ArticlePloS one2026
Preferences for community-based asynchronous-review eye clinics in the UK: A discrete choice experiment among patients, healthcare professionals, and the public.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The United Kingdom government's 10 Year Health Plan for England sets out three shifts for a future-ready health service in England: shifting care from hospitals to communities, harnessing technology in health and care, and prioritising prevention over treatment. In this spirit, a large eye-hospital network in central London piloted a community-based, technician-led, asynchronous/virtual-review clinic to monitor stable chronic eye conditions and reduce avoidable harms, a model which could supplement traditional clinician-led services. Understanding stakeholder preferences around services is crucial for future planning and scaling. This paper describes a national survey examining key attributes for services monitoring chronic eye disease and calculating their relative importance for key stakeholders in the UK. We developed a discrete choice experiment (DCE) and distributed it electronically across the UK, targeting ophthalmology patients, healthcare professionals (HCP), and the public, asking all to respond from a patient's perspective due to logistical and analytical considerations. Conditional logistic regression estimated the strength of stated preferences and trade-offs stakeholders would make between attributes, expressed as willingness to wait (WTW) longer than planned for their next appointment and willingness to travel (WTT) longer to the appointment location. Other attributes included whether a clinician or technician led the tests and how results were communicated (combined into single attribute reflecting service realities), venue accessibility by public transport, and parking. We received 389 responses, and the attribute describing who the patient saw and how results were received was the most important for all three groups. Compared to seeing a clinician with same-day results, respondents required appointment delay reductions of 6.27 months (95%CI 4.52-8.03) or travel reductions of 153 minutes (95%CI 88-219) if seeing a technician and receiving results by post, or smaller reductions if seeing technician then receiving results by phone. Differences across the respondent groups are discussed. This work suggests that technician-led asynchronous-review ophthalmology services could acceptably supplement clinician-led models, provided they improve appointment delays and reduce travel time. Therefore, service designers should align with these preferences when planning new services.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.