Developing Multidisciplinary Models of Care in Rheumatology at University College London Hospital: 18 Months of Learning from Conception to Delivery and Beyond

Background/Aims The COVID-19 pandemic has placed unprecedented pressures on NHS departments, with demand rapidly outstripping capacity. The British Society for Rheumatology 'Rheumatology Workforce: a crisis in numbers (2021)' highlighted the need to provide innovative ways of delivering rheumatology specialist care. At University College London Hospitals (UCLH) we created a rheumatology multidisciplinary team (MDT) clinic to meet rising demands on our service. The aims of the Rheumatology MDT clinic were to: reduce new appointment/follow-up waiting times, increase clinic capacity, incorporate musculoskeletal (MSK) point of care ultrasound, reduce number of hospital visits and add value to each clinic encounter. Methods We ran a 6-month pilot, supported by our outpatient transformation team, incorporating a Rheumatology Advanced Practice Physiotherapist (APP), Clinical Nurse Specialist (CNS) and MSK ultrasound within a Consultant clinic. The success of the pilot helped secure funding for a further 12 months. Over 18 months we have implemented: APP/Consultant enhanced triage - up to 40% of referrals were appropriate for APP assessment, including regional MSK problems and back pain. This increased capacity for consultant-led appointments. Standardisation of time-lapse between CNS and consultant follow-up appointments to ensure appropriate spacing between patient encounters. Facilitated overbooking of urgent cases afforded by additional capacity provided by the APP. MSK ultrasound embedded in the clinic template. 'Zoom' patient education webinars facilitated by MDT members and wider disciplines e.g. dietetics, to empower self-management and reduce the administrative burden of patient emails/phone calls occurring outside the clinic. Patient participation sessions and feedback to help shape the service. Results During the 6-month pilot we reduced our waiting time for follow-up appointments from 9 months to 2. We now have capacity to book 1-2 urgent cases each week. Pre-MDT the average wait from consultant referral to physiotherapist appointment was 55 days. The MDT allows for same day assessment (reducing 2-3 patient journeys a clinic) and where suitable, facilitates discharge or onwards referral to the appropriate service. A dedicated MDT CNS has shortened treatment times, reduced email traffic between CNS and consultant and allows for same day, joint decision-making resulting in fewer appointments. Zoom webinar feedback has been positive. Patients value the broad expertise of allied health professionals which supports self-management. Embedding ultrasound allows for same day diagnostics, decreased referrals to radiology and reduced hospital visits. Conclusion Our MDT model has reduced waiting lists, decreased treatment delays and cut hospital attendances. Point of care ultrasound allows for same day decision making and abolishes the cost and diagnostic delay associated with referrals to radiology or outsourced providers. Shared decision-making adds value to outpatient attendances, which is reflected in patients' positive feedback. The MDT model maximises the existing workforce skill set by enhancing the APP and CNS role, allowing patients immediate access to their expertise.

Digital future beyond pandemic outbreak: systematic review of the impact of COVID-19 outbreak on digital psychology

Purpose: The globe has experienced a devastating COVID-19 pandemic, putting the planet under lockdown and causing social alienation. The near collapse of social and economic activities is disrupting the supply chain. Customer-required products were in low supply across the world. A slew of new digital firms springs up to fill the need during this time. This study aims to reach a holistic goal by better understanding customers' digitalisation behaviour. The first step is to review existing consumer digital psychology research to map this study's current knowledge of the pandemic's early and late phases and the impact of digital businesses on consumer behaviour. Finally, it provides lawmakers with a future agenda for limiting the digital psychology of consumers and enterprises. Design/methodology/approach: This study used the Scopus and Web of Science databases to extract records to follow the preferred reporting items for systematic reviews and meta-analyses statement. The final 57 papers were applied after the screening process. The digital environment, psychological digitalisation and behavioural changes were recognised as three primary classes based on a comprehensive examination of the previous literature. This study identified possible difficulties in earlier literature: the scarcity of collaborative and transdisciplinary research on digital psychology, which various academics have emphasised in the past. On the other hand, these investigations were primarily conducted in the psychological surroundings of technology users. Findings: According to this study, digital psychology has improved significantly during the pandemic and many new digital start-ups have arisen. This study also used digital research to create a framework for a pandemic strategic response plan to help minimise the current COVID-19 pandemic and prepare for future outbreaks. Originality/value: The study mapped existing literature on digital psychology alterations because of the novel COVID-19 outbreak. © 2023, Emerald Publishing Limited.

Consumers' Online Buying Behaviour during COVID-19 Pandemic Using Structural Equation Modeling

Due to the pandemic, businesses turned to alternatives and took up online marketing. E-marketing is a versatile tool for streamlining business processes, reducing managerial costs, reducing turnaround time, maintaining social distance, staying at home, protecting against viruses, and illuminating relationships with customers and business partners. Therefore, this research examined the factors affecting consumers' online purchase behaviour during the COVID-19 pandemic using partial least square structural equation modeling (PLS-SEM). Both quantitative and descriptive analysis methods were used. A standardized questionnaire was used to collect data from a sample of 200 local consumers in Bangladesh. A partial least square structural equation modeling (PLS-SEM) approach was used to evaluate the data and test the hypotheses. PLS-SEM showed that web design, price, administrative and product had a positive and significant relationship with consumers' online buying behaviour during the pandemic. This research adds theoretical contributions by evaluating the changes of consumers’ online buying behaviour during the COVID-19 pandemic. © All rights reserved 2022 Transnational Press London

CREATION of A MULTI-DISCIPLINARY TEAM (MDT) RHEUMATOLOGY CLINIC at UNIVERSITY COLLEGE LONDON HOSPITAL (UCLH) to TACKLE the BACKLOG of PATIENTS WAITING for TREATMENT AS A RESULT of the COVID-19 PANDEMIC

Background: Covid-19 has consumed hospital resources since January 2020. In the UK, routine care has been disrupted with an estimated 30 million fewer outpatient attendances (2020/21) and over 6 million patients waiting for consultant led care (1). The British Society for Rheumatology 'Rheumatology Workforce: a crisis in numbers (2021)' highlights the challenges facing National Health Service rheumatology departments in managing rising caseloads (2). In 2021, UCLH wait time for follow up rheumatology appointments was 9 months. We were inundated with patients requiring urgent treatment. Innovative ways of running outpatients were required which led to the formation of an MDT clinic. Objectives: Create a Rheumatology MDT clinic to: Reduce follow up time Increase clinic capacity Reduce number of hospital attendances Add value to each clinic encounter Methods: The consultant lead identifed an existing clinical nurse specialist (CNS) interested in supporting the MDT. With a UCLH Outpatient Transformation grant of £15,000 we recruited an advanced physiotherapy practitioner (APP) and administrator for a 6 month trial period. Managerial support was provided by the board. We met weekly to agree aims and allocate responsibilities. We did the following: Reviewed clinic lists for 6 months to identify duplicate appointments. Identifed patients with CNS and consultant follow up scheduled in a short time frame and cancelled unnecessary appointments. Reviewed the clinic list weekly to identify patients suitable for APP management. This allowed overbooking of urgent cases. Embedded hand ultrasound appointments in the clinic template. Created CNS 'Zoom' virtual drop-ins for routine enquiries to reduce the administrative burden of patient emails/phone calls occurring outside the clinic. Organised patient participation sessions to help shape the service and collected patient feedback questionnaires. Results: We reduced our waiting time for follow up appointments from 9 months to 2 months. Pre-MDT the average wait from consultant referral to physiotherapist appointment was 55 days. The MDT allows for same day assessment (reducing 2-3 patient journeys a clinic) and where suitable, facilitates discharge or onwards referral to the appropriate service i.e. pain management, hand therapy, APP-led hypermobility programme. A dedicated MDT CNS has shortened treatment times, reduced email traffic between CNS and consultant and allows for same day, joint decision making resulting in fewer appointments. Patients welcomed the Zoom sessions as an efficient, reliable method of raising concerns/queries. Our administrator helps to facilitate communication between patients and clinicians and streamline MDT processes. Embedding point of care ultrasound reduces hospital visits and enhances treatment decision making thereby reducing follow up attendances. Conclusion: Our MDT model has reduced waiting lists, decreased treatment delays and cut the number of hospital visits. Performing ultrasound in clinic helped prevent patients being sent for scans at private providers. This cost saving likely covers the APP, ensuring the project is close to cost neutral. Shared decision making added value to outpatient attendances, refected in patients positive feedback. The MDT enhances the role of APP and CNS, utilising their unique skill set. Administrative support is crucial, enhances team working and places added value on this often underappreciated role. We encourage other Rheumatology departments to adopt an MDT approach to tackle the backlog of patients awaiting treatment, add value to clinic encounters and maximise the skill set of clinicians involved in patient care.

A study on the challenges of predictive analysis on the outbreak of pandemic

With a rapid outbreak of corona virus pandemic disease 2019 (COVID-19), caused by a novel severe acute respiratory syndrome corona virus 2 (SARS-CoV-2), numerous measures are taken by the countries in order to contain the primary spread of the disease. The use of IoT and cloud for collecting and analysing data to prevent the spread of the disease through mobile applications was a major challenge. The conventional centralized cloud computing used for storing the victim’s data is encountering severe challenges, such as high latency and high energy consumption. Also, the possibility of occurrence of coverage hole can lead to the loss of actual data causing the system to provide erroneous information. This paper addresses a detailed review of various predictive models to identify the challenges in determining the outset of a pandemic like COVID and thereby health measures can be taken. © 2021 Universitatea de Vest Vasile Goldis din Arad. All rights reserved.

Psychological impact of covid-19 outbreak on nurses: A systematic review

The sudden exposure of COVID-19 has affected more than one hundred mil-lion people live and heath across the world. COVID-19 pandemic not only affected the lives of people, and it also affected the functions of Health care systems and also produced an overburden to the Health care systems. During the COVID-19 period, health care workers are affected by psychological problems, especially nurses working in the hospital and protecting the lives of everyone affected with COVID-19 infections. It is important to identify the issues that producing psychological problems among nurses, and it is necessary to support the nurses during their struggle. The researcher considering these issues, did a rapid systematic review to identify the percentage of nurses affected with psychological impact and causes for psychological impacts among nurses during COVID19 outbreaks. The researcher searched Google scholar and Science direct for selecting relevant research articles. The searched the studies based on the title, Study design, population, psychological problems of the nurses like anxiety, depression, fear, stress, sleeping problems, key words of nursing, psychological problems, and COVID-19. A PRISM protocol was used for selecting relevant research articles. According to the systematic review, the result shows that 26.4% of the nurses had depression, 40.8% had anxiety, and 42.7% had somatic symptoms, 50.5% had stress, and 91.2% had fear. The nurses are at risk of psychological problems and physical problems as being due to Covid-19. Effective intervention should be planned on nurses’ issues, and it helps to strengthen the mental health of nurses. © International Journal of Research in Pharmaceutical Sciences Production and Hosted by Pharmascope.org © 2020 ;All rights reserved.

Severe acute myopathy following SARS-CoV-2 infection: a case report and review of recent literature.

BACKGROUND: SARS-CoV2 virus could be potentially myopathic. Serum creatinine phosphokinase (CPK) is frequently found elevated in severe SARS-CoV2 infection, which indicates skeletal muscle damage precipitating limb weakness or even ventilatory failure. CASE PRESENTATION: We addressed such a patient in his forties presented with features of severe SARS-CoV2 pneumonia and high serum CPK. He developed severe sepsis and acute respiratory distress syndrome (ARDS) and received intravenous high dose corticosteroid and tocilizumab to counter SARS-CoV2 associated cytokine surge. After 10 days of mechanical ventilation (MV), weaning was unsuccessful albeit apparently clear lung fields, having additionally severe and symmetric limb muscle weakness. Ancillary investigations in addition with serum CPK, including electromyogram, muscle biopsy, and muscle magnetic resonance imaging (MRI) suggested acute myopathy possibly due to skeletal myositis. CONCLUSION: We wish to stress that myopathogenic medication in SARS-CoV2 pneumonia should be used with caution. Additionally, serum CPK could be a potential marker to predict respiratory failure in SARS-CoV2 pneumonia as skeletal myopathy affecting chest muscles may contribute ventilatory failure on top of oxygenation failure due to SARS-CoV2 pneumonia.

Survey on Forecasting the vulnerability of Covid 19 in Tamil Nadu

Predictive and analytic models for forecasting the vulnerability and recovery rate of patients who are affected by COVID 19 are made in this project for good analysis and better decision-making. In this project, linear regression (LR) a Machine Learning model is used to forecast the number of patients will get the infection in near future. By simulating SIRD model, the infection spread and recovery rate of the disease in a geographic region can be predicted. The vulnerability of the disease is checked by observing the transmission of disease over a period. In addition to this many info graphic models and graphs are created for easy understanding of data to get more insights about the disease. However, these prediction models enable us to make quick response of pandemic and to bring a conclusion to the disease. INDEX TERMS: Covid 19, data science, machine learning, prediction, analysis, pandemic, recovery and infection. © Published under licence by IOP Publishing Ltd.