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| Name | Class |
|---|---|
| University of Plymouth | OTHER |
| Nuffield Trust | UNKNOWN |
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18 month study, funded by ESRC COVID-19 research fund. The aim is to explore and support the rapid shift from face-to-face to remote (telephone and video) conversations in primary care. There are three components: a study of clinical interactions and decision making (micro); four locality-based organisational case studies of new models of care (meso); abd a a study of how digital innovation can support NHS infrastructure and vice versa (macro).
18 month study, funded by ESRC COVID-19 research fund. The aim is to explore and support the rapid shift from face-to-face to remote (telephone and video) conversations in primary care. There are three components: a study of clinical interactions and decision making (micro); four locality-based organisational case studies of new models of care (meso); abd a a study of how digital innovation can support NHS infrastructure and vice versa (macro). The methods are mainly qualitative (interviews, virtual ethnography, analysis of documents, micro-analysis of conversations) and are designed to inform action research.
Key deliverables:
At least two evidence-based assessment tools: qualitative (questions for remote assessment of breathlessness) and quantitative (a COVID-19-specific early warning score)
Transferable lessons about how to achieve rapid spread and scale-up, spread in real time through our extensive intersectoral networks
Strengthened infrastructure for supporting digital innovation in the NHS
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Remote assessment tools | Qualitative methods: semi-structured interviews for approx 40 front line clinical practitioners | ||
| RECAP early warning score | Development of disease specific early warning score, building on earlier work through literature review and NEWS2 score | ||
| Implementation/Scale up case studies | Study of implementation and scale up of remote-by-default at four different UK sites | ||
| Infrastructure strengthening | Theory and data driven change effort involving policymakers, regulators, professional bodies, industry, patients and citizens with a view to overcoming interacting issues impacting success of digital projects. |
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| Measure | Description | Time Frame |
|---|---|---|
| Remote COVID-19 Assessment in Primary Care (RECAP) Early warning score | A set of questions and a predictive tool built into electronic records, designed to distinguish people with suspected covid-19 who need to go to hospital from those who can safely be monitored at home. The final Remote COVID-19 Assessment in Primary Care (RECAP) Early warning score score divides people into 'green' (stay at home, self-monitor), amber (professional monitoring e.g., via virtual wards with home oximetry), or red (assess in person promptly). | 18 months |
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Inclusion Criteria:
Willing and able to give informed consent for participation
Aged 18 years or above
Staff involved in delivering remote-by-default services in the frontline or 'back offices'
Patients/carers who have crossed paths with primary care services during the Covid pandemic.
Pharmacy case studies:
Staff involved in delivering remote pharmacist consultation services in the frontline or 'back offices'
Patients/carers who have crossed paths with community pharmacy primary care services during the COVID-19 pandemic.
Inclusion criteria for video and telephone consultations
Patients who have remote primary care consultation regarding symptoms associated with COVID-19 and their clinicians (based in Oxford/Thames Valley) who have agreed to participate in the study
Inclusion criteria for focus groups
Patients that have experienced self-reported 'long Covid' symptoms (for patient only focus groups)
Clinicians that have experienced self-reported 'long Covid' symptoms (for clinician only focus groups)
Exclusion Criteria:
Patients or clinicians who are too ill to be interviewed
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Mixed methods study
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Oxford | Oxford | United Kingdom |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34468322 | Derived | Fiorentino F, Prociuk D, Espinosa Gonzalez AB, Neves AL, Husain L, Ramtale SC, Mi E, Mi E, Macartney J, Anand SN, Sherlock J, Saravanakumar K, Mayer E, de Lusignan S, Greenhalgh T, Delaney BC. An Early Warning Risk Prediction Tool (RECAP-V1) for Patients Diagnosed With COVID-19: Protocol for a Statistical Analysis Plan. JMIR Res Protoc. 2021 Oct 5;10(10):e30083. doi: 10.2196/30083. | |
| 33342437 |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot | Yes | No | No | Study Protocol | Mar 22, 2021 | Mar 29, 2022 | Prot_000.pdf |
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| ID | Term |
|---|---|
| D000086382 | COVID-19 |
| ID | Term |
|---|---|
| D011024 | Pneumonia, Viral |
| D011014 | Pneumonia |
| D012141 | Respiratory Tract Infections |
| D007239 | Infections |
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| Derived |
| Ladds E, Rushforth A, Wieringa S, Taylor S, Rayner C, Husain L, Greenhalgh T. Persistent symptoms after Covid-19: qualitative study of 114 "long Covid" patients and draft quality principles for services. BMC Health Serv Res. 2020 Dec 20;20(1):1144. doi: 10.1186/s12913-020-06001-y. |
| 33184088 | Derived | Greenhalgh T, Thompson P, Weiringa S, Neves AL, Husain L, Dunlop M, Rushforth A, Nunan D, de Lusignan S, Delaney B. What items should be included in an early warning score for remote assessment of suspected COVID-19? qualitative and Delphi study. BMJ Open. 2020 Nov 12;10(11):e042626. doi: 10.1136/bmjopen-2020-042626. |
| D014777 |
| Virus Diseases |
| D018352 | Coronavirus Infections |
| D003333 | Coronaviridae Infections |
| D030341 | Nidovirales Infections |
| D012327 | RNA Virus Infections |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |