Delivery of virtual care increased throughout the COVID-19 pandemic and persisted after physical distancing measures ended. However, little is known about how to measure the quality of virtual care, as current measures focus on in-person care and may not apply to a virtual context. This scoping review aims to understand the connections between virtual care modalities used with ambulatory patient populations and quality measures across the Quintuple Aim (provider experience, patient experience, per capita cost, population health and health equity).

Virtual care was considered any interaction between patients and/or their circle of care occurring remotely using any form of information technology. Five databases (MEDLINE, Embase, PsycInfo, Cochrane Library, JBI) and grey literature sources (11 websites, 3 search engines) were searched from 2015 to June 2021 and again in August 2022 for publications that analysed virtual care in ambulatory settings. Indicators were extracted, double-coded into the Quintuple Aim framework; patient and provider experience indicators were further categorised based on the National Academy of Medicine quality framework (safety, effectiveness, patient-centredness, timeliness, efficiency and equity). Sustainability was added to capture the potential for continued use of virtual care.

13 504 citations were double-screened resulting in 631 full-text articles, 66 of which were included. Common modalities included video or audio visits (n=43), remote monitoring (n=11) and mobile applications (n=11). The most common quality indicators were related to patient experience (n=58 articles), followed by provider experience (n=25 articles), population health outcomes (n=23 articles) and health system costs (n=19 articles).

The connections between virtual care modalities and quality domains identified here can inform clinicians, administrators and other decision-makers how to monitor the quality of virtual care and provide insights into gaps in current quality measures. The next steps include the development of a balanced scorecard of virtual care quality indicators for ambulatory settings to inform quality improvement.

The English National Health Service (NHS) Diabetic Eye Screening Programme (DESP) performs around 2.3 million eye screening appointments annually, generating approximately 13 million retinal images that are graded by humans for the presence or severity of diabetic retinopathy. Previous research has shown that automated retinal image analysis systems, including artificial intelligence (AI), can identify images with no disease from those with diabetic retinopathy as safely and effectively as human graders, and could significantly reduce the workload for human graders. Some algorithms can also determine the level of severity of the retinopathy with similar performance to humans. There is a need to examine perceptions and concerns surrounding AI-assisted eye-screening among people living with diabetes and NHS staff, if AI was to be introduced into the DESP, to identify factors that may influence acceptance of this technology.

People living with diabetes and staff from the North East London (NEL) NHS DESP were invited to participate in two respective focus groups to codesign two online surveys exploring their perceptions and concerns around the potential introduction of AI-assisted screening.

Focus group participants were representative of the local population in terms of ages and ethnicity. Participants’ feedback was taken into consideration to update surveys which were circulated for further feedback. Surveys will be piloted at the NEL DESP and followed by semistructured interviews to assess accessibility, usability and to validate the surveys.

Validated surveys will be distributed by other NHS DESP sites, and also via patient groups on social media, relevant charities and the British Association of Retinal Screeners. Post-survey evaluative interviews will be undertaken among those who consent to participate in further research.

Ethical approval has been obtained by the NHS Research Ethics Committee (IRAS ID: 316631). Survey results will be shared and discussed with focus groups to facilitate preparation of findings for publication and to inform codesign of outreach activities to address concerns and perceptions identified.