-site (22.9%) appointments were made, whereas other systems were less used by patients. Between the non-appointment and appointment groups there were significant differences in gender, educational degree, and residence location (P < 0.05), but no significant difference in age (P > 0.05). While the clinical appointment system had the greatest number of appointment days (25.75), the bank's self-service terminal appointment had the least number of appointment days (5.05). Leaflets sent from the hospital (50.70%) and the recommendations of friends or families (40.77%) were the two main ways of knowing about the appointment registration systems. With the exception of those who felt no need to make an appointment (30.12%), not having the capability to use the appointment systems (24.10%) and the lack of a registered health card (34.53%) were the two main reasons for not using appointment registration systems.

CONCLUSIONS

Convenience was a major motivation for patients' use of appointment registration systems. Personal knowledge and capability were the two important factors that influenced patients' appointment system choices. Hospitals must improve the design and promotion of appointment registration systems to better facilitate their use.

Hourly-block and standard patient scheduling systems at two private hospitals in Alexandria

Introduction:

Patient appointment systems are of great importance for efficiently managing outpatient clinics as well as patient satisfaction as an indirect indicator for quality care rendered.

Purpose:

To describe the hourly block and standard sequential scheduling appointment systems at two different hospitals, as well as to assess the patients’ opinions regarding their waiting time in both systems.

Study settings:

The study was conducted at ENT (Ear, Nose, and Throat) clinics in two of the biggest and reputable private hospitals in Alexandria. Hospital A follows the standard appointment system and Hospital B follows the hourly block appointment system.

Study design:

A cross-sectional descriptive study was designed to compare the two settings.

Results:

For new cases, the mean time was longer for the standard system with regards to access time (12.2 ± 5.9) days, while the mean time was longer in the hourly block system with regards to punctuality, waiting time, and consultation time (28.5 ± 12.3, 27.5 ± 17.1, and 14.5 ± 9.0 minutes, respectively). For return cases, the mean time was longer for the standard system with regards to access and punctuality times (14.5 ± 6.1 days and 48.9 ± 27.0 minutes, respectively), while the highest mean times in the hourly block system were for waiting and consultation (19.4 ± 6.9 and 12.3 ± 3.9 minutes, respectively). Most of the patients in both systems preferred the standard appointment system to the hourly block system (73.3% for Hospital A and 55.0% for Hospital B).

Conclusion:

Every health care organization should know how to choose the most appropriate method of appointment system and how best to organize it to meet the needs of its patients. Patient scheduling is an important tool for efficient outpatient department management as well as rationally operating outpatient resources and critical areas like physician productivity, patient satisfaction, and practice profits.

Capacity of clinical pathways--a strategic multi-level evaluation tool

In this paper we strategically evaluate the efficiency of clinical pathways and their complex interdependencies with respect to joint resource usage and patient throughput. We propose a discrete-event simulation approach that allows for the simultaneous evaluation of multiple clinical pathways and the inherent uncertainty (resource, duration and arrival) that accompanies medical processes. Both the consultation suite and the surgery suite may be modeled and examined in detail by means of sensitivity or scenario analyses. Since each medical facility can somehow be represented as a combination of clinical pathways, i.e. they are conceptually similar, the simulation model is generic in nature. Next to the formulation of the model, we illustrate its applicability by means of a case study that was conducted in a Belgian hospital.

Personnel and patient scheduling in the high demanded hospital services: a case study in the physiotherapy service

High demand but limited staffs within some services of a hospital require a proper scheduling of staff and patients. In this study, a hierarchical mathematical model is proposed to generate weekly staff scheduling. Due to computational difficulty of this scheduling problem, the entire model is broken down into manageable three hierarchical stages: (1) selection of patients, (2) assignment of patients to the staff, (3) scheduling of patients throughout a day. The developed models were tested on the data collected in College of Medicine Research Hospital at Cukurova University using GAMS and MPL optimization packages. From the results of the case study, the presented hierarchical model provided a schedule that ensures to maximize the number of selected patients, to balance the workload of physiotherapist, and to minimize waiting time of patients in their treatment day.

Mobile information and communication in the hospital outpatient service

OBJECTIVES

Most healthcare providers provide mobile service for their medical staff; however, few healthcare providers provide mobile service as part of their outpatient service. The mobile outpatient service system (MOSS) focuses on illness treatment, illness prevention and patient relation management for outpatient service users. Initiated in a local hospital in Taiwan, the MOSS pilot project was developed to improve outpatient service quality and pursue higher patient safety.

METHOD

This study focuses on the development of the MOSS. The workflow, architecture and target users of the MOSS are delineated. In addition, there were two surveys conducted as part of this study. After a focus group of medical staff identified areas in which outpatient services might be improved by the MOSS, the first survey was administered to outpatients to confirm the focus group's intuitions. The second administration of the survey explored outpatient satisfaction after they used the MOSS service.

RESULTS

With regard to outpatient attitudes, about 93% of participants agreed that the mobile outpatient service improved outpatient service quality. In the area of outpatient satisfaction, about 89% of participants indicated they were satisfied with the mobile outpatient service.

DISCUSSION/CONCLUSION

Supported by our study finding, we propose that more diverse mobile outpatient services can be provided in the future.