Clinical trial NCT04435041: Remote-by-Default Care in the COVID-19 Pandemic
Official title: Remote-by-Default Care in the COVID-19 Pandemic: Addressing the Micro-, Meso-, and Macro-level Challenges of a Radical New Service Model
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: COVID-19
Lead sponsor: University of Oxford
Sponsor class: OTHER
Collaborators: name: University of Plymouth
name: Nuffield Trust
First posted: 2020-06-17
Enrollment: 103
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: OTHER
Time perspective: OTHER
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Mixed methods study

Brief summary: 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).

Detailed description: 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

Eligibility criteria: Inclusion Criteria:

* Inclusion criteria for interviews

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

-

Primary outcomes:
measure: Remote COVID-19 Assessment in Primary Care (RECAP) Early warning score
timeFrame: 18 months
Secondary outcomes:
Other outcomes:
Locations:
city: Oxford
country: United Kingdom
facility: University of Oxford
Study officials:
References:
citation: 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.
citation: 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.
citation: 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.