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.

BACKGROUND: Inefficient supply chain management within the US healthcare industry results in significant financial and environmental impact. Unopened medical supplies may routinely be discarded in the Emergency Department (ED), contributing as a source of unnecessary medical waste.
OBJECTIVE: Quantify the financial and environmental impact of unopened medical supplies that are routinely discarded in two EDs.
METHODS: The study utilized a waste audit of collection bins targeting unopened medical supplies that would have otherwise been discarded. Associated financial cost was calculated using data from the purchasing department and from an online search. End-of-life (EOL) environmental impact was calculated using the M+ Wastecare calculator. A lifecycle analysis was performed on a supplier-packaged intubation kit, which the study identified as a significant source of waste.
RESULTS: High volumes of unused, unopened supplies (143.48 kg) were collected during the study period with a yearly extrapolated value of 1337 kg. Purchasing costs over 44 days at Hospital A and 37 days at Hospital B for these items amounted to $16,159.71 across both sites with a yearly extrapolated value of $150,631.73. Yearly extrapolated EOL impact yielded 5.79 tons per year of CO2eq. Components from supplier-packaged intubation kits were found to contribute to 45.2% of collected items at one site which purchased them. Lifecycle analysis of an intubation kit yields 23.6 kg of CO2eq.
CONCLUSIONS: This study demonstrates that the disposal of unopened medical supplies contributes a significant source of financial and environmental waste in the ED setting. The results continue to support the trend of procedure kits generating significant environmental and financial waste.

UNASSIGNED: Strengthen the legal, compliant, and rational use of medical equipment and further guide the rationalization of medical behaviors.
UNASSIGNED: By utilizing the Internet of Things (IoT) and image analysis technology, collect real-time operation data of the equipment, establish a real-time running database for medical equipment, and cooperate with the 12 key links of the \"whole life\" of the equipment and the 8+6 management system framework to implement lean management of the efficiency, benefit, and effectiveness of medical equipment usage.
UNASSIGNED: It realizes the improvement of the quality and efficiency of medical equipment, cost reduction and cost control, and provides data support for scientific decision-making.
UNASSIGNED: This study innovates the management model for the entire life cycle of medical equipment, providing a scientific approach to the management of hospital equipment.
UNASSIGNED: 加强医疗设备的合法、合规、合理使用，进一步引导医疗行为的合理化。.
UNASSIGNED: 利用物联网+图像分析技术，采集医疗设备真实的运行数据，建立医疗设备实时运行数据库。结合设备“全生命周期”的12大关键环节和8+6管理制度框架，对医疗设备的使用效率、效益、效果进行精益管理。.
UNASSIGNED: 实现了医疗设备提质增效、降本控费，并为科学决策提供了数据支撑。.
UNASSIGNED: 创新了医疗设备全生命周期的管理模式，为医院设备的管理提供了科学的方法。.

BACKGROUND: Medical equipment (ME) maintenance retains an asset\'s original anticipated useful life and preserves its reliability and cost-effectiveness. This study developed and implemented a multicomponent program to improve ME use and maintenance in nine Sri Lankan hospitals from May 2020 to May 2021.
METHODS: This pre-post implementation study involved an initial baseline assessment of existing ME maintenance systems, the development and implementation of a multicomponent improvement program, and a 3-month postevaluation. Five targets ME were selected for the study: oxygen regulator, electrocardiogram (ECG) machine, suction apparatus, blood pressure apparatus, and mini autoclave. A pretested questionnaire was administered to randomly selected nursing officers (n = 101) and health-care assistants (n = 120) to obtain baseline ME maintenance data. Six focus group discussions and 24 key informant interviews were conducted with key stakeholders to codesign the multicomponent interventions, which included: developing a standard operating procedure targeting preventive maintenance activities; establishing focal points to provide technical and logistic support; staff training; and the introduction of institutional ME maintenance documents. Program effectiveness was assessed at 3 months postimplementation using the seven predefined outcome variables.
RESULTS: Baseline assessment identified no ME maintenance programs implemented in any of the hospitals. The highest availability was observed for oxygen regulator (62% to 82.3%) and ECG machine (66.1% to 84.7%). The highest functionality improvement was observed for ECG machine (40.4% to 79.7%). The positive perception of maintenance process of ME achieved the highest (33% to 80%) improvement. Following program implementation, improvements were noted in: the availability (P = 0.00) and functionality (P = 0.00 to P = 0.02) of all selected ME; equipment maintenance processes (P = 0.000); as well as staff knowledge, skills, perceptions, and satisfaction.
CONCLUSIONS: The program improved the use and maintenance of ME and was widely supported by the key stakeholders. The approach is relevant to other resource-poor hospital settings, as inadequate ME maintenance causes health system inefficiencies.

UNASSIGNED: The hospital supply chain has revealed increasing vulnerabilities and disruptions in the wake of the COVID-19 pandemic, threatening the healthcare services and patient safety. The resilience of hospital supply chains has emerged as a paramount concern within the healthcare system. However, there is a lack of systematic research to develop an instrument tailored to the healthcare industry that is both valid and reliable for measuring hospital supply chain resilience. Therefore, this study aims to construct and validate a comprehensive scale for assessing hospital supply chain resilience, based on dynamic capability theory.
UNASSIGNED: This study followed rigorous scale development steps, starting with a literature review and 15 semi-structured interviews to generate initial items. These items were then refined through expert panel feedback and three rounds of Delphi studies. Using data from 387 hospitals in Province S, mainland China, the scale underwent rigorous testing and validation using structural equation modeling. To ensure the most effective model, five alternative models were examined to determine the most suitable parsimonious model.
UNASSIGNED: The study produced a 26-item scale that captures five dimensions of resilience in line with dynamic capability theory: anticipation, adaptation, response, recovery, and learning, all showing satisfactory consistency, reliability and validity.
UNASSIGNED: The multi-dimensional scale offers hospital managers a valuable tool to identify areas needing attention and improvement, benchmark resilience against their counterparts, and ultimately strengthen their supply chains against unexpected risks.

OBJECTIVE: This study was conducted to assess the availability of equipment and supplies in the emergency departments of the hospitals in the West Bank of Palestine.
METHODS: This study was conducted in a cross-sectional design using a data collection form that was specifically developed for this study. The standardized data collection form contained a detailed list of all essential pediatric emergency equipment and supplies.
RESULTS: This study was conducted in a total of 30 hospitals all across the West Bank of Palestine. The median number of patients visiting the emergency department per day was 115.0, the median number of patients admitted to the hospital per day was 14.5, and the median number of pediatric patients visiting the emergency department per day was 6.0. The median number of pediatricians in the hospital was 4.0, the median number of pediatricians in the emergency department was 1.0, the median number of nurses in the hospital was 75.0, and the median number of nurses in the emergency department was 8.5. Both governmental and private hospitals lacked the equipment and supplies needed for monitoring, gaining vascular access, airway management, resuscitation medications, cervical immobilization equipment, and other equipment and supplies.
CONCLUSIONS: Decision and policymakers might use the findings reported in this study to allocate resources to restock and increase the availability of pediatric emergency equipment and supplies. More studies are still needed to compare the outcomes of patients before and after restocking and increasing the availability of pediatric emergency equipment and supplies.

UNASSIGNED: A strong link exists between adequate supply chain management and nurse efficiency and satisfaction. Implementing Lean methodology, specifically 5S process improvement, staff created a unit-based supply room that was clean, safe, and well organized which led to reduced waste, greater efficiency, and cost savings.

The relationship between two variables is an essential factor in statistics, and the accuracy of the results depends on the data collected. However, the data collected for statistical analysis can be unclear and difficult to interpret. One way to predict how one variable will change about another is by using the correlation coefficient (CC), but this method is not commonly used in interval-valued Pythagorean fuzzy hypersoft set (IVPFHSS). The IVPFHSS is a more advanced and generalized form of the Pythagorean fuzzy hypersoft set (PFHSS), which allows for more precise and accurate analysis. In this research, we introduce the correlation coefficient (CC) and weighted correlation coefficient (WCC) for IVPFHSS and their essential properties. To demonstrate the applicability of these measures, we use the COVID-19 pandemic as an example and establish a prioritization technique for order preference by similarity to the ideal solution (TOPSIS) model. The technique is used to study the problem of optimizing the allocation of hospital beds during the pandemic. This study provides insights into the importance of utilizing correlation measures for decision-making in uncertain and complex situations like the COVID-19 pandemic. It is a robust multi-attribute decision-making (MADM) methodology with significant importance. Subsequently, it is planned to increase a dynamic bed allocation algorithm based on biogeography to accomplish the superlative decision-making system. Moreover, numerical investigations deliberate the best decision structures and deliver sensitivity analyses. The efficiency of our encouraged algorithm is more consistent than prevalent models, and it can effectively control and determine the optimal configurations for the study.

BACKGROUND: Nosocomial outbreaks of urinary tract infections caused by Achromobacter spp. have been rare in recent decades.
OBJECTIVE: To identify the origin of an Achromobacter sp. outbreak, conduct multi-modal infection control measures, and finally to stop the outbreak. To this end, an epidemiological outbreak investigation and risk factor analysis were performed.
METHODS: Achromobacter sp. was detected in 22 patients in our urology wards and six environmental cultures of specimens obtained from the operating rooms. Strains isolated were submitted for antimicrobial susceptibility testing. An on-site epidemiological investigation, evaluation of patient medical records, and environmental sampling were performed to identify the source of the outbreak, and implementation of infection control intervention. A case-control study was performed to analyse the potential risk factors.
RESULTS: Environmental sampling showed that the source of the infection for 22 patients was an ISA-IIIA-type medical pressurizer containing contaminated water. A case-control analysis showed that the risk factors for infection were: diagnosis of kidney/ureteral stones, surgery, placement of a double-J stent, and history of hospitalization in the past three months.
CONCLUSIONS: It was concluded that the outbreak occurred in patients who underwent internal lithotripsy and double-J stent placement, due to contact transmission with the contaminated sensor and connecting tubes of the ISA-IIIA-type medical pressurizer.

BACKGROUND: Modern magnetic resonance imaging (MRI) scanners utilise superconducting magnets that are permanently active. Patients and healthcare professionals have been known to unintentionally introduce ferromagnetic objects into the scanning room. In this study, we evaluated the projectile risk of Singapore coinage as well as some common healthcare equipment within a 3 T MRI scanner.
METHODS: A rig termed \'Object eNtry Guidance and Linear Acceleration Instrument\' (ONG LAI) was custom-built to facilitate safe trajectory of the putative ferromagnetic objects. A ballistic gel target was utilised as a human tissue surrogate to estimate tissue penetration. The point at which objects would self-propel towards the scanner was named \'Huge Unintended Acceleration Towards Actual Harm (HUAT AH)\'.
RESULTS: Singapore third-series coins (10-cent to 1-dollar coins) are highly ferromagnetic and would accelerate towards the MRI scanner from more than one metre away. Cannulas with their needles are ferromagnetic and would self-propel towards the scanner from a distance of 20 cm. Standard surgical masks are ferromagnetic and may lose their sealing efficacy when they are worn too close to the magnet. Among the tested objects, a can of pineapple drink (Lee Pineapple Juice) had the highest HUAT AH at a distance of more than 1.5 m.
CONCLUSIONS: Some local coinage and commonly found objects within a healthcare setting demonstrate ferromagnetic activity with projectile potential from a distance of more than 1 m. Patients and healthcare professionals should be cognisant of the risk associated with introducing these objects into the MRI scanning room.