Simulation Model of a Multi-Hospital Critical Care Network

We develop a discrete event simulation model for a network of eight major intensive care units (ICUs) in British Columbia, Canada. The model also contains high acuity units (HAUs) that provide critical care to patients that cannot be cared for in a general medical ward, but do not require the full spectrum of care available in an ICU. We model patient flow within the ICU and HAU for each of the hospitals, as well as patient transfers to address ICU capacity. Included in the model is early discharge from ICU to HAU, sometimes called 'bumping', when the ICU is full, as well as ICU overflow beds. The simulation model, which is calibrated using the British Columbia Critical Care Database, will be used to support planning for critical care capacity under endemic and seasonal COVID-19. © 2022 IEEE.

Two-Stage Multi-Objective Stochastic Model on Patient Transfer and Relief Distribution in Lockdown Area of COVID-19.

The outbreak of an epidemic disease may cause a large number of infections and a slightly higher death rate. In response to epidemic disease, both patient transfer and relief distribution are significant to reduce corresponding damage. This study proposes a two-stage multi-objective stochastic model (TMS-PTRD) considering pre-pandemic preparedness measures and post-pandemic relief operations. The proposed model considers the following four objectives: the total number of untreated infected patients, the total transfer time, the overall cost, and the equity distribution of relief supplies. Before an outbreak, the locations of temporary relief distribution centers (TRDCs) and the inventory levels of established TRDCs should be determined. After an outbreak, the locations of temporary hospitals (THs), the locations of designated hospitals (DHs), the transfer plans for patients, and the relief distribution should be determined. To solve the TMS-PTRD model, we address an improved preference-inspired co-evolutionary algorithm named the PICEA-g-AKNN algorithm, which is embedded with a novel similarity distance and three different tailored evolutionary strategies. A real-world case study of Hunan of China and 18 test instances are randomly generated to evaluate the TMS-PTRD model. The finding shows that the PICEA-g-AKNN algorithm is better than some most widely used multi-objective algorithms.

Level-loading a health system by transferring emergency department patients to a community hospital: Prospective cohort study.

BACKGROUND: Emergency department boarding and crowding lead to worse patient outcomes and patient satisfaction. OBJECTIVE: We describe the implementation of a program to transfer patients requiring medical admission from an academic emergency department to a community hospital's medical floor and analyze its effects on patient outcomes. METHODS: A prospective cohort study was performed. Data was collected on patient flow through the transfer program. Patient characteristics, boarding time in the emergency department, and hospital-based outcome measures were compared between patients in the transfer program who were successfully transferred to the community hospital and patients who were admitted to the academic medical center. RESULTS: 79 patients were successfully transferred to the community hospital between November 23, 2020 and August 5, 2021, resulting in 279 bed days in the community hospital. Successfully transferred patients experienced a statistically shorter ED boarding time (5.7 vs. 10.9 h, p < 0.0001), ED length of stay (10.5 vs 16.1 h, p < 0.0001), and hospital length of stay (3.5 vs 5.7 days, p < 0.0001) compared to patients initially referred to the transfer program who were admitted to the academic medical center. There were no reported adverse events during transfer, upgrades to the ICU within 24 h of admission, or inpatient deaths for patients who were transferred. CONCLUSION: We implemented an academic emergency department to partner community hospital transfer program that safely level-loads medical patients in a healthcare system.

Key Care Provision Aspects That Affect Care Transition in the Long-Term Care Systems: Preliminary Review Findings.

The aim of this brief report is to present the protocol and preliminary findings of a systematic review on key aspects of care provision that affect care transition of older adults 60+ within the long-term care systems. This brief report describes and classifies the relevant literature found in the review with the purpose to provide a base for further full systematic reviews, and to outlines a model of organizational and financing aspects that affect care transition. Our search was conducted in MEDLINE, Embase and CINAHL on 2 March 2020, before the COVID-19 pandemic. The protocol was registered at the International Prospective Register of Systematic Reviews (number: CRD42020162566). Ultimately, 229 full-text records were found eligible for further deliberation. We observed an increase in the number of publications on organizational and financial aspects of care transition since 2005. Majority of publications came from the United States, United Kingdom and Australia. In total, 213 (92%) publications discussed organizational aspects and only 16 (8%) publications were related to financial aspects. Records on organizational aspects were grouped into the following themes: communication among involved professional groups, coordination of resources, transfer of information and care responsibility of the patient, training and education of staff, e-health, education and involvement of the patient and family, social care, and opinion of patients. Publications on financial aspects were grouped into provider payment mechanisms, incentives and penalties. Overall, our search pointed out various care provision aspects being studied in the literature, which can be explored in detail in subsequent full systematic reviews focused on given aspects. We also present a model based on our preliminary findings, which enables us to better understand what kind of provision aspects affect care transition. This model can be tested and validated in subsequent research. Understating factors that affect care transition is crucial to improve the quality of transitions and ultimately the outcomes for the patients.

Improving Patient Safety in General Hospitals Using Structured Handoffs: Outcomes From a National Project.

Background: Promoting quality and patient safety is one of the health policy pillars of Israel's Ministry of Health. Communication among healthcare professionals is of utmost importance and can be improved using a standardized, well-known handoff tool such as the Introduction, Situation, Background, Assessment, and Recommendations (ISBAR). This study aims to present implementation process and participants' satisfaction of a national project that used a standardized tool for team communication. Methods: This national intervention project included process implementation teams from 17 Israeli general hospitals evaluating the ISBAR implementation process for transferring patients from intensive care units to medical/surgical wards. The project, conducted between January 2017 and March 2018, used Fischer's test and logistic regression. The project evaluation was based on the participants' assessment of and satisfaction with the handoff process. Results: Eighty-seven process implementers completed the questionnaire. A statistically significant increase in satisfaction scores in terms of four variables (p < 0.001) was observed following the implementation of the project. Nurses reported higher satisfaction at the end of the process (0.036). Participants who perceived less missing information during handoffs were more satisfied with the process of information flow between wards (84.9%) than those who perceived more missing information (15.6%). Participants who responded that there was no need to improve information flow were more satisfied with the project information flow (95.6%) compared to the group which responded that it was necessary to improve information flow (58.2%). Three out of four variables predicted satisfaction with the process. Being a nurse also predicted satisfaction with information flow with a point estimate of 2.4. The C value of the total model was 0.87. Conclusions: Implementation of a safety project at a national level requires careful planning and the close involvement of the participating teams. A standardized instrument, a well-defined process, and external controls to monitor and manage the project are essential for success. Disparities found in the responses of nurses vs. physicians suggest the need for a different approach for each profession in planning and executing a similar project in the future.

Designing and Assessment of a Checklist for Transfer Status of Patient with COVID-19 Referred to Emergency Departments

Background: When transferring patients admitted to hospitals due to coronavirus disease 2019 (COVID-19), it is necessary to take appropriate measures to maintain the safety of patients and staff. The aim of this study was to design a checklist and evaluate in-hospital transfer status of patients with COVID-19 disease in emergency departments. Methods: In this cross-sectional study, a checklist for evaluation of in-hospital transfer of patients with COVID-19 in the emergency department was designed, and then assessed. The initial in-hospital transfer checklist was prepared based on data from guidelines and published articles regarding patients with COVID-19. Its validity was confirmed using face validity (by 20 emergency nurses). Then, the items were evaluated in terms of content validity in both quantitative and qualitative methods. To evaluate the content validity in a quantitative way, the content validity ratio (CVR) coefficient and the content validity index (CVI) were used. Waltz and Basel methods were used to determine CVR from the panel of experts and for CVI, respectively. Using the final checklist, the transfer status of patients with COVID-19 in three stages (before, during, and after transfer) by three samplers, from May to September 2020, in the emergency departments of selected hospitals in Qazvin City, Iran. Findings: In this study, the modes of transmission of 167 patients during 501 observations were investigated. Errors occurred in 50.9% of transfers, especially during transfer (32.9%), the most important cases of which included reduction of arterial blood oxygen saturation, decrease and increase in blood pressure, and incompliance with transfer protocols including non-disinfection of transmission routes (73.7%), lack of hand hygiene (74.6%), and non-replacement of personal protective equipment (60.5%). Conclusion: The results of the study showed that the most accidents were reduction of arterial blood oxygen saturation and hypotension, respectively, which occurred in terms of time, mainly during patient transfer. © 2021 Isfahan University of Medical Sciences(IUMS). All rights reserved.

An Edge Based Multi-Agent Model for Improving Hospital Bed Management

Today, and due to the population growth, the healthcare field recognizes many difficulties and challenges in many countries, especially in the underdeveloped ones. The spread of COVID-19 has shown these difficulties such as the lack of equipment and the failing of patient admission process. Therefore, healthcare systems require quick, newer and more sophisticated solutions that match the speed of technology and the citizens' aspirations. In this context, we propose in this paper a model for improving and helping hospital managers to orchestrate the patient admission process. The proposed model deals with the hospital bed management in order to ensure a quick patient transfer to the nearest and the most appropriate hospital. The proposed model is based on the coupling of multi-agent an edge computing system. Multi-agent systems represent a powerful choice to develop complex, distributed, dynamic and interactive systems, which represent typically our case. In addition, edge computing ensures a real-time collection of data about the bed's availability in the neighboring hospitals in order to transfer the patient to the adequate one as quickly as possible. © 2021 IEEE.

[The disaster task force medical officer as a pivotal decision maker in the superordinate pandemic hospital capacity management : A field report covering the initial COVID-19 surge in a Bavarian district]. / Der Ärztliche Leiter Führungsgruppe Katastrophenschutz als zentrale Entscheidungsinstanz bei der Steuerung regionaler Krankenhauskapazitäten in der Pandemie : Ein Erfahrungsbericht zur ersten Welle der COVID-19-Pandemie in einem bayerischen Regierungsbezirk.

BACKGROUND AND OBJECTIVE: During the initial phase of the COVID-19 pandemic the government of the state of Bavaria, Germany, declared a state of emergency for its entire territory for the first time in history. Some areas in eastern Bavaria were among the most severely affected communities in Germany, prompting authorities and hospitals to build up capacities for a surge of COVID-19 patients. In some areas, intensive care unit (ICU) capacities were heavily engaged, which occasionally made a redistribution of patients necessary. MATERIAL AND METHODS: For managing COVID-19-related hospital capacities and patient allocation, crisis management squads in Bavaria were expanded by disaster task force medical officers ("Ärztlicher Leiter Führungsgruppe Katastrophenschutz" [MO]) with substantial executive authority. The authors report their experiences as MO concerning the superordinate patient allocation management in the district of Upper Palatinate (Oberpfalz) in eastern Bavaria. RESULTS: By abandoning routine patient care and building up additional ICU resources, surge capacity for the treatment of COVID-19 patients was generated in hospitals. In parts of the Oberpfalz, ICU capacities were almost entirely occupied by patients with corona virus infections, making reallocation to other hospitals within the district and beyond necessary. The MO managed patient pathways in an escalating manner by defining local (within the region of responsibility of a single MO), regional (within the district), and cross-regional (over district borders) reallocation lanes, as needed. When regional or cross-regional reallocation lanes had to be established, an additional management level located at the district government was involved. Within the determined reallocation lanes, emitting and receiving hospitals mutually agreed on any patient transfer without explicitly involving the MO, thereby maintaining the established interhospital routine transfer procedures. The number of patients and available treatment resources at each hospital were monitored with the help of a web-based treatment capacity registry. If indicated, reallocation lanes were dynamically revised according to the present situation. To oppose further virus spreading in nursing homes, the state government prohibited patient allocation to these facilities, which led to considerably longer hospital length of stay of convalescent elderly and/or dependent patients. In parallel to the flattening of the COVID-19 incidence curve, routine hospital patient care could be re-established in a stepwise manner. CONCLUSION: Patient allocation during the state of emergency by the MO sought to keep up routine interhospital reallocation procedures as much as possible, thereby reducing management time and effort. Occasionally, difficulties were observed during patient allocations crossing district borders, if other MO followed different management principles. The nursing home blockade and conflicting financial interests of hospitals posed challenges to the work of the disaster task force medical officers.

Factors impacting hospital avoidance program utilisation in the care of acutely unwell residential aged care facility residents.

BACKGROUND: An existing hospital avoidance program, the Aged Care Rapid Response Team (ARRT), rapidly delivers geriatric outreach services to acutely unwell or older people with declining health at risk of hospitalisation. The aim of the current study was to explore health professionals' perspectives on the factors impacting ARRT utilisation in the care of acutely unwell residential aged care facility residents. METHODS: Semi-structured interviews were conducted with two Geriatricians, two ARRT Clinical Nurse Consultants, an ED-based Clinical Nurse Specialist, and an Extended Care Paramedic. Interview questions elicited views on key factors regarding care decisions and care transitions for acutely unwell residential aged care facility residents. Thematic analysis was undertaken to identify themes and sub-themes from interviews. RESULTS: Analysis of interviews identified five overarching themes affecting ARRT utilisation in the care of acutely unwell residents: (1) resident care needs; (2) family factors; (3) enabling factors; (4) barriers; and (5) adaptability and responsiveness to the COVID-19 pandemic. CONCLUSION: Various factors impact on hospital avoidance program utilisation in the care of acutely unwell older aged care facility residents. This information provides additional context to existing quantitative evaluations of hospital avoidance programs, as well as informing the design of future hospital avoidance programs.