Glaucoma referral refinement in Ireland: managing the sensitivity-specificity paradox in optometric practice

Impact of Community Eye Clinics (CEC) on Specialist Eye Clinic Referrals

PURPOSE

Community Eye Clinics (CEC) increase accessibility of specialist ophthalmic services in the community, reducing demand for tertiary eye services. This paper aims to evaluate the impact of CEC on first-visit referrals from Hougang Polyclinic (HOU) to Tan Tock Seng Hospital Ophthalmology Specialist Outpatient Clinic (SOC).

METHODS

A retrospective analysis was performed on first-visit referrals from Hougang Polyclinic (HOU) to Tan Tock Seng Hospital Ophthalmology Specialist Outpatient Clinic (SOC) over a similar 3-months period before and after the introduction of CEC in August 2018 (1 January to 31 March in 2018 and 2019, respectively). Data pertaining to patients' presenting complaints, referral reasons, final diagnoses, follow-up plans, and need for ophthalmic intervention were obtained.

RESULTS

We included 978 patients in our study. There was a 27.5% reduction in the number of first-visit referrals seen at SOC after the establishment of CEC. Patients were more likely to be referred on to sub-specialty eye clinics (10.8% vs. 12.9%, p= p = .304) and receive more ophthalmic interventions (15% vs. 16.3%, p = .066) than prior to CEC.

CONCLUSION

The CEC provides greater accessibility to eye care within the community. Optometrists are upskilled to manage patients with stable eye conditions, whilst eye specialists can provide timely care to the SOC for patients with more severe eye conditions.

Characterization of ophthalmology virtual visits during the COVID-19 pandemic

OBJECTIVES

To characterize the use of virtual visits, as well as compare the characteristics to in-person visits during the pandemic period.

METHODS

This retrospective study included patients who had virtual and in-person ophthalmology visits from March 19, 2020, to July 31, 2020, in a large multispecialty ophthalmic center. Exclusion criteria included patients aged less than 18 years old; canceled, incomplete, mislabelled, and duplicated visits. 2943 virtual and 56,174 in-person visits were identified. A random sample of 3000 in-person visits was created. Each visit was analyzed as an individual data point.

RESULTS

2,266 virtual visits (2,049 patients, 64.3% female, mean [SD] age 64.3 [16.6] years old) and 2590 in-person visits (2509 patients, 59.5% female, 65.9 [15.8] years old) were included. Most virtual visits were classified as comprehensive ophthalmology (34.6%), optometry-related (19.5%), and oculoplastics (13.0%). For in-person visits, the most common specialties were optometry (29.8%), comprehensive ophthalmology (23.9%), and retina and uveitis (17.3%). The most common diagnoses in the virtual group were from the eyelids, lacrimal system, and orbits group (26.9%), while in the in-person groups were choroid and retina conditions (19.3%).

CONCLUSIONS

Numerous ocular conditions were evaluated and managed through virtual visits, and external complaints and oculoplastic consults appear to be well-suited to the virtual format. Further studies focusing on visual outcomes and patient experience will be beneficial.

Clinical outcomes of the Centre for Eye Health: an intra-professional optometry-led collaborative eye care clinic in Australia

Clinical relevance: This novel clinical model is the first of its kind in Australia and was designed to help reduce unnecessary referrals into overburdened public systems by utilising pre-existing community-based resources.Background: The Centre for Eye Health (CFEH) is an intra-professional optometry-led care clinic offering an alternative pathway to traditional ophthalmology-based pathways (public hospital clinics or private practices) for 'at-risk' patients requiring ocular imaging, diagnostic and management services. This study evaluates the CFEH integrated eye-care model in the identification of chronic eye diseases within the community.Methods: A retrospective random clinical audit of over 750 medical records of patients referred to the CFEH between July 2016 and June 2019 was conducted. Demographics of patients, referral type, final diagnosis and recommended management plans were extracted from this subset. Clinic key performance indicators (referral turnaround time, and net cost per patient appointment) were also extracted.Results: Of the 755 referrals associated with the audited records, 77.4% resulted in the identification of patients with or at-risk of developing eye diseases with 73.5% of this cohort requiring ongoing monitoring at CFEH or referral to ophthalmology. Although the CFEH model is not designed to diagnose or manage acute conditions, 1.5% of patients in this pathway required same day ophthalmological or medical intervention. The cost per patient was equivalent to hospital eye departments costs.Conclusion: This integrated care pathway has the potential to reduce unnecessary referrals from optometrists to hospital ophthalmological service by offering a safe and effective alternate pathway. The majority of patients seen within this pathway were able to be monitored within optometry-led services. This is a unique clinical model utilising inter-professional referrals within optometry which has the potential to reduce preventable blindness within the community through the early detection of eye diseases.

Care pathways for glaucoma detection and monitoring in the UK

Glaucoma presents considerable challenges in providing clinically and cost-effective care pathways. While UK population screening is not seen as justifiable, arrangements for case finding have historically been considered relatively ineffective. Detection challenges include an undetected disease burden, whether from populations failing to access services or difficulties in delivering effective case-finding strategies, and a high false positive rate from referrals via traditional case finding pathways. The enhanced General Ophthalmic Service (GOS) in Scotland and locally commissioned glaucoma referral filtering services (GRFS) elsewhere have undoubtedly reduced false positive referrals, and there is emerging evidence of effectiveness of these pathways. At the same time, it is recognised that implementing GRFS does not intrinsically reduce the burden of undetected glaucoma and late presentation, and obvious challenges remain. In terms of diagnosis and monitoring, considerable growth in capacity remains essential, and non-medical health care professional (HCP) co-management and virtual clinics continue to be important solutions in offering requisite capacity. National guidelines, commissioning recommendations, and the Common Clinical Competency Framework have clarified requirements for such services, including recommendations on training and accreditation of HCPs. At the same time, the nature of consultant-delivered care and expectations on the glaucoma specialist's role has evolved alongside these developments. Despite progress in recent decades, given projected capacity requirements, further care pathways innovations appear mandated. While the timeline for implementing potential artificial intelligence innovations in streamlining care pathways is far from established, the glaucoma burden presents an expectation that such developments will need to be at the vanguard of future developments.

Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile

Background

Glaucoma is the leading cause of irreversible blindness worldwide. It is a heterogeneous group of conditions with a common optic neuropathy and associated loss of peripheral vision. Both over and under-diagnosis carry high costs in terms of healthcare spending and preventable blindness. The characteristic clinical feature of glaucoma is asymmetrical optic nerve rim narrowing, which is difficult for humans to quantify reliably. Strategies to improve and automate optic disc assessment are therefore needed to prevent sight loss.

Methods

We developed a novel glaucoma detection algorithm that segments and analyses colour photographs to quantify optic nerve rim consistency around the whole disc at 15-degree intervals. This provides a profile of the cup/disc ratio, in contrast to the vertical cup/disc ratio in common use. We introduce a spatial probabilistic model, to account for the optic nerve shape, we then use this model to derive a disc deformation index and a decision rule for glaucoma. We tested our algorithm on two separate image datasets (ORIGA and RIM-ONE).

Results

The spatial algorithm accurately distinguished glaucomatous and healthy discs on internal and external validation (AUROC 99.6% and 91.0% respectively). It achieves this using a dataset 100-times smaller than that required for deep learning algorithms, is flexible to the type of cup and disc segmentation (automated or semi-automated), utilises images with missing data, and is correlated with the disc size (p = 0.02) and the rim-to-disc at the narrowest rim (p<0.001, in external validation).

Discussion

The spatial probabilistic algorithm is highly accurate, highly data efficient and it extends to any imaging hardware in which the boundaries of cup and disc can be segmented, thus making the algorithm particularly applicable to research into disease mechanisms, and also glaucoma screening in low resource settings.