scholarly journals Patient flow analysis in a children’s clinic

2021 ◽  
Vol 2 (3) ◽  
pp. 412-417
Author(s):  
S. Assetzadeh
Keyword(s):  
Waiting Time ◽  
Patient Flow ◽  
Waiting Times ◽  
Flow Analysis ◽  
Outpatient Department ◽  
Paediatric Outpatient

Patient flow analysis was used to assess the waiting time of patients referred to a large paediatric outpatient department, and also the lengths of the consultations of the paediatricians and interns. The average waiting times to see the paediatricians and interns were 77 minutes and 7.8 minutes, respectively. The average lengths of consultation for the paediatricians and interns were 3.4 minutes, and 7.7 minutes, respectively

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 Review on Queueing Problem in Healthcare

2018 ◽  
Vol 7 (4.30) ◽  
pp. 304
Author(s):  
Hajar Ariff ◽  
M Ghazali Kamardan ◽  
Suliadi Sufahani ◽  
Maselan Ali
Keyword(s):  
Emergency Department ◽  
Healthcare System ◽  
Waiting Time ◽  
Patient Flow ◽  
Outpatient Department ◽  
Scheduling Theory ◽  
Appointment System

This article shows the application of queueing, simulation and scheduling used in the field of healthcare. A summary of queueing, simulation and scheduling theory used in waiting time, appointment system and patient flow are summarised in this article. Different departments in the healthcare system are also considered in this article such as emergency department, outpatient department and the pharmacy. The aim is to provide the reader a general background into queueing, simulation and scheduling in the healthcare.

scholarly journals How does clinical space utilisation impact patient flow?

2019 ◽  
Vol 8 (3) ◽  
pp. e000542 ◽  
Author(s):  
Alexandra von Guionneau ◽  
Charlotte M Burford
Keyword(s):  
Quality Improvement ◽  
Waiting Time ◽  
Primary Outcome ◽  
Patient Flow ◽  
Waiting Times ◽  
Wait Time ◽  
Limiting Factor ◽  
Electronic Systems ◽  
Improvement Project ◽  
Medical Wards

BackgroundLong waiting times in accident and emergency (A&E) departments remain one of the largest barriers to the timely assessment of critically unwell patients. In order to reduce the burden on A&Es, some trusts have introduced ambulatory care areas (ACAs) which provide acute assessment for general practitioner referrals. However, ACAs are often based on already busy acute medical wards and the availability of clinical space for clerking patients means that these patients often face long waiting times too. A cheap and sustainable method to reducing waiting times is to evaluate current space utilisation with the view to making use of underutilised workspace. The aim of this quality improvement project was to improve accessibility to pre-existing clinical spaces, and in doing so, reduce waiting times in acute admissions.MethodsData were collected retrospectively from electronic systems and used to establish a baseline wait time from arrival to having blood taken (primary outcome). Quality improvement methods were used to identify potential implementations to reduce waiting time, by increasing access to clinical space, with serial measurements of the primary outcome being used to monitor change.ResultsData were collected over 54 consecutive days. The median wait time increased by 55 min during the project period. However, this difference in waiting time was not deemed significant between the three PDSA cycles (p=0.419, p=0.270 and p=0.350, Mann-Whitney U). Run chart analysis confirmed no significant changes occurred.ConclusionIn acute services, one limiting factor to seeing patients quickly is room availability. Quality improvement projects, such as this, should consider facilitating better use of available space and creating new clinical workspaces. This offers the possibility of reducing waiting times for both staff and patients alike. We recommend future projects focus efforts on integration of their interventions to generate significant improvements.

scholarly journals Reducing Waiting Time in the General Pediatric Clinic at Al Wakra Hospital, Qatar

2022 ◽  
Vol 5 (1) ◽  
pp. 01-10
Author(s):  
Sara Kazkaz ◽  
Ghadeer Mustafa ◽  
Almunzer Zakaria ◽  
Muna Atrash ◽  
Ayman Tardi ◽  
...  
Keyword(s):  
Public Health ◽  
Quality Improvement ◽  
Waiting Time ◽  
Pediatric Population ◽  
Waiting Times ◽  
Outpatient Department ◽  
Predictive Tool ◽  
Improvement Project ◽  
Average Waiting Time ◽  
Pediatric Clinic

Background: Waiting times for clinic appointments constitute a key indicator of an outpatient department performance for access to care and patient satisfaction. This is particularly relevant for pediatric population. The Ministry of Public Health in Qatar set a waiting time of 28 days for patients to get new appointment in General Outpatient Department (GOPD). The current average waiting time to get a new appointment in the general pediatric clinic (GPC) at AWH is 57 days. Aim: Decrease the average waiting time to get a new clinic appointment from 57 days to 28 days by the end of December 2018, and to meet the national targets set by the Ministry of Public Health. Methodology: This is a Quality Improvement (QI) project using the Model for Improvement (MFI). The MFI framework is designed to support organizations answering fundamental questions before agreeing on drivers for change. The implementation of change was be facilitated by the Plan-Do-Study-Act (PDSA) cycles methodology. The QI project team performed a root cause analysis using the Ishikawa diagram and identified the key contributing factors to the long waiting times to get a new appointment. Twenty-seven PDSA cycle ramps were designed with support of predictive tool to test innovative changes in current operational processes in an attempt to improve waiting time in the general pediatric clinic at Al Wakra Hospital. Results: The monthly average number of referrals for GPC increased by 200% between the pre and post implementation periods. The average triage waiting time improved from 6 to 2.6 days in 2018 and the average become 1 day in 2019. Post-implementation the average waiting time for patients to get new appointment improved from 57 days to 28 days in 2018 and the average waiting time improved to 16 days in 2019. Conclusion: The quality improvement project for the AWH general pediatric clinic demonstrates significant improvement in waiting times for new appointments, the recommendation for the hospital leadership would be to rollout the improvement methodology to other clinics that suffer from similar challenges.

Are we able to predict who needs a bed the most?

2018 ◽  
Vol 17 (3) ◽  
pp. 120-120
Author(s):  
MNT (Marjolein) Kremers ◽  
◽  
Prabath WB Nanayakkara ◽  
Keyword(s):  
Length Of Stay ◽  
The Netherlands ◽  
Hospital Admission ◽  
Acute Care ◽  
Risk Score ◽  
Waiting Time ◽  
Patient Flow ◽  
Waiting Times ◽  
Case Mix ◽  
Medical Patients

In recent years we indeed have witnessed an increasing demand on healthcare services coupled with spiraling healthcare costs forcing us towards identifying factors and interventions leading to greater healthcare efficiency. The case mix of our ED patients is changing with an increase in the number of the elderly needing acute (hospital) care, often suffering from multiple comorbidities leading to simple problems becoming easily complex and demanding admission. Partly due to this changing case mix, acute bed capacity is under serious pressure leading to ED stagnation and increased waiting times internationally. When the ED is at its capacity, acute physicians have to make choices how to divide the few available beds. Are we able to predict who needs a bed the most and make justified decisions? Which patient can wait at the ED before admission and which ones can’t? The study of Byrne et al. in this issue focused on the association between ED waiting times and clinical outcomes in Ireland, measured by 30 days mortality, using patient data of admitted acute medical patients collected from 2002 until 2017. High Risk Score patients with a longer waiting time at the ED, appear to have an increased risk on mortality. It is therefore necessary to identify these patients early and prioritize their hospital admission. However, to our knowledge, the used risk score isn’t implemented in daily practice. In 2012 the National Early Warning Score (NEWS) has been broadly implemented and it would be of interest to know whether the used retrospective Risk Score using laboratory data accord to the NEWS. Curiously, in this study, patients in all three MTS urgent categories with <4 hours waiting time, have a higher risk on mortality than patients experiencing a longer waiting time. What’s the cause of this effect? Are patients so severely ill that urgent treatment and admission can’t change the adverse outcome? Or is it possible that all three urgent MTS categories identify patients who are sicker with a higher chance of dying? Intriguingly, in Ireland the mortality amongst admitted acute medical patients decreased since 2002 by 1.3%. An important question remained unanswered by Byrne et al: why has this mortality decreased? Has the severity of the diseases by urgently admitted patients diminished? Has the treatment for acute medical patients been improved? Don’t severely ill patients come to the ED anymore, due to proper advanced care planning? In contrast to the decreased mortality, the median waiting times >6 hours have increased by 50%, from 10 to 15 hours. What caused this increase? What happened in the acute care in Ireland? Have other European countries experienced the same effect or can’t the Irish results not being extrapolated to other European acute care systems? For example, in the Netherlands, the total number of patients being seen at the ED has decreased and stabilised in the last years, although the number of acute medical patients, especially elderly, is increasing. During the last flu season patients we were faced with ED closures, long length of stay and overnight ED stays due to the lack of beds in-hospital. However, waiting hours >12 hours at the ED are rare in Dutch EDs. A key factor in constraining the patient flow to the ED is the well-functioning primary care system with adequate out of office hours care by GP-posts. When a GP post is placed at an ED, GPs treat 75% of the self-referred patient, which is safe and cost-effective. Due to this the ED`s can concentrate on the sick patients who need urgent care. Despite the decreased patient flow to the ED in the Netherlands, the organisation of the acute care has gained much attention of policy makers, media and health care professionals due to frequent ED closures and stagnation in some regions in the Netherlands. Recently, a prediction model for hospital admission in a mixed ED population has been established by using data directly available after triage, aiming to use for shortening the Length of Stay (LOS) at the ED. A computerised tool calculates admission probability for any patient at the time of triage by using age, triage category, arrival mode and main symptom. It demonstrates that different European countries are facing the same issues and are trying to optimize the acute care with some overlapping focus. We believe that at a time where the demand on acute care is increasing, it’s essential to pay attention to the organisation of acute care so that high-quality care is guaranteed and the available resources should be handled efficiently. Studies such as executed by Byrne et al. contribute to this topic and provide lessons which can be learned internationally. We need tools to identify sick patients who need properly care on time and acute physicians can play a central role in developing these tools.

scholarly journals A Multi-Faceted Strategy for Evidence Translation Reduces Healthcare Waiting Time: A Mixed Methods Study Using the RE-AIM Framework

2021 ◽  
Vol 2 ◽  
Author(s):  
Katherine E. Harding ◽  
Annie K. Lewis ◽  
David A. Snowdon ◽  
Bridie Kent ◽  
Nicholas F. Taylor
Keyword(s):  
Mixed Methods ◽  
Health Services ◽  
Waiting Time ◽  
Patient Flow ◽  
Supply And Demand ◽  
Waiting Times ◽  
Translation Strategy ◽  
Dissemination Of Research ◽  
Barriers To Implementation ◽  
Internal Database

Background: Waiting lists are often thought to be inevitable in healthcare, but strategies that address patient flow by reducing complexity, combining triage with initial management, and/or actively managing the relationship between supply and demand can work. One such model, Specific Timely Appointments for Triage (STAT), brings these elements together and has been found in multiple trials to reduce waiting times by 30–40%. The next challenge is to translate this knowledge into practice.Method: A multi-faceted knowledge translation strategy, including workshops, resources, dissemination of research findings and a community of practice (CoP) was implemented. A mixed methods evaluation of the strategy was conducted based on the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework, drawing on an internal database and a survey of workshop and CoP participants.Results: Demonstrating reach, at July 2020 an internal database held details of 342 clinicians and managers from 64 health services who had participated in the workshop program (n = 308) and/or elected to join an online CoP (n = 227). 40 of 69 (58%) respondents to a survey of this population reported they had adopted the model, with some providing data demonstrating that the STAT model had been efficacious in reducing waiting time. Perceived barriers to implementation included an overwhelming existing waiting list, an imbalance between supply and demand and lack of resources.Conclusion: There is high quality evidence from trials that STAT reduces waiting time. Using the RE-AIM framework, this evaluation of a translation strategy demonstrates uptake of evidence to reduce waiting time in health services.

scholarly journals Interhospital referral of colorectal cancer patients: a Dutch population-based study

2021 ◽  
Author(s):  
A. K. Warps ◽  
◽  
M. P. M. de Neree tot Babberich ◽  
E. Dekker ◽  
M. W. J. M. Wouters ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Patients ◽  
Waiting Time ◽  
Secondary Care ◽  
Advanced Disease ◽  
Waiting Times ◽  
Tertiary Care ◽  
Disease Stage ◽  
Colorectal Cancer Patients ◽  
Tertiary Care Hospitals

Abstract Purpose Interhospital referral is a consequence of centralization of complex oncological care but might negatively impact waiting time, a quality indicator in the Netherlands. This study aims to evaluate characteristics and waiting times of patients with primary colorectal cancer who are referred between hospitals. Methods Data were extracted from the Dutch ColoRectal Audit (2015-2019). Waiting time between first tumor-positive biopsy until first treatment was compared between subgroups stratified for referral status, disease stage, and type of hospital. Results In total, 46,561 patients were included. Patients treated for colon or rectal cancer in secondary care hospitals were referred in 12.2% and 14.7%, respectively. In tertiary care hospitals, corresponding referral rates were 43.8% and 66.4%. Referred patients in tertiary care hospitals were younger, but had a more advanced disease stage, and underwent more often multivisceral resection and simultaneous metastasectomy than non-referred patients in secondary care hospitals (p<0.001). Referred patients were more often treated within national quality standards for waiting time compared to non-referred patients (p<0.001). For referred patients, longer waiting times prior to MDT were observed compared to non-referred patients within each hospital type, although most time was spent post-MDT. Conclusion A large proportion of colorectal cancer patients that are treated in tertiary care hospitals are referred from another hospital but mostly treated within standards for waiting time. These patients are younger but often have a more advanced disease. This suggests that these patients are willing to travel more but also reflects successful centralization of complex oncological patients in the Netherlands.

scholarly journals E-Triage Systems for COVID-19 Outbreak: Review and Recommendations

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2845
Author(s):  
Fahd Alhaidari ◽  
Abdullah Almuhaideb ◽  
Shikah Alsunaidi ◽  
Nehad Ibrahim ◽  
Nida Aslam ◽  
...  
Keyword(s):  
Population Growth ◽  
Disease Severity ◽  
Waiting Time ◽  
Transmission Rate ◽  
Waiting Times ◽  
Triage System ◽  
Disease Symptoms ◽  
Comprehensive Review ◽  
Severity Levels ◽  
Growth And Aging

With population growth and aging, the emergence of new diseases and immunodeficiency, the demand for emergency departments (EDs) increases, making overcrowding in these departments a global problem. Due to the disease severity and transmission rate of COVID-19, it is necessary to provide an accurate and automated triage system to classify and isolate the suspected cases. Different triage methods for COVID-19 patients have been proposed as disease symptoms vary by country. Still, several problems with triage systems remain unresolved, most notably overcrowding in EDs, lengthy waiting times and difficulty adjusting static triage systems when the nature and symptoms of a disease changes. In this paper, we conduct a comprehensive review of general ED triage systems as well as COVID-19 triage systems. We identified important parameters that we recommend considering when designing an e-Triage (electronic triage) system for EDs, namely waiting time, simplicity, reliability, validity, scalability, and adaptability. Moreover, the study proposes a scoring-based e-Triage system for COVID-19 along with several recommended solutions to enhance the overall outcome of e-Triage systems during the outbreak. The recommended solutions aim to reduce overcrowding and overheads in EDs by remotely assessing patients’ conditions and identifying their severity levels.

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.

Principles of capacity management, applied in the mental health context

2018 ◽  
Vol 42 (4) ◽  
pp. 438
Author(s):  
Kathryn Zeitz ◽  
Darryl Watson
Keyword(s):  
Mental Health ◽  
Mental Health Problems ◽  
Average Length ◽  
Patient Flow ◽  
Waiting Times ◽  
Capacity Management ◽  
Mental Health Setting ◽  
Mental Health Consumer ◽  
Mental Health Consumers ◽  
Flow Improvement

Objective The aim of the paper was to describe a suite of capacity management principles that have been applied in the mental health setting that resulted in a significant reduction in time spent in two emergency departments (ED) and improved throughput. Methods The project consisted of a multifocal change approach over three phases that included: (1) the implementation of a suite of fundamental capacity management activities led by the service and clinical director; (2) a targeted Winter Demand Plan supported by McKinsey and Co.; and (3) a sustainability of change phase. Descriptive statistics was used to analyse the performance data that was collected through-out the project. Results This capacity management project has resulted in sustained patient flow improvement. There was a reduction in the average length of stay (LOS) in the ED for consumers with mental health presentations to the ED. At the commencement of the project, in July 2014, the average LOS was 20.5 h compared with 8.5 h in December 2015 post the sustainability phase. In July 2014, the percentage of consumers staying longer than 24 h was 26% (n = 112); in November and December 2015, this had reduced to 6% and 7 5% respectively (less than one consumer per day). Conclusion Improving patient flow is multifactorial. Increased attendances in public EDs by people with mental health problems and the lengthening boarding in the ED affect the overall ED throughput. Key strategies to improve mental health consumer flow need to focus on engagement, leadership, embedding fundamentals, managing and target setting. What is known about the topic? Improving patient flow in the acute sector is an emerging topic in the health literature in response to increasing pressures of access block in EDs. What does this paper add? This paper describes the application of a suite of patient flow improvement principles that were applied in the mental health setting that significantly reduced the waiting time for consumers in two EDs. What are the implications for practitioners? No single improvement will reduce access block in the ED for mental health consumers. Reductions in waiting times require a concerted, multifocal approach across all components of the acute mental health journey.

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