ABSTRACT
INTRODUCTION: Shielding aimed to protect those predicted to be at highest risk from COVID-19 and was uniquely implemented in the UK during the COVID-19 pandemic. Clinically extremely vulnerable people identified through algorithms and screening of routine National Health Service (NHS) data were individually and strongly advised to stay at home and strictly self-isolate even from others in their household. This study will generate a logic model of the intervention and evaluate the effects and costs of shielding to inform policy development and delivery during future pandemics. METHODS AND ANALYSIS: This is a quasiexperimental study undertaken in Wales where records for people who were identified for shielding were already anonymously linked into integrated data systems for public health decision-making. We will: interview policy-makers to understand rationale for shielding advice to inform analysis and interpretation of results; use anonymised individual-level data to select people identified for shielding advice in March 2020 and a matched cohort, from routine electronic health data sources, to compare outcomes; survey a stratified random sample of each group about activities and quality of life at 12 months; use routine and newly collected blood data to assess immunity; interview people who were identified for shielding and their carers and NHS staff who delivered healthcare during shielding, to explore compliance and experiences; collect healthcare resource use data to calculate implementation costs and cost-consequences. Our team includes people who were shielding, who used their experience to help design and deliver this study. ETHICS AND DISSEMINATION: The study has received approval from the Newcastle North Tyneside 2 Research Ethics Committee (IRAS 295050). We will disseminate results directly to UK government policy-makers, publish in peer-reviewed journals, present at scientific and policy conferences and share accessible summaries of results online and through public and patient networks.
Subject(s)
COVID-19 , State Medicine , Humans , Wales , Quality of Life , Pandemics , Patient ComplianceABSTRACT
BackgroundTRIM is an evaluation of the models used to triage and manage emergency ambulance service care for patients with suspected Covid-19 during the first wave of the pandemic in 2020. We aimed to understand experiences and concerns of clinical and managerial staff about implementation of triage protocols in call centre and on-scene.MethodsResearch paramedics in four study sites across England interviewed purposively selected stakeholders from ambulance services (call handlers, clinical advisors in call centres, clinicians providing emergency response, managers) and ED clinical staff from one hospital per site. Interviews (n=23) were conducted remotely using MS Teams, recorded, and transcribed in full. Analysis generated themes from the implicit and explicit ideas within participants’ accounts, following the six stages of analysis described by Braun and Clarke, conducted by a group of researchers and PPI partners working together.ResultsWe identified the following themes:Constantly changing guidelines – at some points, updates several times a dayThe ambulance service as part of the wider healthcare system - changes in other parts of the healthcare system left ambulance services as the default optionPeaks and troughs of demand - demand fluctuated greatly over time, with workload varying across the ambulance service, including an increased role for clinical advisorsA stretched system - resources to respond to patient demand were stretched thinner by staff sickness and isolation, longer job times, and increased handover delays at EDEmotional load of responding to the pandemic - particularly for call centre staffDoing the best they can in the face of uncertainty - in the face of a rapidly evolving situation unlike any which ambulance services had faced beforeDiscussionImplementing triage protocols in response to the Covid-19 pandemic was a complex and process which had to be actively managed by a range of front line staff, dealing with external pressures and a heavy emotional load.
ABSTRACT
Introduction Shielding aimed to protect those predicted to be at highest risk from COVID-19 and was uniquely implemented in the UK during the COVID-19 pandemic. Clinically extremely vulnerable people identified through algorithms and screening of routine National Health Service (NHS) data were individually and strongly advised to stay at home and strictly self-isolate even from others in their household. This study will generate a logic model of the intervention and evaluate the effects and costs of shielding to inform policy development and delivery during future pandemics. Methods and analysis This is a quasiexperimental study undertaken in Wales where records for people who were identified for shielding were already anonymously linked into integrated data systems for public health decision-making. We will: interview policy-makers to understand rationale for shielding advice to inform analysis and interpretation of results;use anonymised individual-level data to select people identified for shielding advice in March 2020 and a matched cohort, from routine electronic health data sources, to compare outcomes;survey a stratified random sample of each group about activities and quality of life at 12 months;use routine and newly collected blood data to assess immunity;interview people who were identified for shielding and their carers and NHS staff who delivered healthcare during shielding, to explore compliance and experiences;collect healthcare resource use data to calculate implementation costs and cost–consequences. Our team includes people who were shielding, who used their experience to help design and deliver this study. Ethics and dissemination The study has received approval from the Newcastle North Tyneside 2 Research Ethics Committee (IRAS 295050). We will disseminate results directly to UK government policy-makers, publish in peer-reviewed journals, present at scientific and policy conferences and share accessible summaries of results online and through public and patient networks.
ABSTRACT
OBJECTIVES: During the first wave of the COVID-19 pandemic in the United Kingdom (UK), to describe volume and pattern of calls to emergency ambulance services, proportion of calls where an ambulance was dispatched, proportion conveyed to hospital, and features of triage used. METHODS: Semistructured electronic survey of all UK ambulance services (n = 13) and a request for routine service data on weekly call volumes for 22 weeks (February 1-July 3, 2020). Questionnaires and data request were emailed to chief executives and research leads followed by email and telephone reminders. The routine data were analyzed using descriptive statistics, and questionnaire data using thematic analysis. RESULTS: Completed questionnaires were received from 12 services. Call volume varied widely between services, with a UK peak at week 7 at 13.1% above baseline (service range -0.5% to +31.4%). All services ended the study period with a lower call volume than at baseline (service range -3.7% to -25.5%). Suspected COVID-19 calls across the UK totaled 604,146 (13.5% of all calls), with wide variation between services (service range 3.7% to 25.7%), and in service peaks of 11.4% to 44.5%. Ambulances were dispatched to 478,638 (79.2%) of these calls (service range 59.0% to 100.0%), with 262,547 (43.5%) resulting in conveyance to hospital (service range 32.0% to 53.9%). Triage models varied between services and over time. Two primary call triage systems were in use across the UK. There were a large number of products and arrangements used for secondary triage, with services using paramedics, nurses, and doctors to support decision making in the call center and on scene. Frequent changes to triage processes took place. CONCLUSIONS: Call volumes were highly variable. Case mix and workload changed significantly as COVID-19 calls displaced other calls. Triage models and prehospital outcomes varied between services. We urgently need to understand safety and effectiveness of triage models to inform care during further waves and pandemics.