Objective
We estimated the quality of life impact of vision loss in a community-based population with diabetes.
Design and methods
We randomly surveyed 4,000 members of a large health maintenance organization with type 2 diabetes to assess quality of life
using the EQ-5D instrument. Visual acuity was obtained by automated text processing of clinical notes recorded during the
two years preceding subjects’ surveys. Natural language processing was used to collect data from electronic medical records
and to read clinical notes to determine the stage of retinopathy. Linear regression was used to model quality of life scores.
Results
Of the 4,000 surveys sent, approximately 55% of patients responded. Patients with ≥20/20 acuity reported the highest mean
utility (mean = 0.82), which declined as the visual angle doubled to 20/40 (mean = 0.75), and then doubled again to ≤20/80
(mean = 0.71). Perfect utility (1.0) was reported by 28% of the sample. Only 7% of patients suffered visual impairment (≤20/40),
and lower levels of visual acuity rarely occurred. Compared with patients with ≥20/20 acuity, the first doubling of the visual
angle (20/40) lowered utility by three points (95% confidence interval [CI], −0.05 to −0.01), and the second doubling of the
visual angle (≤20/80) lowered utility by six points (95%CI, −0.10 to −0.02).
Conclusions
This study aimed to estimate disutility associated with visual loss in patients with diabetes using a community-based sample
and controlled for many characteristics associated with quality of life. We found a smaller utility decrement compared to
other studies, suggesting that visual acuity’s impact on the quality of life for patients with diabetes in the community setting
differs from more selected populations.
Keywords Diabetes - Natural language processing - Quality of life - Visual impairment