Patients views on a new surveillance pathway involving allied non-medical staff for people with treated diabetic macular oedema and proliferative diabetic retinopathy

Abstract

Background/objective: To explore acceptability by patients and health care professionals of a new surveillance pathway for people with previously treated and stable diabetic macular oedema (DMO) and/or proliferative diabetic retinopathy (PDR).

Subject/methods: Structured discussions in 10 focus groups with patients; two with ophthalmic photographers/graders, and one with ophthalmologists, held across the UK as part of a large diagnostic accuracy study (EMERALD).

Results: The most prominent issues raised by patients concerned (i) expertise of the various professionals within clinic, (ii) quality of interactions with clinic professionals, especially the flow of information from professionals to patients, and (iii) wish to be treated holistically. Ophthalmologists suggested such issues could be best dealt with via a programme of patient education and tended to overlook deeper implications of patient concerns for the organisation of services.

Conclusion: For patients, the clinical service should not only include the identification and treatment of disease but also exchange of information, reassurance, and mitigation of anxiety. Alterations in the standard care pathway need to take account of such concerns and their implications, in addition to any assessments of 'efficiency' that may flow from changes in diagnostic technology, or the division of professional labour.

Fig. 1. Issues discussed in focus group (FG) Discussion 5.

The web was constructed using textual codes and numerical counts. Initially, each ‘turn’ (or phase of talk) in the FG transcript was linked to an identifiable speaker. Following that, the content of the turn was allocated to a node label or code (sometimes a number of codes). Node labels used included ‘my diabetes’, ‘injections’, ‘eye test’, ‘virtual clinic’, ‘the doctor’, ‘nurse’, ‘photographer’, and so forth. A simple count of the number of times that a specific speaker could be linked to a code, and the number of times that one code was associated with another in the same turn, was subsequently used as the basis for the construction of a 20 × 20 square matrix. The matrix was then integrated into social network software (using Pajek [23]) to generate a graphical representation of the discussion. Within the graph, node size reflects the number of turns that an individual speaker took during the meeting, or the number of times that an issue was referred to. The thickness of the links between nodes (the arcs) reflects the number of times that any one code was associated with another in the responses of participants. Because the diagram was generated using a Fruchterman–Reingold projection, distances between nodes are suggestive of the closeness (or otherwise) of the links between them (unfortunately, overlapping P2–P4 nodes, had to be separated manually to enhance clarity). Given large variations in the node and arc size, the counts were scaled using a square root transformation. ANX anxiety, AI artificial intelligence for detecting change in retina, DIABETES My diabetes, DRIVE Car Driving, THE DOC Consultant; FEEDBAK Information and results for ‘me’, FOTOG Photographer, INJECT Injections, LAMPEX Slit-lamp exam with doctor, OPTOS Optos imager, VIRT CLINIC Virtual Consultation, WAIT Waiting during routine visits. Participants are labelled ‘Pn.’.

Fig. 2

Accumulation of ‘issues’ in 10 consecutive focus groups.