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Co-designing and Evaluating a Real-world Implementation Model for Remote Consultation with Vision Self-testing.

Co-designing and Evaluating a Real-world Implementation Model for Remote Consultation with Vision Self-testing. the ReVise Study.

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05941182
Acronym
ReVise
Enrollment
200
Registered
2023-07-12
Start date
2023-09-03
Completion date
2026-02-02
Last updated
2025-02-12

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Ophthalmic Disorders

Keywords

Remote consultation, visual acuity testing, self-testing applications, home-testing applications

Brief summary

This study aims to involve the public, patients and National Health Service (NHS) staff in co-designing a scalable, inclusive and sustainable implementation model for ophthalmic remote consultation with vision self-testing (the intervention). The main study questions are: What are the barriers to uptake of the intervention and how can these be mitigated by the design of the implementation model. How do implementation outcome measures compare before and after real world application of the model.

Detailed description

Background: Increasing demand for hospital eyecare and limited resources makes improved uptake of remote consultation essential. Unsupported workflows and the lack of an accurate visual acuity (VA) assessment are recognised factors limiting its uptake by ophthalmologists. Difficulties with accessing and trusting technology are widely reported barriers for patients. A novel implementation model of remote consultation with vision selftesting (using the DigiVis app in this study) which is co-designed with stakeholders could support and promote its use. Methods: This mixed methodology, highly pragmatic study will take place in three large NHS eye departments (in Cambridge, Peterborough and Manchester) with high levels of age, ethnic, cultural and socio-economic diversity. Qualitative and quantitative data from semi-structured interviews, ethnographic field notes in the community and the Planning and Evaluating Remote Consultation Services (PERCS) framework in hospital-based patient and staff focus groups will identify implementation challenges. An implementation model to mitigate these challenges will be co-designed with stakeholders and put into operation. Patients will be allocated to the intervention pathway at their clinician's discretion and with their implied agreement in accepting the appointment. Implementation and service outcomes will be assessed using the Practical, Robust, Implementation and Sustainability Model of the Reach Effectiveness Adoption Implementation Maintenance (PRISM RE-AIM) framework before, during and after 14 months of operation, enabling adaptation of the model. Online questionnaires of approximately 100 patients assigned to the intervention by their clinician, will enable quantitative analysis of change in patients' perceived attributes of the e-health innovation scores before and after its use. Online questionnaires will enable quantitative changes in the Normalisation Process (NoMAD) scores of approximately 100 staff before and after implementation of the co-deisgned model to be analysed by descriptive statistics. The optimised implementation model for the intervention, when scaled up, could reach over 3 million patients a year and alleviate some of the pressures on United Kingdom (UK) ophthalmology services. Dissemination of the model and toolkit via websites, publications and presentations to patients, clinicians, service managers and policy makers will supportthe adoption of remote consultations using self-assessment apps, like DigiVis. This could not only improve patient care in the NHS but improve access to eyecare and vision screening for rural communities internationally.

Interventions

Before and after online questionnaires

Sponsors

Manchester University NHS Foundation Trust
CollaboratorOTHER_GOV
University of East Anglia
CollaboratorOTHER
National Institute for Health Research, United Kingdom
CollaboratorOTHER_GOV
Cambridge University Hospitals NHS Foundation Trust
Lead SponsorOTHER

Study design

Observational model
CASE_ONLY
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
4 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

* Patients 4 years and older scheduled by their clinician for a follow up remote eye clinic consultation following an initial face-to face consultation.

Exclusion criteria

-Patients refusing remote consultation or converted to a face-to-face appointment following scheduling.

Design outcomes

Primary

MeasureTime frameDescription
Change in patient reported perceived attributes of e-health innovation score30 monthsChange in the perceived attributes of e-health innovation score before and after experiencing remote consultation and self-testing of vision. This questionnaire results in a summated score for each patient with a minimum of 0 and a maximum of 100. Change in overall score before and after the remote consultation will be calculated for each patient and a mean change in score calculated. A higher magnitude positive change in score reflects an improved perception of the technology after the experience.
Change in staff reported normalisation measure of the technology (NoMAD) score30 monthsChange in the NoMAD score before and after implementation of the remote consultation and self-testing of vision.This questionnaire results in a summated score for each patient with a minimum of 0 and a maximum of 100. Change in overall score before and after service implementation the remote consultation will be calculated for each member of staff and a mean change in score calculated. A higher magnitude positive change in score reflects improved normalisation and acceptance of the technology after implementation.

Countries

United Kingdom

Contacts

Primary ContactLouise Allen
Louise.allen47@nhs.net01223254665
Backup ContactMahmoud Hassan
mahmoud.hassan7@nhs.net01223254665

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026