scholarly journals P1‐3: Prescribing oxygen: An audit of prescribing and delivery practices at two tertiary hospitals in Melbourne, Australia

Respirology ◽  
2021 ◽  
Vol 26 (S3) ◽  
pp. 70-70
2020 ◽  
Vol 3 ◽  
pp. 36-39
Author(s):  
Samson O. Paulinus ◽  
Benjamin E. Udoh ◽  
Bassey E. Archibong ◽  
Akpama E. Egong ◽  
Akwa E. Erim ◽  
...  

Objective: Physicians who often request for computed tomography (CT) scan examinations are expected to have sound knowledge of radiation exposure (risks) to patients in line with the basic radiation protection principles according to the International Commission on Radiological Protection (ICRP), the Protection of Persons Undergoing Medical Exposure or Treatment (POPUMET), and the Ionizing Radiation (Medical Exposure) Regulations (IR(ME)R). The aim is to assess the level of requesting physicians’ knowledge of ionizing radiation from CT scan examinations in two Nigerian tertiary hospitals. Materials and Methods: An 18-item-based questionnaire was distributed to 141 practicing medical doctors, excluding radiologists with work experience from 0 to >16 years in two major teaching hospitals in Nigeria with a return rate of 69%, using a voluntary sampling technique. Results: The results showed that 25% of the respondents identified CT thorax, abdomen, and pelvis examination as having the highest radiation risk, while 22% said that it was a conventional chest X-ray. Furthermore, 14% concluded that CT head had the highest risk while 9% gave their answer to be conventional abdominal X-ray. In addition, 17% inferred that magnetic resonance imaging had the highest radiation risk while 11% had no idea. Furthermore, 25.5% of the respondents have had training on ionizing radiation from CT scan examinations while 74.5% had no training. Majority (90%) of the respondents were not aware of the ICRP guidelines for requesting investigations with very little (<3%) or no knowledge (0%) on the POPUMET and the IR(ME)R respectively. Conclusion: There is low level of knowledge of ionizing radiation from CT scan examinations among requesting physicians in the study locations.


2020 ◽  
Author(s):  
Jing Liu ◽  
Hong Shan ◽  
Changli Tu ◽  
Meizhu Chen ◽  
Xiujuan Qu ◽  
...  

UNSTRUCTURED Background: Since December 2019, Coronavirus Disease 2019 (COVID-19) emerged in Wuhan city and rapidly spread throughout China. Facing this kind of public health emergency, an efficient, fast and group communication method is needed. Method: As a director of the department Pulmonary and Critical Care Medicine in a tertiary hospitals, which is the only designated one for diagnosis and treatment of COVID-19 in a medium-sized city, I analyzed and summarized the “group function” of WeChat (Weixin, micro-message) App in working about COVID-19. Results: By February 16, 2020, we have completed 1,526 citywide consultations and treatment of 322 inpatients, including 97 patients diagnosed with COVID-19, with the help of 12 WeChat groups by handy. The advantages of WeChat group are as follows: 1. Work efficiency can be improved greatly, saving labor costs. 2. Accurate and intuitive information can be gotten fast and timely, avoiding close contacting with COVID-19 patients. 3. Data and message in WeChat groups can be saved, arranged and reviewed at any time. Conclusions: The “group function” in WeChat App plays a greater role in the public health emergent work about management, diagnosis and treatment of COVID-19.


2020 ◽  
Author(s):  
Ke Zeng ◽  
Weiguo Zhu ◽  
Caiyou Wang ◽  
Liyan Zhu

BACKGROUND The rapid spread of COVID-19 has created a severe challenge to China’s healthcare system. Hospitals across the country reacted quickly under the leadership of the Chinese government and implemented a range of informatization measures to effectively respond to the COVID-19. OBJECTIVE To understand the impact of the pandemic on the medical business of Chinese hospitals and the difficulties faced by hospital informatization construction. To discuss the application of hospital informatization measures during the COVID-19 pandemic. To summarize the practical experience of hospitals using information technology to fight the pandemic. METHODS Performing a cross-sectional on-line questionnaire survey in Chinese hospitals, of which the participants are invited including hospital information staff, hospital administrators, medical staff, etc. Statistical analyzing the collected data by using SPSS version 24. RESULTS A total of 804 valid questionnaires (88.45%) are collected in this study from 30 provinces in mainland China, of which 731 (90.92%) were filled out by hospital information staff. 473 (58.83%) hospitals are tertiary hospitals while the remaining 331 (41.17%) are secondary hospitals. The majority hospitals (82.46%) had a drop in their business volume during the pandemic and a more substantial drop is found in tertiary hospitals. 70.40% (n=566) of hospitals have upgraded or modified their information systems in response to the epidemic. The proportion of tertiary hospitals that upgraded or modified systems is significantly higher than that of secondary hospitals. Internet hospital consultation (70.52%), pre-check and triage (62.56%), telemedicine (60.32%), health QR code (57.71%), and telecommuting (50.87%) are the most used informatization anti-pandemic measures. There are obvious differences in the application of information measures between tertiary hospitals and secondary hospitals. Among these measures, most of them (41.17%) are aiming at serving patients and most of them (62.38%) are universal which continue to be used after pandemic. The informatization measures are mostly used to control the source of infection (48.19%), such as health QR Code, etc. During the pandemic, the main difficulties faced by the hospital information department are “information construction projects are hindered” (58.96%) and “increased difficulty in ensuring network information security” (58.58%). There are significant differences in this issue between tertiary hospitals and secondary hospitals. The shortcomings of hospital informatization that should be made up for are “shorten patient consultation time and optimize consultation process” (72.51%), “Ensure network information security” (72.14%) and “build internet hospital consultations platform” (59.95%). CONCLUSIONS A significant number of innovative medical information technology have been used and played a significant role in all phases of COVID-19 prevention and control in China. Since the COVID-19 brought many challenges and difficulties for informatization work, hospitals need to constantly improve their own information technology skills to respond to public health emergencies that arise at any moment.


2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Felix Fleissner ◽  
Alexandru Mogaldea ◽  
Andreas Martens ◽  
Ruslan Natanov ◽  
Stefan Rümke ◽  
...  

Abstract Background Extracorporeal life support (ECLS) is an established tool to stabilize severely ill patients with therapy-refractory hemodynamic or respiratory failure. Recently, we established a mobile ECLS retrieval service at our institution. However, data on the outcome of patients receiving ECLS at outside hospitals for transportation into tertiary hospitals is still sparse. Methods We have analyzed all patients receiving ECLS in outside hospitals (Transport group, TG) prior to transportation to our institution and compared the outcome to our in-house ECLS experience (Home Group, HG). Results Between 2012 and 2018, we performed 978 ECLS implantations, 243 of which were performed on-site in tertiary hospitals for ECLS supported transportation. Significantly more veno-venous systems were implanted in TG (n = 129 (53%) vs. n = 327 (45%), p = 0.012). Indication for ECLS support differed between the groups, with more pneumonia; acute respiratory distress syndromes in the TG group and of course, more postcardiotomy patients in HG. Mean age was 47 (± 20) (HG) vs. 48 (± 18) (TG) years, p = 0.477 with no change over time. No differences were seen in ECLS support time (8.03 days ±8.19 days HG vs 7.81 days ±6.71 days TG, p = 0.675). 30-day mortality (n = 379 (52%) (HG) vs. n = 119 (49%) (TG) p = 0.265) and death on ECLS support (n = 322 (44%) (HG) vs. n = 97 (40%) TG, p = 0.162) were comparable between the two groups, despite a more severe SAVE score in the v-a TG (HG: − 1.56 (± 4.73) vs. TG -3.93 (± 4.22) p < 0.001). Mortality rates did not change significantly over the years. Multivariate risk analysis revealed Influenza, Peak Insp. Pressure at implantation, pO2/FiO2 ratio and ECLS Score (SAVE/RESP) as well as ECLS support time to be independent risk factors for mortality. Conclusion Mobile ECLS support is a tremendous challenge. However, it is justified to offer 24 h/7d ECLS standby for secondary and primary hospitals as a tertiary hospital. Increasing indications and total numbers for ECLS support raise the need for further studies to evaluate outcome in these patients.


2021 ◽  
Vol 20 ◽  
pp. 153303382110246
Author(s):  
Jihwan Park ◽  
Mi Jung Rho ◽  
Hyong Woo Moon ◽  
Jaewon Kim ◽  
Chanjung Lee ◽  
...  

Objectives: To develop a model to predict biochemical recurrence (BCR) after radical prostatectomy (RP), using artificial intelligence (AI) techniques. Patients and Methods: This study collected data from 7,128 patients with prostate cancer (PCa) who received RP at 3 tertiary hospitals. After preprocessing, we used the data of 6,755 cases to generate the BCR prediction model. There were 16 input variables with BCR as the outcome variable. We used a random forest to develop the model. Several sampling techniques were used to address class imbalances. Results: We achieved good performance using a random forest with synthetic minority oversampling technique (SMOTE) using Tomek links, edited nearest neighbors (ENN), and random oversampling: accuracy = 96.59%, recall = 95.49%, precision = 97.66%, F1 score = 96.59%, and ROC AUC = 98.83%. Conclusion: We developed a BCR prediction model for RP. The Dr. Answer AI project, which was developed based on our BCR prediction model, helps physicians and patients to make treatment decisions in the clinical follow-up process as a clinical decision support system.


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