scholarly journals A challenge for healthcare system resilience after an earthquake: The crowdedness of a first-aid hospital by non-urgent patients

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249522
Author(s):  
You-Xuan Lin ◽  
Chi-Hao Lin ◽  
Chih-Hao Lin
Keyword(s):  
Healthcare System ◽  
Waiting Time ◽  
Emergency Care ◽  
Patient Flow ◽  
Discrete Event ◽  
Severe Case ◽  
First Aid ◽  
Response Measure ◽  
Preparedness Planning ◽  
The Impact

After a violent earthquake, the supply of medical services may fall short of the rising demand, leading to overcrowding in hospitals, and, consequently, a collapse in the healthcare system. This paper takes the emergency care system in Taiwan as the research context, where first-aid hospitals are ranked to three levels, advanced, intermediate, and general, and, currently, emphasizes on a general emergency responsibility hospital. Having limited capacity and capability, a general emergency responsibility hospital treats minor and moderate injuries, from which the majority of earthquake-induced casualties suffer. The purpose of this study is to analyze the impact of this group of earthquake-induced non-urgent patients on the performance of a hospital. A patient flow model was built to represent patients’ paths throughout emergency care. Based on the model, discrete event simulation was applied to simulate patients’ trajectories and states of a hospital under four seismic scenarios, where patient visits are 1.4, 1.6, 1.9, and 2.3 times the normal number. A healthcare performance index, Crowdedness Index (CI), is proposed to measure crowdedness on a daily basis, which is defined as the ratio of the average waiting time for treatment to the recommended maximal waiting time. Results of simulations rendered the establishment of empirical equations, describing the relation between the maximum CIs and the patient growth ratios. In the most severe case in this study, the maximum CI exceeds 92 and it takes 10 days to recover from the quality drop. This highlights the problem a general emergency responsibility hospital may encounter if no emergency response measure is implemented. Findings are provided pertaining to the predication of a recovery curve and the alarming level of patient increase, which are supportive information for preparedness planning as well as response measure formulation to improve resilience.

scholarly journals Rethinking preparedness planning in disaster emergency care: lessons from a beyond-surge-capacity event

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Sheuwen Chuang ◽  
David D. Woods ◽  
Morgan Reynolds ◽  
Hsien-Wei Ting ◽  
Asher Balkin ◽  
...  
Keyword(s):  
Emergency Care ◽  
Large Scale ◽  
Patient Flow ◽  
Surge Capacity ◽  
Preparedness Plan ◽  
Preparedness Planning ◽  
Wide Range ◽  
Care Systems ◽  
Hospital Readiness ◽  
Depth Interviews

Abstract Background Large-scale burn disasters can produce casualties that threaten medical care systems. This study proposes a new approach for developing hospital readiness and preparedness plan for these challenging beyond-surge-capacity events. Methods The Formosa Fun Coast Dust Explosion (FFCDE) was studied. Data collection consisted of in-depth interviews with clinicians from four initial receiving hospitals and their relevant hospital records. A detailed timeline of patient flow and emergency department (ED) workload changes of individual hospitals were examined to build the EDs' overload patterns. Data analysis of the multiple hospitals' responses involved chronological process-tracing analysis, synthesis, and comparison analysis in developing an integrated adaptations framework. Results A four-level ED overload pattern was constructed. It provided a synthesis of specifics on patient load changes and the process by which hospitals' surge capacity was overwhelmed over time. Correspondingly, an integrated 19 adaptations framework presenting holistic interrelations between adaptations was developed. Hospitals can utilize the overload patterns and overload metrics to design new scenarios with diverse demands for surge capacity. The framework can serve as an auxiliary tool for directive planning and cross-check to address the insufficiencies of preparedness plans. Conclusions The study examined a wide-range spectrum of emergency care responses to the FFCDE. It indicated that solely depending on policies or guidelines for preparedness plans did not contribute real readiness to MCIs. Hospitals can use the study's findings and proposal to rethink preparedness planning for the future beyond surge capacity events.

Design and comparison of scheduling strategy for teleconsultation

2021 ◽  
pp. 1-15
Author(s):  
Yan Qiao ◽  
Lun Ran ◽  
Jinlin Li ◽  
Yunkai Zhai
Keyword(s):  
Waiting Time ◽  
Operations Management ◽  
System Performance ◽  
Discrete Event ◽  
Arrival Rate ◽  
Disease Diagnosis ◽  
Scheduling Strategy ◽  
Static Strategy ◽  
Current Resource ◽  
The Impact

BACKGROUND: Telemedicine is playing an increasingly more important role in disease diagnosis and treatment. The market of telemedicine application is continuously promoted, thus bringing some issues on telemedicine operations management. OBJECTIVE: We aimed to compare the teleconsultation scheduling performance of newly designed proactive strategy and existing static strategy and explore the decision-making under different conditions. METHODS: We developed a discrete-event simulation model based on practical investigation to describe the existing static scheduling strategy of teleconsultation. The static strategy model was verified by comparing it with the historical data. Then a new proactive strategy was proposed, whose average waiting time, variance of waiting time and completed numbers were compared with the static strategy. RESULTS: The analysis indicated that the proactive strategy performed better than static under the current resource allocation. Furthermore, we explored the impact on the system of both strategies varying arrival rate and experts’ shift time. CONCLUSIONS: Under different shift times and arrival rates, the managers of telemedicine center should select different strategy. The experts’ shift time had a significant impact on all system performance indicators. Therefore, if managers wanted to improve the system performance to a greater extent, they needed to reduce the shift time as much as possible.

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.

Discrete event simulation modelling to evaluate the impact of a quality improvement initiative on patient flow in a paediatric emergency department

2020 ◽  
Vol 37 (4) ◽  
pp. 193-199 ◽  
Author(s):  
Kenneth W McKinley ◽  
John Babineau ◽  
Cindy G Roskind ◽  
Meridith Sonnett ◽  
Quynh Doan
Keyword(s):  
Quality Improvement ◽  
Discrete Event Simulation ◽  
Patient Flow ◽  
Discrete Event ◽  
Simulation Modelling ◽  
Quality Improvement Initiative ◽  
Event Simulation ◽  
Specific Protocol ◽  
Time Specific ◽  
The Impact

ObjectiveWe developed a discrete event simulation model to evaluate the impact on system flow of a quality improvement (QI) initiative that included a time-specific protocol to decrease the time to antibiotic delivery for children with cancer and central venous catheters who present to a paediatric ED with fever.MethodsThe model was based on prospective observations and retrospective review of ED processes during the maintenance phase of the QI initiative between January 2016 and June 2017 in a large, urban, academic children’s hospital in New York City, USA. We compared waiting time for full evaluation (WT) and length of stay (LOS) between a model with and a model without the protocol. We then gradually increased the proportion of patients receiving the protocol in the model and recorded changes in WT and LOS.ResultsWe validated model outputs against administrative data from 2016, with no statistically significant differences in average WT or LOS for any emergency severity index (ESI). There were no statistically significant differences in these flow metrics between the model with and the model without the protocol. By increasing the proportion of total patients receiving this protocol, from 0.2% to 1.3%, the WT increased by 2.8 min (95% CI: 0.6 to 5.0) and 7.6 min (95% CI: 2.0 to 13.2) for ESI 2 and ESI 3 patients, respectively. This represents a 14.0% increase in WT for ESI 3 patients.ConclusionsSimulation modelling facilitated the testing of system effects for a time-specific protocol implemented in a large, urban, academic paediatric ED, showing no significant impact on patient flow. The model suggests system resilience, demonstrating no detrimental effect on WT until there is a 7-fold increase in the proportion of patients receiving the protocol.

scholarly journals Simulation and Improvement of Patients’ Workflow in Heart Clinics during COVID-19 Pandemic Using Timed Coloured Petri Nets

2020 ◽  
Vol 17 (22) ◽  
pp. 8577
Author(s):  
Masoomeh Zeinalnezhad ◽  
Abdoulmohammad Gholamzadeh Chofreh ◽  
Feybi Ariani Goni ◽  
Jiří Jaromír Klemeš ◽  
Emelia Sari
Keyword(s):  
Petri Nets ◽  
Waiting Time ◽  
Patient Flow ◽  
Discrete Event ◽  
Healthcare Providers ◽  
Coloured Petri Nets ◽  
Event Simulation ◽  
Simulation Techniques ◽  
Patient Waiting Time ◽  
Multiple Challenges

The COVID-19 epidemic has spread across the world within months and creates multiple challenges for healthcare providers. Patients with cardiovascular disease represent a vulnerable population when suffering from COVID-19. Most hospitals have been facing difficulties in the treatment of COVID-19 patients, and there is a need to minimise patient flow time so that staff health is less endangered, and more patients can be treated. This article shows how to use simulation techniques to prepare hospitals for a virus outbreak. The initial simulation of the current processes of the heart clinic first identified the bottlenecks. It confirmed that the current workflow is not optimal for COVID-19 patients; therefore, to reduce waiting time, three optimisation scenarios are proposed. In the best situation, the discrete-event simulation of the second scenario led to a 62.3% reduction in patient waiting time. This is one of the few studies that show how hospitals can use workflow modelling using timed coloured Petri nets to manage healthcare systems in practice. This technique would be valuable in these challenging times as the health of staff, and other patients are at risk from the nosocomial transmission.

Prehospital Emergency Care and Medical Preparedness for the 2005 World Championship Games in Athletics in Helsinki

2007 ◽  
Vol 22 (4) ◽  
pp. 304-311 ◽  
Author(s):  
Tuomas Hiltunen ◽  
Markku Kuisma ◽  
Teuvo Määttä ◽  
Arto Tennilä ◽  
Tuomo Hari ◽  
...  
Keyword(s):  
Health Care ◽  
Healthcare System ◽  
Emergency Care ◽  
Patient Characteristics ◽  
First Aid ◽  
Prehospital Emergency Care ◽  
World Championship ◽  
Mass Gatherings ◽  
Institutional Review ◽  
Number Of Patients

AbstractIntroduction:International mass gatherings can cause great challenges to local healthcare system and emergency medical services (EMS). Traditionally, planning has been based on retrospective reports of previous events, but there still is a need for prospective studies in order to make the process more evidence-based. The aim of this study was to analyze the success of medical preparedness, ambulance patient characteristics, emergency care, and the use of pre-hospital resources during the 2005 World Championship Games in Athletics in Helsinki, Finland.Methods:The study was a prospective, observational study conducted within the Helsinki EMS. Data from all emergency calls at the sport venues and Games village between 05 and 14 August 2005 were collected. Data from the organizations responsible for the health care and first aid of spectators and accredited persons (e.g., athletes, coaches, the press, very important persons and personnel working in the Games area) also were collected. The Institutional Review Board of Helsinki University Central Hospital approved the study plan.Results:A total of 479,000 persons visited the Games. The ambulance call incidence at the Olympic Stadium was 0.50 per 10,000 people and 0.7 per 10,000 when the Games Village was included. The overall need for ambulance transportation to the emergency department was 0.52 per 10,000. No patients needed cardiopulmonary resuscitation or other immediate, life-saving procedures on-site. First aid was provided to 554 spectators (0.17per 10,000 people). The three medical organizations cared for 1,586 patients of which 25 (1.6%) were transported to a hospital by an ambulance. The number of patients needing transportation and the overall patient loadfor the healthcare system was well-anticipated. Accredited persons sought health care a total of 1,009 times.The number of patients treated was associated closely with the number of spectators (p = 0.05). The number of ambulance calls in the city increased 5.9 % as compared to the corresponding time period in the five previous years.Conclusions:The medical preparedness and resources for the Games proved to be sufficient. The EMS personnel were able to provide quality emergency care. This prospective study provided new, detailed data for the medical aspects of mass gatherings and confirmed many previous observations.

Evaluating intensive care unit admission and discharge policies using a discrete event simulation model

SIMULATION ◽  
2020 ◽  
Vol 96 (6) ◽  
pp. 501-518 ◽  
Author(s):  
Imran Hasan ◽  
Esmaeil Bahalkeh ◽  
Yuehwern Yih
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Discrete Event Simulation ◽  
Waiting Time ◽  
Discrete Event ◽  
Wait Time ◽  
Average Waiting Time ◽  
Event Simulation ◽  
The Impact ◽  
Patient Mix

The efficient utilization and management of a scarce resource such as the intensive care unit (ICU) is critical to the smooth functioning of a hospital. This study investigates the impact of a set of operational policies on ICU behavior and performance. Specifically, the implemented policies are (a) wait time thresholds on how long patients can wait for an ICU bed, (b) the time windows during which patient discharges and transfers take place, and (c) different patient mix combinations. The average waiting time of patients for ICU beds and the admission ratio, the ratio of admitted patients to total ICU bed requests, are the performance measures under consideration. Using discrete event simulation, followed by analysis of variance and post hoc tests (Tukey multiple comparison), it is shown that increasing discharge windows has a statistically significant impact on the total number of admissions and average patient wait times. Moreover, average waiting time increased when wait time thresholds increased, especially when the number of emergency surgeries in the mix increased. In addition, larger proportions of elective surgery patients in the patient mix population can lead to significantly reduced ICU performance.

scholarly journals The potential for digital patient symptom recording through symptom assessment applications to optimize patient flow and reduce waiting times in Urgent Care Centers: a simulation study

2020 ◽  
Author(s):  
Maryam Montazeri ◽  
Jan Multmeier ◽  
Claire Novorol ◽  
Shubhanan Upadhyay ◽  
Paul Wicks ◽  
...  
Keyword(s):  
Health Care ◽  
Waiting Time ◽  
Patient Flow ◽  
Care Center ◽  
Discrete Event ◽  
Symptom Assessment ◽  
Health Care Facilities ◽  
Urgent Care ◽  
History Taking ◽  
Digital History

AbstractBackgroundOvercrowding can negatively affect the performance of the health care facilities not only for patients in terms of delayed care delivery and increased health risk, but also for health care workers in terms of increased burden and stress. Sometimes overcrowding is a result duplicate activity such as history taking and recording of patients’ symptoms. In this case, using a digital symptom assessment application can prevent duplication of such activities and may decrease the crowding in health care facilities.ObjectiveWe sought to understand the effect of a digital symptom assessment app that facilitates the taking of patient clinical history to optimize patient flow. We hypothesized that waiting times and crowding in an urgent care center could be reduced through the introduction of a digital history taking tool, and that this would be more efficient than simply adding more staff.MethodsA discrete event approach was used to simulate patient flow in an urgent care center during a hypothetical 4-hour time window. The baseline case simulated a small center with 2 triage nurses, 2 doctors, 1 treatment/examination nurse and 1 discharge administrator in service. In addition to the base case, the center is simulated in 32 scenarios either with different number of staff or different assumption on time saved by the app. Target outcomes included average queue length, waiting time, idle time and utilization of staffResultsDiscrete event simulation found that a few minutes saved by a digital history taking app during triage could significantly increase efficiency. An estimated time-saving per patient of 2.5 minutes decreased average patient wait for triage by 26.17%; a 5 minutes time-saving would lead to a 54.88% reduction. Alternatively, adding an additional triage nurse was less efficient, as the additional staff were only required at the busiest times. While reduction in waiting time for triage was similar (approximately 50%) for either approach, adding a triage nurse reduced the median nurse utilization from 97% to 41%, while adding the tool resulted in median nurse utilization of 88%.ConclusionsDigital history taking could result in substantial reduction in patient waiting time for triage nurses, which is associated with reduced patient anxiety, staff anxiety and improved patient care. Patient history taking could be carried out in waiting room (via a check-in kiosk or portable tablet computer) or out at home. This simulation has the potential to impact service provision and approaches to digitalization at scale.

Guardianship in hospitals: a collaborative pilot project

2020 ◽  
Vol 44 (2) ◽  
pp. 322
Author(s):  
Rob Hoffman ◽  
Sally Costar ◽  
Tass Kostopoulos ◽  
Justine Little ◽  
Aaron Livingstone ◽  
...  
Keyword(s):  
Health Services ◽  
Healthcare System ◽  
Patient Flow ◽  
Pilot Project ◽  
Wait Times ◽  
Control Group ◽  
Pilot Program ◽  
Control Group Design ◽  
Healthcare Resources ◽  
The Impact

Objectives This paper describes the development, implementation and preliminary results of a collaborative pilot project aimed at reducing the time hospital-based patients with cognitive impairments spend waiting for the allocation of legally appointed Advocate Guardian decision makers from the Office of the Public Advocate (OPA). The aim of the study was to investigate the effect of increased availability of public advocate guardians on guardian allocation waits, patient discharge outcomes and healthcare system demand. Methods A multi-institutional pilot program created a dedicated hospital guardian team within OPA, funded by the health networks, to reduce the time to guardian allocation for patients within each network. A multisite, quasi-experimental historical control group design was used, with initial data collection over 12 months, followed by study of 12-month post-implementation cohorts. Results Under the pilot program, the time from guardianship order lodgement to guardian allocation decreased significantly from 46.5 to 22.9 days, halving the average time hospital-based patients spend waiting for a guardian (difference –23.55 days, two-sample t(154) = –6.575, P < 0.0001, 95% confidence interval [–30.65, –16.48].). Mean total length of stay decreased from 163.2 to 148.5 days. The estimated value of the reduction in allocation wait time was A$15473 per patient, or A$5 of resources released per A$1 spent on increased staffing. Conclusions Direction of a small amount of resources from health services to staff within OPA appears to have created much greater savings for the health services involved. The pilot program has reduced the period of time vulnerable patients spend waiting in hospital for a guardian. What is known about the topic? Guardianship resources are under increasing stress, with demand outstripping funding and hospital-based applicants deprioritised due to assumptions of lower risk, leading to extensive wait times for guardian allocation. What does this paper add? The paper quantifies the impact of greater guardianship resourcing on access to both guardianship and healthcare resources, highlighting benefits for vulnerable patient groups, healthcare system sustainability and access to both guardianship and healthcare resources for the broader community. What are the implications for clinicians? Improving patient flow through healthcare systems may involve allocating resources to services that are managed outside the healthcare system where ‘bottlenecks’, such as wait times for guardian allocation, have been identified.

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