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Annals of Emergency Medicine ; 80(4 Supplement):S40, 2022.
Article in English | EMBASE | ID: covidwho-2176221


Study Objectives: To evaluate the impact of a general practitioner (GP) programme on low-acuity patient load (patient acuity scale P3 or P4) presenting at a participating emergency department (ED) of a regional public hospital in Singapore. Secondly, to analyse the appropriateness of participating GPs' referrals to ED based on programme criteria. Study Design/Methods: This is a descriptive observational study of a regionally implemented, government funded programme called GPFirst, from 2014 to 2019 (pre-COVID). In this programme, a patient attended to at a GPFirst clinic and subsequently referred to ED, will qualify for an ED attendance fee discount. Data are retrospectively collected from referral letters of GPs participating in the programme and the hospital's electronic health record system. Results/Findings: During the study period, 207 GPs were progressively enrolled. The annual number of low acuity attendances reduced from 62,213 in 2013 (pre-GPFirst) to 53,480 in 2019 even though the annual number of ED attendances increased gradually from 138,784 in 2014 to 141,072 in year 2019. Moreover, the annual proportion of low-acuity, self-referred cases decreased from 63.4% (39,425) in 2013 to 57.1% (30,528) in year 2019. The annual percentage of GPFirst referrals to the ED which meet referral appropriateness criteria increased from 94.5% (FY2014) to 97.6% (FY2019) and 98.0% (FY2020). Overall, the roll out of GPFirst appears to coincide with a reduction in low acuity patient load without compromising the appropriateness of GP referrals to the ED. Conclusion(s): A multi-faceted regional programme which included campaigned public education, regular GP continuous education, a supportive administrative team and financial incentive for patients, is able to reduce low acuity attendances. An ecosystem emerges which contributes to GPFirst's success. Further research is needed to evaluate safety and the effects of scaling this programme to a national level. No, authors do not have interests to disclose Copyright © 2022

2021 IEEE International Conference on Big Data, Big Data 2021 ; : 4381-4386, 2021.
Article in English | Scopus | ID: covidwho-1730902


This study aims to effectively analyze and visualize the concept to concept network derived from the COVID-19 Open Research Dataset (CORD-19) dataset, where we have more than 48,000 concepts with more than 300,000 relationships between concepts. In analyzing networks, we focus on finding relationship patterns between the coronavirus disease 2019 (COVID-19) concepts and other concepts. Given the node and edge datasets, we construct directional graphs and calculate all pair shortest paths based on multiple edge weight schemes. However, statistical metrics are not sufficient to identify specific relationships represented in the network. Therefore, we also propose a visual analytics approach to effectively understand the knowledge graph. Our highly interactive visual analytics allows users to effectively analyze the evolving graphs and (COVID-19) concept nodes and other nodes related to the COVID-19 nodes. We envision that this study will pave the path to develop strategies to provide more accurate and scalable predictive analysis on knowledge graphs related to CORD19 and other biomedical knowledge graphs. © 2021 IEEE.

Industrial Robot-the International Journal of Robotics Research and Application ; ahead-of-print(ahead-of-print):12, 2021.
Article in English | Web of Science | ID: covidwho-1550685


Purpose A harvesting robot is developed as part of kiwifruit industry automation in New Zealand. This kiwifruit harvester is currently not economically viable, as it drops and damages too many kiwifruit in the harvesting task due to the positional inaccuracy of the gripper. This is due to the difficulties in measuring the exact effective dimensions of the gripper from the manipulator. The purpose of this study is to obtain the effective gripper dimensions using kinematic calibration procedures. Design/methodology/approach A setup of a constraint plate with a dial gauge is proposed to acquire the calibration data. The constraint plate is positioned above the robot. The data is obtained by using a dial gauge and a permanent marker. The effective dimensions of the gripper are used as error parameters in the calibration process. Calibration is exercised by minimizing the difference between target positions and measured positions iteratively. Findings The robot with the obtained effective dimensions is tested in the field. It is found that the fruit drops due to positional inaccuracy of the gripper are greatly reduced after calibration. Practical implications The kiwifruit industry in New Zealand is growing rapidly and announced plans in 2017 to double global sales by 2025. This growth will put extra pressure on the labour supply for harvesting. Furthermore, the Covid pandemic and resulting border restrictions have dramatically reduced seasonal imported labour availability. A robotic system is a potential solution to address the labour shortages for harvesting kiwifruit. Originality/value For kiwifruit harvesting, the picking envelope is well above the robot;the experimental data points obtained by placing a constraint plate above the robot are at similar positions to the target positions of kiwifruit. Using this set of data points for calibration yields a good effect of obtaining the effective dimension of the gripper, which reduces the positional inaccuracy as shown in the field test results.