Every ophthalmologist is a quality-of-life expert: most of us devote our days not to “adding years to life,” but rather to “adding life to years.”1 The quality-of-life assessment that occurs during a busy clinic visit is typically brief and informal, asking primarily about vision symptoms and problems with specific visual tasks and ascertaining in broad terms the impact of eye disease on the patient’s overall well-being. Even such limited quality-of-life information, however, can be invaluable in determining which patient is most likely to benefit from surgery or other treatment. When formally assessed in a clinical research setting, quality-of-life data can be even more powerful: patients’ baseline quality of life has been shown to predict patient outcomes, need for physician services, and health service charges.2-4 This predictive ability of quality of life is independent of clinical and laboratory measures, indicating that quality-of-life measurement captures information that traditional biomedical parameters do not. Additionally, quality-of-life data can meet or exceed the reproducibility of “hard” biomedical data,5 supporting the feasibility of including quality-of-life assessment in clinical trials and prospective studies. Measuring quality of life to generate valid and reliable data, however, is difficult, as it requires surveying patients. The report by Hall and coauthors6 illustrates some of the practical issues involved in designing and executing meaningful studies of quality of life in ophthalmic disease.
Bradley EA, Bradley D, Bartley GB. Evaluating Health-Related Quality of Life in Ophthalmic Disease: Practical Considerations. Arch Ophthalmol. 2006;124(1):121–122. doi:10.1001/archopht.124.1.121
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