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IMPACTS OF COVID-19 ON INTERNATIONAL STUDENTS AND THE FUTURE OF STUDENT MOBILITY: International Perspectives and Experiences ; : 172-183, 2022.
Article in English | Web of Science | ID: covidwho-2156775
Pediatrics ; 149, 2022.
Article in English | EMBASE | ID: covidwho-2003451


Purpose/Objectives: 1) To design and implement a clinical pathway that delineates evidence-based recommendations of screening for newly arrived immigrant children in an academic primary care setting. 2) To improve adherence to recommended biomedical and infectious screening by providers caring for newly arrived immigrant children. 3) To evaluate the effectiveness of the clinical pathway and adjunct tools to support uptake and adherence to the pathway with a goal of achieving 90% adherence to key indicators in 18 months. Design/Methods: A clinical pathway for primary care of newly arrived immigrant children was developed and implemented based on existing evidence from immigrant and refugee populations, delineating recommended psychosocial, developmental, biomedical, and infectious screenings by region of origin. Adjuncts to support uptake were implemented, including an EMR order-set and note template. Faculty and resident education to the pathway was conducted in person and with pre-recorded educational presentations. Indicators of adherence were defined as the percentage of patients who obtained the recommended screening tests according to their world region of origin. Results: A total of 301 newly arrived immigrant patients were seen at the clinics during our observation period (from Dec 2018-May 2021);190 (63%) were seen after the rollout of our main interventions in August 2019, and 70 (23%) were seen after the onset of the COVID-19 pandemic in March 2020. We observed an improvement in the % of patients who obtained lead level, Complete Blood Count (CBC) with differential, Strongyloides, and Tuberculosis screening on their first visit in the U.S. following the introduction of the clinical pathway and order-set (Images 1 and 2). There have been six consecutive points above the mean in the case of lead level and Tuberculosis screening. In the case of Strongyloides screening, a mean shift was observed months after the implementation of the pathway. On average, 74% of the ordered screening tests for these patients were entered using the order-set. The COVID-19 pandemic impacted the number of new patients in both clinics from April 2020-Sep 2020. Periodical reminders and continuous education to providers also have proved beneficial to our goals. Conclusion/Discussion: Implementation of a clinical pathway for the care of newly arrived immigrant children resulted in improvements in adherence to region-specific recommendations for biomedical and infectious screenings;specifically for lead, CBC with differential, Strongyloides, and Tuberculosis screening. Implementation of an order-set embedded in the electronic medical records system was a successful strategy to facilitate adherence. Drastic reductions in the number of new immigrant children seeking care during the initial months of the COVID-19 pandemic raised concerns about access barriers for this vulnerable population and required strategies to remind clinicians about the use of the pathway as numbers of new immigrant patients return to baseline.

4th International Conference on Machine Learning and Machine Intelligence, MLMI 2021 ; : 65-70, 2021.
Article in English | Scopus | ID: covidwho-1635884


SVM has been used in several studies in bioinformatics concerning disease classification. Currently, the world is experiencing a pandemic called COVID-19 which is a contagious disease that can be transferred through droplets in the air from the infected person. Individuals who carry this virus demand to be diagnosed promptly to prevent the virus from spreading which can cause danger to human lives, but COVID-19 testing kits were not easily accessible, and laboratory tests cannot be done right away. In line with this, the authors utilized Support Vector Machine supervised machine learning algorithm in building a model to analyze and predict the presence of COVID-19 in a person based on symptoms experienced by the person. Hyperparameters such as degree, cost, gamma, and kernels including Linear, Radial, Polynomial, and Sigmoid were tuned through R Studio to attain the best possible performance of the model. The model was evaluated using 10 - fold cross validation and results show that polynomial kernel with optimized hyperparameters yielded the best accuracy of 98.02%. © 2021 ACM.

Critical Care Medicine ; 49(1 SUPPL 1):42, 2021.
Article in English | EMBASE | ID: covidwho-1193803


INTRODUCTION: COVID-19 2020 pandemic with New York City (NYC) as the epicenter necessitated an unprecedented increase in critical care capacity and development of institutional guidelines for care. We describe our drastic increased ICU capacity and how we created and disseminated our guidelines. We hope our experiences help others manage their COVID-19 peaks. METHODS: Mount Sinai Hospital System includes a medical school and eight campuses, the largest being Mount Sinai Hospital (MSH). Since 2013, MSH had system-wide staffing models, cross credentialed staff, and combined leadership. MSH has and Institute for Critical Care Medicine (ICCM) that includes seven adult ICUs, 45 critical care faculty, rapid response team (RRT), vascular access team (VAS), difficult airway team (DART), patient safety quality team (PSQ), clinical research team, and post-ICU recovery clinic. ICCM coordinated COVID-19 critical care response within MSHS. ICCM, Emergency Medicine, Anesthesiology, and Infection Prevention helped develop systemwide guidelines on our COVID-19 website accessible to all hospital employees. RESULTS: MSH expanded from 1139-beds, 104 ICU beds, to 1453 beds, 235 ICU beds during the COVID-19 peak. CONCLUSIONS: MSH's response to COVID-19 surge by expanding critical care bed capacity from 104 to over 200 ICU beds required teamwork across disciplines. We developed new guidelines for airway management, cardiac arrest, anticoagulation, vascular access, and proning that helped streamline workflow and accommodate the surge in critically ill patients. Non-ICU services and staff were deployed to augment the critical care work force and open new critical care units by leveraging a tiered staffing model. This approach to rapidly expanding bed availability and staffing across the system was made possible by the collaboration between ICCM, emergency department, anesthesia department, and infection prevention, and helped to provide the best care for our patients and saved lives.