Evaluation of a real-life experience with a digital fluid balance monitoring technology.

BACKGROUND: Innovations in healthcare technologies have the potential to address challenges, including the monitoring of fluid balance. OBJECTIVE: This study aims to evaluate the functionality and accuracy of a digital technology compared to standard manual documentation in a real-life setting. METHODS: The digital technology, LICENSE, was designed to calculate fluid balance using data collected from devices measuring urine, oral and intravenous fluids. Participating patients were connected to the LICENSE system, which transmitted data wirelessly to a database. These data were compared to the nursing staff's manual measurements documented in the electronic patient record according to their usual practice. RESULTS: We included 55 patients in the Urology Department needing fluid balance charting and observed them for an average of 22.9 hours. We found a mean difference of -44.2 ml in total fluid balance between the two methods. Differences ranged from -2230 ml to 2695 ml, with a divergence exceeding 500 ml in 57.4% of cases. The primary source of error was inaccurate or omitted manual documentation. However, errors were also identified in the oral LICENSE device. CONCLUSIONS: When used correctly, the LICENSE system performs satisfactorily in measuring urine and intravenous fluids, although the oral device requires revision due to identified errors.

[Sustainability in occupational dermatology : Starting points, challenges, and potentials for sustainable care of work-related skin diseases]. / Nachhaltigkeit in der Berufsdermatologie : Ansatzpunkte, Herausforderungen und Potenziale für eine nachhaltige(re) Versorgung beruflich Hauterkrankter.

Sustainability is becoming increasingly important in healthcare and has moved into focus at various levels. This article aims to provide an overview of guiding principles, concepts, and target systems of sustainability and to transfer these to occupational dermatology. Current and future starting points are outlined for various levels, e.g., politics, research, industry, and patient care, in order to link sustainability and occupational dermatology in a structured and systematic way and to transform the structures of patient care in occupational dermatology care towards sustainability. Using the specific example of protective gloves, which is a pivotal personal protective measure to prevent work-related hand eczema, starting points, potentials, and challenges are analyzed and specific possibilities and perspectives for more ecologically sustainable action are presented.

The development research on marine ecological environment online monitoring equipment system in China.

There is an urgent need for marine ecological environment monitoring in China at present, but the traditional manual periodic sampling and testing has such disadvantages as low monitoring frequency and limited station coverage, which could not meet the requirements of large-scale real-time continuous data for current marine ecological early-warning monitoring. Therefore, constructing the multi-level, multi-system, and multi-space marine ecological environment online monitoring system could effectively develop marine ecological environment early-warning monitoring capacity. In this paper, the concept of "System of Systems" was introduced into the construction of marine ecological environment online monitoring equipment system, and the architecture of "System of Systems" of the monitoring equipment was constructed from two layers, structure layer and function layer. The composition of the two layers, and the difficulties in construction of the two layers were emphatically discussed. The paper also analyzed the methods of developing "System of Systems" of marine ecological environment online monitoring system.

Evaluating soft collars in pre-hospital cervical spine immobilisation: A cohort study on neurological outcomes, patient comfort and paramedic perspectives.

OBJECTIVE: Cervical spinal immobilisation procedures often include rigid cervical collars which, despite associated complications, may provide less immobilisation than previously thought. The present study reports the incidence of worsening neurological outcomes following soft collar application, and additionally reports patient comfort, compliance with spinal immobilisation, and paramedic perspectives on usage. METHODS: This was an observational cohort study conducted in selected metropolitan and regional areas of NSW Ambulance between 1 May 2022 and 31 March 2023. Soft collars were used exclusively in place of rigid collars. The SPEED (SPinal Emergency Evaluation of Deficits) tool was used to evaluate new or worsening neurological deficits following pre-hospital soft collar application. Secondary outcomes included patient-reported comfort of the device, and paramedic assessment of efficacy. RESULTS: Overall, 2098 soft collars were applied, of which 74 patients (3.5%) were subsequently found to have a cervical spine injury. Eight patients had a spinal cord injury, of which two experienced a worsening neurological deficit after soft collar application. In both instances, comprehensive case reviews determined that this was unlikely to have been attributable to the soft collar. The majority of patients found the soft collar comfortable, and they were well-tolerated by patients who generally complied with immobility directions. Paramedics found the collar easy to apply, and felt it assisted in minimising patient movement. CONCLUSIONS: Pre-hospital use of soft collars does not appear to increase the risk of significant injury. Patients found these devices relatively comfortable, and clinicians reported overall ease of use with good patient compliance with immobility directives.

Applying Microsoft Power Platform to Improve Primary Medical Equipment Maintenance Processes.

Post-COVID, our hospital shifted to online systems using Microsoft Power Platform to mitigate errors and delays. SharePoint and Power Apps manage equipment maintenance records and submissions, enhancing immediacy and transparency. Power Automate automates report generation and reminders, improving task completion rates. Power BI visualizes data for streamlined management. Adjustments to real-time reporting enhanced efficiency, reducing manual efforts and improving completion rates.

Improving Safety and Comfort of Healthcare Workers Caring for Patients With High-Consequence Infectious Diseases in a High-Level Isolation Unit Using Innovative Approaches.

Patients with high-consequence infectious diseases (HCIDs) require high-quality care by specially trained staff in a high-level isolation unit (HLIU) that follows strict infection prevention and control (IPC) measures. Caring for patients with (suspected) HCID is challenging, mainly because of the strict personal protective equipment (PPE) and IPC protocols healthcare workers (HCW) must adhere to for protection. The Radboud University Medical Center, located in Nijmegen, the Netherlands, has been a dedicated HLIU facility since 2008. A newly built HLIU opened in May 2022, and encouraged us to review the existing PPE selection, IPC protocols, and HCID training program to improve safety and comfort for HCWs working in the HLIU. Based on a systematic search through (inter)national HCID PPE guidelines and semistructured interviews with end users, we selected an improved, more comfortable set of PPE. Additionally, we developed a more concise and easier-to-use patient care process flow and implemented a new teaching strategy. The new way of working was tested in October 2022 when the first 2 patients with suspected HCID were admitted to our unit. We used surveys to evaluate the experiences of HCWs involved in this care to further improve the workflow of the unit. When optimizing safety and comfort for HCWs, it is important to consider (inter)national guidelines as well as user preferences. By systematically evaluating recent experiences of patient admission to the HLIU and then adjusting protocols and training, we can ensure that the quality of provided healthcare and the safety of HCWs working in the HLIU remains high.

Investigating Microbial Contamination of Indoor Air, Environmental Surfaces, and Medical Equipment in a Southwestern Ethiopia Hospital.

Introduction: Healthcare-associated infections, primarily caused by microorganisms, are widespread in healthcare facilities. These infections pose a significant challenge, especially in low and middle-income countries, and have a detrimental impact on patient outcomes. It is crucial to assess the level of microbial load and associated factors to prevent the spread of these infections. The objective of this study was to assess the microbial load and identify the factors associated with it in various wards at Jimma Medical Center. Method: A cross-sectional study conducted at Jimma Medical Center. Indoor air samples were collected using the settle plate method with a 1/1/1 scheme. Inanimate surfaces and medical equipment were sampled using Swabs from a 10 × 10 cm area. A total of 268 samples were collected from 10 rooms. Pertinent information regarding the associated factors was gathered using an observational checklist. A multiple linear regression model was used to identify any associations with the microbial load. Result: Out of the total samples, 181 (67.5%) tested positive for culture, and 270 microbes were isolated. The average load of bacteria and fungi in the indoor air ranged from 124.4 to 1607 and 96 to 814.6 Colony-forming unit (CFU)/m3, respectively. The mean total aerobic colony counts of bacteria and fungi from all surfaces in the wards ranged from 5.25 to 43.3 CFU/cm2. Crowdedness [ß = 2.748 (95% Confidence Interval (CI): 1.057-4.44)], the presence of waste material [ß = 1.747 (95% CI: 0.213-3.282)], and an unclean room [ß = 2.505 (95% CI: 0.990-4.019)] were significantly associated with the microbial load. Conclusion: The microbial load detected in indoor air, inanimate surfaces and medical equipment was posing potential health risks. Consequently, it is recommended to implement regular microbial surveillance of the hospital environment and enhance the infection prevention program to mitigate these concerns.

The refurbishment and redistribution of disability equipment from the UK to low- and middle-income countries: a case study focusing on 2016-2021 redistributions to Romania.

The surplus of used disability equipment contributing to waste in the UK and the lack of access to disability equipment in low- and middle-income countries (LMICs) are two issues in need of solution. To address such problems, UK charities refurbish and redistribute used disability equipment to LMICs. To date, there is a scarcity of data on how LMICs could access surplus disability equipment from UK organisations. This study aimed to collate and map out the process by which equipment is refurbished and redistributed from the UK to LMIC's and identify factors which influence the development and sustainability of the partnership. An explorative qualitative case study design was used. Nine semi-structured interviews were conducted with participants from sender (UK) and a receiver (Romania) organisation between January-February 2022, with real-time translation where necessary. Intelligent verbatim transcription was used, and data was analysed using latent thematic analysis. The process of collection, refurbishment and redistribution of disability equipment from the UK to a LMIC organisation was mapped. Three key themes were identified from the interviews: (1) Development out of need; (2) Service development requires an adequate working relationship; (3) Process consolidation and future. Strong, honest and transparent relationships between organisations was identified as underpinning the success of the initiative. Raising service provision standards to meet specific needs of LMIC organisations supports development of suitable equipment prescription. Development of similar partnerships has potential of reducing the inequity gap and waste. Global collaboration and planning are required to address challenges of access to disability equipment in LMICs.

Refurbishment and redistribution of surplus disability equipment has emerged and continues to be developed as a response to a critical need for equipment provision in low- and middle-income countries (LMICs), as well as to reduce surplus waste of equipment within the UK.The development of strong, honest, transparent and continued relationships between organisations was identified as underpinning the success of the initiative, in particular raising service provision standards to meet specific needs of LMIC organisations to develop suitable equipment prescription for service users.Development of similar partnerships has the potential of reducing the inequity gap and waste. Global collaboration and planning are required to address challenges of access to disability equipment in LMICs.

A comprehensive review of 5G NR RF-EMF exposure assessment technologies: fundamentals, advancements, challenges, niches, and implications.

This review offers a detailed examination of the current landscape of radio frequency (RF) electromagnetic field (EMF) assessment tools, ranging from spectrum analyzers and broadband field meters to area monitors and custom-built devices. The discussion encompasses both standardized and non-standardized measurement protocols, shedding light on the various methods employed in this domain. Furthermore, the review highlights the prevalent use of mobile apps for characterizing 5G NR radio network data. A growing need for low-cost measurement devices is observed, commonly referred to as "sensors" or "sensor nodes", that are capable of enduring diverse environmental conditions. These sensors play a crucial role in both microenvironmental surveys and individual exposures, enabling stationary, mobile, and personal exposure assessments based on body-worn sensors, across wider geographical areas. This review revealed a notable need for cost-effective and long-lasting sensors, whether for individual exposure assessments, mobile (vehicle-integrated) measurements, or incorporation into distributed sensor networks. However, there is a lack of comprehensive information on existing custom-developed RF-EMF measurement tools, especially in terms of measuring uncertainty. Additionally, there is a need for real-time, fast-sampling solutions to understand the highly irregular temporal variations EMF distribution in next-generation networks. Given the diversity of tools and methods, a comprehensive comparison is crucial to determine the necessary statistical tools for aggregating the available measurement data.

Kinetic investigation on the catalytic pyrolysis of plastic fractions of waste electrical and electronic equipment (WEEE): A mathematical deconvolution approach.

Waste electrical and electronic equipment (WEEE) has become a critical environmental problem. Catalytic pyrolysis is an ideal technique to treat and convert the plastic fraction of WEEE into chemicals and fuels. Unfortunately, research using real WEEE remains relatively limited. Furthermore, the complexity of WEEE complicates the analysis of its pyrolytic kinetics. This study applied the Fraser-Suzuki mathematical deconvolution method to obtain the pseudo reactions of the thermal degradation of two types of WEEE, using four different catalysts (Al2O3, HBeta, HZSM-5, and TiO2) or without a catalyst. The main contributor(s) to each pseudo reaction were identified by comparing them with the pyrolysis results of the pure plastics in WEEE. The nth order model was then applied to estimate the kinetic parameters of the obtained pseudo reactions. In the low-grade electronics pyrolysis, the pseudo-1 reaction using TiO2 as a catalyst achieved the lowest activation energy of 92.10 kJ/mol, while the pseudo-2 reaction using HZSM-5 resulted in the lowest activation energy of 101.35 kJ/mol among the four catalytic cases. For medium-grade electronics, pseudo-3 and pseudo-4 were the main reactions for thermal degradation, with HZSM-5 and TiO2 yielding the lowest pyrolytic activation energies of 75.24 and 226.39 kJ/mol, respectively. This effort will play a crucial role in comprehending the pyrolysis kinetic mechanism of WEEE and propelling this technology toward a brighter future.

Implementation of a Power Down Initiative in 34 Operating Rooms.

Operating rooms (ORs) use energy-intensive equipment such as anesthesia gas machines, patient monitors, and lights. They are major contributors to an institution's carbon footprint; yet ORs are unoccupied 40% of the time. Implementing an initiative to power down electrical devices can reduce energy consumption, equipment failure, and financial outlay. This quality improvement project developed and implemented a power down initiative for anesthesia staff to use in ORs. The initiative included turning off anesthesia gas machines, patient monitors, auxiliary oxygen delivery, and room lights at the end of scheduled cases in ORs that were not used for emergencies. Convenience audits were conducted. Pre- and postimplementation compliance outcomes showed that there was an increase in powering down the anesthesia gas machine, patient monitor, auxiliary oxygen, and room lights. Powering down unnecessary equipment at this facility has the potential to save approximately $50,000 and prevent the emission of over 80 metric tons of CO2 per year. Other facilities can implement a similar quality improvement project aimed at fiscal and ecological conservation.

Research on a Three-Way Decision-Making Approach, Based on Non-Additive Measurement and Prospect Theory, and Its Application in Aviation Equipment Risk Analysis.

Due to the information non-independence of attributes, combined with a complex and changeable environment, the analysis of risks faces great difficulties. In view of this problem, this paper proposes a new three-way decision-making (3WD) method, combined with prospect theory and a non-additive measure, to cope with multi-source and incomplete risk information systems. Prospect theory improves the loss function of the original 3WD model, and the combination of non-additive measurement and probability measurement provides a new perspective to understand the meaning of decision-making, which could measure the relative degree by considering expert knowledge and objective data. The theoretical basis and framework of this model are illustrated, and this model is applied to a real in-service aviation equipment structures risk evaluation problem involving multiple incomplete risk information sources. When the simulation analysis is carried out, the results show that the availability of this method is verified. This method can also evaluate and rank key risk factors in equipment structures, which provides a reliable basis for decisions in aviation safety management.

Minimizing and managing needle and instrument loss during pediatric robotic surgery.

INTRODUCTION: Lost objects and equipment malfunctions during robotic and laparoscopic cases can lead to an increase in operating time and potential risk to the patient. The literature on the management of foreign bodies during pediatric robotic-assisted surgery is limited. The purpose of the video is to review proper instrument handling to prevent loss of an object and to propose our technique for retrieving lost objects through two pediatric case examples. MATERIALS AND METHODS: The first case is a robotic-assisted laparoscopic left pyeloplasty in a 6-week-old male with congenital uteropelvic junction obstruction during which a needle was lost. In the video, we describe our techniques for safe needle passage, proper suturing technique, and recovering a lost needle. The second case is a robotic-assisted right upper pole heminephrectomy in a 14-month-old female with a duplicated renal collecting system and hydroureteronephrosis. We present the management of a rare case during which a harmonic scalpel jaw malfunctioned leading to a lost foreign body. We describe our technique for retrieving the lost fragment. RESULTS: All objects were safely removed, and patients were discharged post-op day one without complication. CONCLUSION: Our video presents two case examples of foreign bodies lost during pediatric robotic surgeries and approaches to manage each of these incidents.

Intelligent Fault Diagnosis Method Based on Cross-Device Secondary Transfer Learning of Efficient Gated Recurrent Unit Network.

In response to the issues of low model recognition accuracy and weak generalization in mechanical equipment fault diagnosis due to scarce data, this paper proposes an innovative solution, a cross-device secondary transfer-learning method based on EGRUN (efficient gated recurrent unit network). This method utilizes continuous wavelet transform (CWT) to transform source domain data into images. The EGRUN model is initially trained, and shallow layer weights are frozen. Subsequently, random overlapping sampling is applied to the target domain data to enhance data and perform secondary transfer learning. The experimental results demonstrate that this method not only significantly improves the model's ability to learn fault features but also enhances its classification accuracy and generalization performance. Compared to current state-of-the-art algorithms, the model proposed in this study shows faster convergence speed, higher diagnostic accuracy, and superior robustness and generalization, providing an effective approach to address the challenges arising from scarce data and varying operating conditions in practical engineering scenarios.

An Improved Method for Detecting Crane Wheel-Rail Faults Based on YOLOv8 and the Swin Transformer.

In the realm of special equipment, significant advancements have been achieved in fault detection. Nonetheless, faults originating in the equipment manifest with diverse morphological characteristics and varying scales. Certain faults necessitate the extrapolation from global information owing to their occurrence in localized areas. Simultaneously, the intricacies of the inspection area's background easily interfere with the intelligent detection processes. Hence, a refined YOLOv8 algorithm leveraging the Swin Transformer is proposed, tailored for detecting faults in special equipment. The Swin Transformer serves as the foundational network of the YOLOv8 framework, amplifying its capability to concentrate on comprehensive features during the feature extraction, crucial for fault analysis. A multi-head self-attention mechanism regulated by a sliding window is utilized to expand the observation window's scope. Moreover, an asymptotic feature pyramid network is introduced to augment spatial feature extraction for smaller targets. Within this network architecture, adjacent low-level features are merged, while high-level features are gradually integrated into the fusion process. This prevents loss or degradation of feature information during transmission and interaction, enabling accurate localization of smaller targets. Drawing from wheel-rail faults of lifting equipment as an illustration, the proposed method is employed to diagnose an expanded fault dataset generated through transfer learning. Experimental findings substantiate that the proposed method in adeptly addressing numerous challenges encountered in the intelligent fault detection of special equipment. Moreover, it outperforms mainstream target detection models, achieving real-time detection capabilities.

Performance Assessment of Object Detection Models Trained with Synthetic Data: A Case Study on Electrical Equipment Detection.

This paper explores a data augmentation approach for images of rigid bodies, particularly focusing on electrical equipment and analogous industrial objects. By leveraging manufacturer-provided datasheets containing precise equipment dimensions, we employed straightforward algorithms to generate synthetic images, permitting the expansion of the training dataset from a potentially unlimited viewpoint. In scenarios lacking genuine target images, we conducted a case study using two well-known detectors, representing two machine-learning paradigms: the Viola-Jones (VJ) and You Only Look Once (YOLO) detectors, trained exclusively on datasets featuring synthetic images as the positive examples of the target equipment, namely lightning rods and potential transformers. Performances of both detectors were assessed using real images in both visible and infrared spectra. YOLO consistently demonstrates F1 scores below 26% in both spectra, while VJ's scores lie in the interval from 38% to 61%. This performance discrepancy is discussed in view of paradigms' strengths and weaknesses, whereas the relatively high scores of at least one detector are taken as empirical evidence in favor of the proposed data augmentation approach.

A Novel Electrical Equipment Status Diagnosis Method Based on Super-Resolution Reconstruction and Logical Reasoning.

The accurate detection of electrical equipment states and faults is crucial for the reliable operation of such equipment and for maintaining the health of the overall power system. The state of power equipment can be effectively monitored through deep learning-based visual inspection methods, which provide essential information for diagnosing and predicting equipment failures. However, there are significant challenges: on the one hand, electrical equipment typically operates in complex environments, thus resulting in captured images that contain environmental noise, which significantly reduces the accuracy of state recognition based on visual perception. This, in turn, affects the comprehensiveness of the power system's situational awareness. On the other hand, visual perception is limited to obtaining the appearance characteristics of the equipment. The lack of logical reasoning makes it difficult for purely visual analysis to conduct a deeper analysis and diagnosis of the complex equipment state. Therefore, to address these two issues, we first designed an image super-resolution reconstruction method based on the Generative Adversarial Network (GAN) to filter environmental noise. Then, the pixel information is analyzed using a deep learning-based method to obtain the spatial feature of the equipment. Finally, by constructing the logic diagram for electrical equipment clusters, we propose an interpretable fault diagnosis method that integrates the spatial features and temporal states of the electrical equipment. To verify the effectiveness of the proposed algorithm, extensive experiments are conducted on six datasets. The results demonstrate that the proposed method can achieve high accuracy in diagnosing electrical equipment faults.

The positioning information that should be provided to caregivers of adults with a physical disability on supply of custom-contoured seating, a Delphi study.

PURPOSE: This research aims to identify information that is important to provide on supply of custom-contoured seating. The way this information would be best communicated is also of interest. A two-round e-Delphi study was utilised to explore consensus. A panel of stakeholders from Ireland including experts in positioning clients in custom-contoured seating and caregivers were recruited. The first round consisted of open-ended questions and was analysed using thematic analysis. The second round employed a rating technique and 7-point Likert scale. Consensus was set a priori at 70% agreement. The way information should be communicated and by whom was rated in order of preference. MATERIALS AND METHODS: Fifteen participants were recruited, nine clinicians and four caregivers. Fifty-two statements under six themes (transfers = 10, positioning = 22, pressure care = 4, general use = 4, post-supply follow-up = 8, functional activity = 4) were generated in round 1 by 13/15 participants. Round 2 was completed by 10/15. 49/52 statements reached consensus and were deemed important. The ways information should be communicated and by whom was identified. Caregivers want individualised information whereas clinicians preferred a more generic approach. RESULTS AND CONCLUSIONS: There was a high degree of consensus on what information is required to support caregivers. The topics demonstrate the extensive information that should be provided. The preferred delivery method for primary caregivers was hands-on training with the opportunity to practice and take videos. Stakeholders differed in how they would prefer information delivered. Further research should evaluate the method of delivering training and its effectiveness.

Caregivers report a lack of guidance on postural management, which exacerbates their own health problems and results in underutilization of positioning equipment.Caregivers should be provided with information on transfers, positioning, pressure care, general chair use, post-supply follow-up, and the impact on functional activities when a new custom contoured seat is supplied.The preferred method of providing information to primary caregivers is to use hands-on training with the opportunity to practice and take videos during the supply appointment. Personalised information booklets or group training sessions may be most appropriate for additional caregivers.

A Cross-Sectional Analysis of Bystander Cardiopulmonary Resuscitation (CPR): Behavioural Changes in the COVID-19 Era.

Objectives The coronavirus disease 2019 (COVID-19) pandemic has impacted public health systems and individuals' behaviour, with decreasing survival rates among out-of-hospital cardiac arrest (OHCA) patients. Bystander cardiopulmonary resuscitation (CPR) improves OHCA outcomes, which may have been affected by COVID-19. We sought to understand the impacts of COVID-19 on bystanders' willingness to administer CPR in three Canadian provinces. Methods Participants ≥ 18 years of age were surveyed online about their current and recalled pre-pandemic attitudes toward CPR and perceived transmission risk. We compared mean willingness to perform various CPR actions before and during the pandemic using paired t-tests. Differences in willingness across three provinces were assessed using analysis of variance (ANOVA) and Tukey's Honestly Significant Difference (HSD) test. We also conducted Chi-square tests to assess changes in willingness to perform CPR on children and older adults. Results Five hundred thirty-five participants were surveyed from October 1 to November 15, 2021. The mean age was 42.7 years (SD 14.5), and 60.2% were female. Participants reported less willingness to perform chest compressions on strangers during the pandemic compared to their recollections before the pandemic (mean willingness 86.2% vs. 94.3% prior, p<0.001). With personal protective equipment (PPE) available, particularly masks, willingness recovered to 91.3% (p<0.001). Willingness was higher in Nova Scotia (NS) than in British Columbia (BC) or Ontario (ON). Reluctance to assist older adults increased from 6.6% to 12.0% (p=0.020). Conclusions This study highlights changes in CPR willingness during the COVID-19 pandemic, underscoring the importance of PPE and offering insights into public health strategies pertaining to CPR during a pandemic.

Personal Protective Equipment Use and Surface Contamination With Antineoplastic Drugs: The Impact of the COVID-19 Pandemic.

BACKGROUND: Surface contamination with antineoplastic drugs (ADs) is persistent. The use of personal protective equipment (PPE) is recommended to reduce exposure to ADs. OBJECTIVES: This study explored the impact of the COVID-19 pandemic on nurses' PPE use and surface contamination with ADs. METHODS: Demographic characteristics, PPE use, and associated factors were assessed on two inpatient oncology units where etoposide and cyclophosphamide were administered before (N = 26) and during the COVID-19 pandemic (N = 31). FINDINGS: PPE use when handling contaminated excreta was significantly higher during the pandemic. Perceived risk of chemotherapy exposure was significantly associated with greater PPE use when handling AD-contaminated excreta, and conflict of interest was related to less PPE use during AD administration and handling of AD-contaminated excreta. During the pandemic, surface contamination with etoposide increased in shared areas and decreased in patient rooms.