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Background <p>Outpatient ophthalmology services face rising demand, and delays in follow-up can result in avoidable sight loss. The problem is often framed as a lack of capacity, but a more accurate description is demand–capacity mismatch. We aimed to develop a generalisable framework to quantify how follow-up interval choice influences service demand, using diabetic retinopathy as a case study.</p> Methods <p>We framed follow-up scheduling as a three-way trade-off between appointment demand, disease detection delay, and risk of progression. The risk of proliferative diabetic retinopathy (PDR) progression at 12 months was taken from Early Treatment Diabetic Retinopathy Study (ETDRS) data. In the absence of intermediate time-point data, we interpolated cumulative PDR risk for months 1–12 using a constant hazard model, which assumes a uniform instantaneous risk of progression across time and provides a transparent way to estimate risk at shorter intervals. We applied this framework to the diabetic retinopathy service of a UK district general hospital and considered other service examples.</p> Results <p>Small changes in follow-up interval produced large shifts in demand. In our service, increasing the mean interval from 4.7 to 6.2 months reduced demand by an estimated 700 appointments per 1000 patients annually. Illustrative examples in injection and glaucoma services showed similar effects.</p> Conclusions <p>Follow-up interval is a powerful, modifiable determinant of outpatient demand. Quantifying trade-offs between demand, detection delay, and disease progression risk supports decision-making regarding follow-up interval selection. This framework complements, rather than replaces, capacity expansion and is generalisable across other chronic disease services.</p>

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Evaluating the impact of follow-up interval selection on the demand–capacity gap in ophthalmology

  • 期刊论文

  • 发表日期：

    2026年6月24日

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  • Kevin Gallagher,
  • Ahmed Al-Janabi

摘要

Background

Outpatient ophthalmology services face rising demand, and delays in follow-up can result in avoidable sight loss. The problem is often framed as a lack of capacity, but a more accurate description is demand–capacity mismatch. We aimed to develop a generalisable framework to quantify how follow-up interval choice influences service demand, using diabetic retinopathy as a case study.

Methods

We framed follow-up scheduling as a three-way trade-off between appointment demand, disease detection delay, and risk of progression. The risk of proliferative diabetic retinopathy (PDR) progression at 12 months was taken from Early Treatment Diabetic Retinopathy Study (ETDRS) data. In the absence of intermediate time-point data, we interpolated cumulative PDR risk for months 1–12 using a constant hazard model, which assumes a uniform instantaneous risk of progression across time and provides a transparent way to estimate risk at shorter intervals. We applied this framework to the diabetic retinopathy service of a UK district general hospital and considered other service examples.

Results

Small changes in follow-up interval produced large shifts in demand. In our service, increasing the mean interval from 4.7 to 6.2 months reduced demand by an estimated 700 appointments per 1000 patients annually. Illustrative examples in injection and glaucoma services showed similar effects.

Conclusions

Follow-up interval is a powerful, modifiable determinant of outpatient demand. Quantifying trade-offs between demand, detection delay, and disease progression risk supports decision-making regarding follow-up interval selection. This framework complements, rather than replaces, capacity expansion and is generalisable across other chronic disease services.