BackgroundDuring the COVID-19 outbreak in May 2021, our hospital—designated as a specialized facility for severely infected patients—faced critical staff and resource shortages. The urgent need for efficient bed management to ensure timely admissions underscored the inefficiencies of the manual, phone-based allocation process, which averaged 454 seconds per query. Traditional IT solutions were not feasible due to time and cost constraints.ObjectiveThis study aims to design and implement a rapid, zero-cost Quick Isolation Bed Inquiry System that provides real-time bed information and enables timely admissions without requiring additional workforce or expense.MethodsWe conducted a 3-cycle pre-post quality improvement study guided by the Toyota business practice (TBP), an 8-step problem-solving framework. After clarifying the problem and constructing a value stream map, we identified bottlenecks. A user-centered solution was developed by leveraging an underutilized data export function in the hospital’s bed inquiry platform. Using Microsoft Excel Visual Basic for Applications, we automated the filtering and display of relevant bed information. The primary outcomes were process time and number of steps; secondary outcomes included staff time savings and system accuracy.ResultsThe baseline manual process required 25 steps and 454 seconds to complete a query. The new system reduced this to 3 steps and 12 seconds, representing a 97.4% gain in efficiency. Single-click execution generated 3 outputs (administrative PDF, large-screen display, and mobile version) in 4 seconds, with distribution to the hospital LINE group completed in 7 seconds. Reliability reached 100%, with continuous availability through virtual private network access. Development and debugging were completed within 3 days using only existing resources. Postpandemic, the system was adapted for general ward management with minimal modifications.ConclusionsApplying TBP enabled the rapid development of a user-centered, zero-cost bed management tool by repurposing existing digital assets. The intervention markedly improved efficiency, reliability, and usability without additional staffing or expenditure, providing a scalable model for agile health care systems operating under resource constraints. Future work will focus on deeper automation, such as application programming interface–based real-time updates, and on evaluating downstream impacts on patient flow and bed turnover.

Objective: to describe the implementation process of the Internal Regulation Center in a public university hospital and its interfaces in care and management processes. Methods: documentary, exploratory, and descriptive study carried out in a public teaching hospital in the north of the State of Paraná. Data collection took place between January and September 2020 in institutional documents. Results: The service was implemented in four stages following strategic actions. Stage 1 provided an insight into the interfaces of the bed management process. In stage 2, the strategies adopted in the implementation of bad management and their interfaces with the management and care sectors were elaborated. In stage 3, institutional performance indicators were monitored, and in stage 4, adjustments were made to the electronic monitoring system for hospital indicators. The biggest challenge faced was the training and acceptance of professionals from the multidisciplinary team in adhering to this new bed management model. Conclusions: The description of the implementation of the NIR in a public university hospital highlighted the importance of developing a strategic plan carried out prior to the implementation of the nucleus, as well as detailing all the actions to be adopted.

68. Estimation of ammonia flux with rice hull partial application for broiler house bedding management

Emergency departments (EDs) are frequently challenged by fluctuating patient volumes and resource constraints, leading to overcrowding and operational inefficiencies. This study presents a framework that combines design thinking and discrete event simulation (DES) to optimize ED processes and improve patient outcomes. By using both methods in conjunction with the design of experiments, the digital twin evaluates the effects of various resource configurations on key performance indicators, such as length of stay (LOS). The model highlights critical resource bottlenecks and explores alternative scenarios to improve ED performance. A case study demonstrates that targeted adjustments in nurse staffing and bed management significantly improve operational productivity and reduce patient LOS. The proposed approach provides hospital administrators with practical information to optimize resource allocation and streamline ED operations, contributing to better patient experience. This methodology is particularly suited for healthcare systems that face different patient demands and limited resources.

BackgroundRetriage is the emergent interhospital transfer of severely injured patients from nontrauma and low-level trauma centers to high-level trauma centers. An estimated 17%‐34% of patients with traumatic injury are undertriaged to nontrauma or low-level trauma centers in the United States each year. These patients see 30% increased odds of mortality at 48 hours and nearly 4-fold increased odds of overall mortality. However, 30%‐50% of undertriaged patients are never retriaged to a high-level trauma center. Informatics-driven solutions facilitate time-sensitive exchange of patient information in other health care contexts. Few studies have explored how informatics-driven solutions can be tailored to address obstacles to timely, effective retriage.ObjectiveWe applied user-centered design to develop a robust, acceptable, and feasible digital health solution to improve the retriage process.MethodsThis was a mixed methods, observational, cross-sectional study. Potential frontline users of an intervention and hospital leadership were recruited to participate. Individuals in these roles included trauma medical directors, emergency department directors, trauma surgeons, emergency medicine physicians, emergency department nurse managers, emergency department nurses, trauma coordinators, emergency department bed managers, and health unit coordinators at nontrauma or low-level trauma centers and high-level trauma centers. We applied the 5-phase user-centered design approach, including phase 1: understanding the design needs, through site visit observations and focus groups; phase 2: ideation of potential solutions through a second round of virtual focus groups; phase 3: rank ordering solutions to identify the most robust, acceptable, and potentially feasible solutions; phase 4: prototyping by creating low-fidelity prototypes for the highest-ranked solutions; and phase 5: validation of the robustness of the prototypes through virtual focus groups. Validation approaches included asking frontline end users to assess the feasibility of each prototype and whether prototypes would address the identified retriage failures and barriers. In addition, leaders were asked to assess the feasibility of implementing the proposed solutions in their trauma center. All virtual sessions were recorded, transcribed, and inductively coded to generate themes of robustness, acceptability, and feasibility of the retriage solution. Thematic analysis was anchored on the desirability, viability, and feasibility design thinking methodology.ResultsNineteen sessions were conducted across all 5 phases with 49 participants from 12 trauma centers across Illinois. Participants included frontline users and leadership. The key design requirement was resource transparency between centers. The ideation phase produced 70 solutions. A systemwide bed tracker was ranked the highest by participants. Prototyping and validation resulted in a centralized, systemwide, bed tracker with hourly updated bed availability being the final solution to improve the retriage of patients with traumatic injury from non- or low-level trauma centers and high-level trauma centers.ConclusionsA 5-phase user-centered design approach resulted in a single solution consisting of a digital bed-tracker with frequently updated data on beds at high-level trauma centers to improve retriage.

Background/Objectives: Elderly patients who require aftercare in an intramural care (IMC) facility may contribute to “bed blocking,” which occurs when patients who are ready for discharge remain hospitalized longer than medically necessary. While most bed-blocking studies focus on capacity issues, this study also investigates the coordination process. In a regional hospital in the Netherlands, we examine the extent to which bed blocking occurs due to patients awaiting IMC, and how this issue can be characterized in terms of capacity and coordination challenges. Methods: The case study employs a mixed-methods approach, analyzing system data, documents, and interviews from the hospital, IMC organizations, and a health insurance provider. The location of each patient (organization and department) was collected and reconstructed to a patient path. All patient paths together formed a network enabling data analysis both on the level of patient paths as well as on the level of the networks as they developed through time. This gave insight into the complexity of the total network that has to be coordinated. Results: In 2023, 6% of the hospital capacity was occupied by patients awaiting IMC. Delays were observed at various coordination stages. Due to a lack of data on IMC bed capacity, we were unable to establish whether capacity limitations also contributed to bed blocking. Conclusions: The coordination system is complex and includes waiting times at each coordination stage, resulting in bed blocking. The absence of a centralized capacity overview, coupled with limited data, prevents decision-makers from identifying bed blocking arising from capacity shortages. Greater insight is needed to coordinate patient flow and determine the required slack capacity.

Healthcare systems face unprecedented operational challenges including capacity constraints and financial pressures, exacerbated by workforce shortages and shifting care delivery models. Optimized transfer centers emerge as a strategic solution, functioning as centralized hubs that coordinate inter- and intra-facility patient transfers while integrating clinical decision-making with logistics and bed management. This article explores how such centers serve as catalysts for enhancing access, efficiency, and cost control across a ten-hospital health system in the DMV region. Through a performance transformation framework, the article examines the structural and technological components contributing to effective transfer center operations, including centralized communication platforms, real-time data integration systems, standardized triage protocols, bed management visualization technologies, and interdisciplinary staffing models. Key outcomes demonstrate significant improvements in transfer times, emergency department boarding, resource utilization, and financial performance. The implementation framework focuses on improving performance and lowering costs for outbound BLS ambulance and wheelchair van services for acute patient transport, while simultaneously reducing administrative burden on clinicians who were previously arranging outbound transportation and decreasing overall length of stay. Optimized transfer centers represent a high-impact intervention for healthcare systems seeking to improve resource allocation while enhancing quality and equity of care across distributed networks.

A bed management system was developed to optimize nurse staffing and improve patient safety by considering patient severity and adverse events.

Exploring delayed admissions to ICU: A qualitative study of clinician perceptions and observations of the ICU admission process.

The aim of this study was to estimate the main hospital organisational impacts of in vivo gene therapy medicine (GTM) deployment, experienced during clinical trials, with a focus on hospital pharmacy. Interviews were performed with 11 healthcare professionals involved in three clinical trials, as was an active field observation. Interviews showed high impact for the management of hospital beds and human resources. Moderate impact concerned facilities/equipment, coordination between stakeholders and training/software. The total cumulative working time of the pharmacy staff, estimated at 11.12 and 11.67 hours in the two centres for a single GTM, has been identified as the main limiting factor for the pharmacy. This study showed that major organisational impacts of in vivo GTMs in injection centres concern hospital bed and pharmaceutical staff management, rather than technical and operational aspects. Overall, no more than 150 GTMs could be prepared each year by one pharmacist and one technician.

Assessment and management of chronic venous, arterial, and diabetic wounds in older adults.

Effective inpatient bed management is critical for optimizing healthcare resource utilization and ensuring high-quality patient care. The growing imbalance between bed capacity and patient demand underscores the need for robust, patient-centered prioritization frameworks. However, existing approaches often neglect patient-specific characteristics, interdependencies among criteria, and uncertainty inherent in decision-making processes. To address these challenges, this study proposes a hybrid multi-criteria decision-making framework that integrates interval type-2 fuzzy sets, the DEMATEL method, and the VIKOR method. Interval type-2 fuzzy sets are used to manage linguistic uncertainty; DEMATEL identifies causal relationships among evaluation criteria; and the 2-tuple linguistic VIKOR method enables comprehensive ranking of patient admission alternatives by balancing clinical urgency, operational efficiency, and fairness. Empirical analysis demonstrates that medical urgency, diagnosis type priority and wait time are the most influential criteria, emphasizing their critical role in patient prioritization. The proposed framework effectively models interdependencies and provides transparent, structured rankings, offering a robust tool for equitable and efficient resource allocation in capacity-constrained healthcare settings. This study contributes to healthcare operations research by delivering a flexible and interpretable method for improving patient admission decision-making.

Estimation of sediment concentration (SC) is of vital importance in terms of siltation and economic life of dams, lakes and aqueducts, reservoir operations, design of water resource structures, monitoring and control of water pollution, and flood management. Direct measurement of SC is a challenging and expensive task. For these reasons, it was used to estimate the SC values at a station in the Euphrates River. New hybrid models were established by combining the CatBoost regressor (CBR) and artificial neural network (ANN) models with the honey badger optimization algorithm (HBA) and coati optimization algorithm (COA). The performance of the new model was compared with stand-alone model of ANN and CBR, and their accuracy was evaluated. In the setup of the models, 4 different input combinations of lagged sediment and discharge values for up to 3months were evaluated. It is noteworthy that as the number of input variables, i.e., lagged data input, increases, the prediction accuracy of the models generally increases. HBA and COA algorithms often improve the accuracy of sediment prediction by optimizing the parameters of the single machine learning model. In addition, according to the AIC performance metric, the HBA algorithm is generally slightly better capable of optimization than the COA. The best model outputs were obtained according to the HBA-CBR hybrid approach of scenario 4 (RMSE = 59.78, AIC = 785.03, R2 = 0.32, PBIAS = 0.016, SI = 0.48, and MBE = - 2.05 in test phase), which consists of discharge and sediment with a delay of up to 3months. The results of the study are valuable for decision-makers and planners in terms of practical reservoir and flood management and protection of coasts and river beds.

Objective: This study aims to explore the reasons for hospital discharge-delay in an acute surgical unit (ASU) and the ways in which discharge-delays can be minimised. Background: Discharge-delay, the period of continued hospital stay after a patient is deemed medically fit to leave hospital, is one of the most significant barriers to optimal patient flow within the hospital system. Discharge-delay retains non-acute patients in the acute environment unnecessarily, while preventing acutely presenting patients from accessing services in a timely manner. It results in overcrowded emergency departments (ED) with delayed admissions, slowed theatre schedules, and bed blocking in critical care, as well as negatively impacting patient experience. Methods: A two phased, mixed methods design was employed in this research. Phase one obtained qualitative data through semi-structured interviews with nine staff members occupying different roles within the health care team. Themes derived from phase one informed the development of an audit and survey form utilised in phase two, which involved collecting quantitative data through its completion by registered nurses working in the ASU during the study period. This audit recorded the time a patient was cleared for discharge, and the time they left the ward, from which the amount of discharge-delay could be calculated. The survey recorded delaying factors that occurred for each patient discharged from the ward during the audit period. Results: Thematic analysis of the interview transcriptions revealed three core themes: (i) It takes a village to discharge a patient; (ii) Preparation, clearance, home; and (iii) Challenges and solutions to discharge-delay. The survey was completed by Registered Nurses regarding 40 discharging patients who they provided care for. Analysis revealed a mean patient discharge-delay of 225 minutes across the 40 patients. The most frequently recorded delay factors were ‘waiting for paperwork’ (55%) and ‘waiting for transport’ (40%). Conclusions: This study found that to reduce discharge-delay system-wide optimisation across the entire patient journey, with particular focus on reducing paperwork related delay, is required. Introducing a ‘discharge-focused clinician’ and improving the utilisation of transit lounge will especially help to reduce discharge-delay. What is already known about the topic? Unnecessarily long hospital admissions negatively impact patient experience and outcomes. Slow acute discharges effects patient flow organisation wide, including EDs, critical care, and theatre. What this paper adds? This paper focuses on the time between a patient being medically cleared and physically leaving the acute ward environment, allowing the specific period of discharge-delay to be quantified, understood and addressed. It clearly identifies specific discharge-delay causing factors in the context of an ASU and proposes solutions to optimise the discharge process.

Effective management of urban green spaces can positively contribute to the biodiversity of a city. Yet, much of the information about which management practices support biodiversity are derived from data on vertebrates, with little known about invertebrates. Here we report on a year-long field study in Melbourne, Australia across 12 urban garden beds that vary in their design and management. We investigate vegetation-based design and management choices that impact arthropod populations, to provide guidelines for the design and management of urban garden beds. First, we show that native vegetation facilitates flowering and enables arthropods to undertake crucial life cycle activities across the year. We also suggest that complex vegetation (that is, vegetation with canopy, midstorey and understorey elements) may facilitate important arthropod behaviours, and find that canopy trees are not strongly associated with arthropod activity, despite being a common target of vegetation management interventions in urban parks. Finally, we find that the vegetation preferences are not uniform across all arthropod groups, and as such a patchwork of garden beds with different design features will support a diverse set of arthropods within a park and across a city. We recommend that these three interventions be considered when designing and managing urban garden beds, to encourage functioning arthropod populations and support conservation in urban areas.

This study seeks to explore the efficacy of utilizing dermal skin pieces as a potential alternative to mesh removal in cases of titanium mesh exposure after cranioplasty, with the goal of preserving the benefits of the rigid prosthesis. This retrospective study analyzed patients who underwent treatment at the Department of Burns and Wound Repair Surgery of Zibo Central Hospital between January 2018 and November 2022 with the intention of preserving the titanium mesh. The treatment protocol involved initial wound bed management, including debridement of necrotic tissue and eradication of bacteria, followed by the augmentation of dermal thickness using a dermal pad to maintain the integrity of the titanium mesh. Eight patients, consisting of 6 males and 2 females with a mean age of 47.5 ± 17.5 years (range, 30-65), were included in the study. The exposed area of the mesh varied from 0.3 × 1 to 2 × 3.0cm, with the thinning scalp area around the exposed titanium mesh ranging from 1.6 × 1.8 to 2 × 2.5cm. The hospital stay duration ranged from 21 to 40 days, with all 8 patients achieving primary wound healing. No signs of recurrence were observed during the 6 to 18 months of follow-up, and cranial CT scans showed no abnormalities. In conclusion, the utilization of dermal skin grafts to cover exposed titanium mesh after cranioplasty may facilitate the preservation of the titanium mesh.

Efficacy of lime-based conditioner against environmental udder pathogens in different bedding materials.

The COVID-19 outbreak put a significant pressure on limited healthcare resources. The specific number of people that may be affected in the near future is difficult to determine. We can therefore deduce that the corona virus pandemic’s healthcare requirements surpassed available capacity. The Internet of Things (IoT) has emerged an crucial concept for the advancement of information and communication technology. Since IoT devices are used in various medical fields like real-time tracking, patient data management, and healthcare management. Patients can be tracked using a variety of tiny-powered and lightweight wireless sensor nodes which use the body sensor network (BSN) technology, one of the key technologies of IoT advances in healthcare. This gives clinicians and patients more options in contemporary healthcare management. This study report focuses on the conditions for vacating beds available for COVID-19 patients. The patient’s health condition is recognized and categorised as positive or negative in terms of the Coronavirus disease (COVID-19) using IoT sensors. The proposed model presented in this paper uses the ARIMA model and Transformer model to train a dataset with the aim of providing enhanced prediction. The physical implementation of these models is expected to accelerate the process of patient admission and the provision of emergency services, as the predicted patient influx data will be made available to the healthcare system in advance. This predictive capability of the proposed model contributes to the efficient management of healthcare resources. The research findings indicate that the proposed models demonstrate high accuracy, as evident by its low mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE).

Background: Improving the efficiency of teaching hospitals is a growing concern in health systems worldwide. These institutions face unique challenges due to their dual role in delivering care and training professionals. This review synthesizes recent international evidence on strategies to improve teaching hospital efficiency. Methods: A structured literature search was conducted in the PubMed, EMBASE, and Cochrane Library databases for English-language articles published between 2015 and 2024. Articles were selected based on predefined inclusion and exclusion criteria. Eligible studies were analysed and thematically synthesized. Results: Five studies met the inclusion criteria. The most common analytical method was Data Envelopment Analysis (DEA) (n=3), with one study each using DEA combined with PROMETHEE, DEA with propensity score matching, and stochastic frontier analysis. Key efficiency drivers identified included fixed-price payment systems, hospital closures, centralized bed and waitlist management, outpatient service prioritization, and resource optimization. Teaching hospitals were generally found to be less efficient than non-teaching ones, largely due to greater operational complexity. Conclusion: A variety of strategies and hybrid analytical methods are being used internationally to enhance efficiency in teaching hospitals. Structural reforms and operational innovations, particularly those related to centralized management and financial incentives, appear to be most effective. Partnerships between public and academic hospitals may improve efficiency through better resource sharing. However, findings are limited to a small number of countries. Further research is needed to assess the long-term impacts of these strategies across diverse healthcare contexts.

BackgroundSuboptimal patient flow and impaired hospital access can lead to adverse outcomes, including lower care quality, higher mortality risk, and patient dissatisfaction. Despite awareness, optimizing patient flow remains an area requiring further development. This study aimed to comprehensively identify factors hindering patient flow in a large healthcare system and explore potential solutions, using a qualitative approach for context-specific insights.MethodsThis qualitative study followed COREQ guidelines. We conducted four focus group discussions (FGDs) involving 23 healthcare workers (HCWs) and patients selected through purposive sampling. The data were analysed using the directed content analysis method, ensuring rigor through methods such as credibility, dependability, authenticity, and transferability. The study also mapped qualitative findings to outcomes from our recent umbrella review (UR) to enhance comprehensiveness.ResultsPatient flow challenges were categorized into population (patients and providers), capacity, and process. Population challenges included community-based care, staffing issues, and inequities in access. The capacity challenges involved inefficient resource allocation, resource constraints, and patient volume growth. The process challenges included bed management, modernization struggles, private hospital issues, funding model problems, information sharing gaps, coordination challenges, transition issues, particularly delayed discharges from inpatient wards, and problems in healthcare management and patient communication. The solutions focused on human factors, infrastructure, and management, organization, and policy. FGDs identified new challenges and solutions were not covered in the recent UR.DiscussionThe participants’ insights highlight the critical necessity for systemic improvements, which include enhancing infrastructure, communication, and collaboration. These improvements include early identification of discharge barriers, facilitating community discharge, addressing diverse patient needs, optimizing prehospital services, and improving patient communication. Shifting the focus from traditional emergency department processes to a system-wide approach is crucial. The comparative mapping between FGDs and the UR insights into both common and specific challenges and solutions enriches discussions on healthcare reform.