scholarly journals Toward Implementing Patient Flow in a Cancer Treatment Center to Reduce Patient Waiting Time and Improve Efficiency

2017 ◽  
Vol 13 (6) ◽  
pp. e530-e537 ◽  
Author(s):  
Samuel Suss ◽  
Nadia Bhuiyan ◽  
Kudret Demirli ◽  
Gerald Batist
Keyword(s):  
Complex Systems ◽  
Cancer Treatment ◽  
Patient Flow ◽  
Waiting Times ◽  
Value Added ◽  
Treatment Center ◽  
Quality Patient Care ◽  
Metropolitan Hospital ◽  
Patient Waiting Time ◽  
Patient Waiting

Outpatient cancer treatment centers can be considered as complex systems in which several types of medical professionals and administrative staff must coordinate their work to achieve the overall goals of providing quality patient care within budgetary constraints. In this article, we use analytical methods that have been successfully employed for other complex systems to show how a clinic can simultaneously reduce patient waiting times and non-value added staff work in a process that has a series of steps, more than one of which involves a scarce resource. The article describes the system model and the key elements in the operation that lead to staff rework and patient queuing. We propose solutions to the problems and provide a framework to evaluate clinic performance. At the time of this report, the proposals are in the process of implementation at a cancer treatment clinic in a major metropolitan hospital in Montreal, Canada.

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.

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 Impact of value added services on patient waiting time at the ambulatory pharmacy Queen Elizabeth Hospital

2017 ◽  
Vol 15 (1) ◽  
pp. 846-846 ◽  
Author(s):  
Benjamin C. Loh ◽  
Kheng F. Wah ◽  
Carolyn A. Teo ◽  
Nadia M. Khairuddin ◽  
Fairenna B. Fairuz ◽  
...  
Keyword(s):  
Waiting Time ◽  
Value Added ◽  
Queen Elizabeth Hospital ◽  
Patient Waiting Time ◽  
Patient Waiting

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.

scholarly journals Experience and Impact of a Locally-Based Peer, Volunteer Cancer Support Programme in Hospital Melaka, Melaka Malaysia

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 113s-113s
Author(s):  
M. Chua ◽  
V. Silvathorai ◽  
M. Muniasamy ◽  
H.S. Mohd Hashim ◽  
C. Lim ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Treatment ◽  
Cancer Patients ◽  
Waiting Times ◽  
Drop Out ◽  
Support Program ◽  
Care Process ◽  
Treatment Center ◽  
Breast Cancer Patients ◽  
Cancer Support

Background: Melaka is a small southern state in Peninsular Malaysia. On average, the state has an annual incidence of 200 odd breast cancer patients, largely treated out of its public, subsidized, single tertiary treatment center of Hospital Melaka. Hospital Melaka is an 800-bedded hospital with multiple specialties including surgery and radiology. Though the hospital does not have a dedicated oncology department, cancer treatment is carried out via phone consultations and visiting oncologists as well as a team of on-site nursing staff who are trained to initiate and monitor treatment. Feedback from Hospital Melaka staff highlighted that there was a drop-out rate of about 30% of patients from the treatment journey. Qualitative interviews with different stakeholders including patient revealed that the drop-out may be driven by factors such as: i) fear of surgery, ii) fear of chemotherapy, iii) fear of disfigurement, iv) loss of spouse v) emotional distress and shock; and vi) delay in waiting times for different levels of diagnostics and treatment. Aim: The aim of the initiative was to reduce the rate of patients who defaulted out from the cancer treatment journey via a three-pronged approach: a) improving understanding about cancer and treatment by patients and family members; b) integrating peer-support into the clinical treatment pathway at the hospital and reduction of waiting times; and c) maintaining a continuous interaction with the patient throughout the treatment journey. Methods: The inception and deployment of a locally-based peer, volunteer support program for breast cancer patients and families as part of the formal cancer treatment process in Hospital Melaka. Volunteers were consisted of a trained mix of cancer survivors, current and retired healthcare practitioners and provided information pertaining to treatment and care aspects of breast cancer as well as emotional support and follow-up of patients via phone or in person to ensure compliance to treatment. In this study, we engaged with various stakeholders including hospital management and clinicians. Then, support group's services were formalized into the care pathway for all patients with breast cancer; with both volunteers able to send and receive patient referrals. Results: Statistically significant reductions in patient delays in decision-making to seek treatment as well as a significant decrease of 12.5% in the number of defaulters. Conclusion: A support program built with support from all stakeholders and run by volunteers and embedded within the formal care process acts as a catalyst to enhance both service delivery as well as keeping patients engaged on the cancer care journey.

Transient Modeling in Simulation of Hospital Operations for Emergency Response

2006 ◽  
Vol 21 (4) ◽  
pp. 223-236 ◽  
Author(s):  
Jomon Aliyas Paul ◽  
Santhosh K. George ◽  
Pengfei Yi ◽  
Li Lin
Keyword(s):  
Waiting Times ◽  
Exponential Model ◽  
Hospital Capacity ◽  
Modeling Approach ◽  
System A ◽  
Hospital Operations ◽  
Transient Modeling ◽  
Patient Waiting Time ◽  
The Impact ◽  
Patient Waiting

AbstractRapid estimates of hospital capacity after an event that may cause a disaster can assist disaster-relief efforts. Due to the dynamics of hospitals, following such an event, it is necessary to accurately model the behavior of the system. A transient modeling approach using simulation and exponential functions is presented, along with its applications in an earthquake situation. The parameters of the exponential model are regressed using outputs from designed simulation experiments. The developed model is capable of representing transient, patient waiting times during a disaster. Most importantly, the modeling approach allows real-time capacity estimation of hospitals of various sizes and capabilities. Further, this research is an analysis of the effects of priority-based routing of patients within the hospital and the effects on patient waiting times determined using various patient mixes. The model guides the patients based on the severity of injuries and queues the patients requiring critical care depending on their remaining survivability time. The model also accounts the impact of prehospital transport time on patient waiting time.

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.

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