The model for delivery of primary eye care in Europe varies from country to country with differing reliance on ophthalmologists, optometrists and dispensing opticians. Comparative analysis of models has tended to focus on interprofessional working arrangements, training and regulatory issues, rather than on whether a particular model is effective for delivering public health goals for that country. National Health Service (NHS) primary eye care services in the United Kingdom (UK) are predominantly provided under a General Ophthalmic Services (GOS) Contract between the NHS and practice owners (contractors).Over two thirds of sight tests conducted in England, Wales and Northern Ireland and all in Scotland are performed under a GOS contract, however many people entitled to a GOS sight test do not take up their entitlement. The fee paid for sight tests conducted under a GOS contract in England, Wales and Northern Ireland does not cover the full cost of conducting the examination. The shortfall must be made up through profits of sale of optical appliances but this business model can be a deterrent to establishing practices within socio-economically deprived communities, and can also be a barrier to uptake of sight tests, even though many people are entitled to a NHS Optical Voucher towards the cost of spectacles or contact lenses. This paper critiques the GOS Contracts within the UK. We argue that aspects of the way the GOS Contract is implemented are contrary to the public health interest and that different approaches are needed to address eye health inequalities and to reduce preventable sight loss. 3 Key wordsPrimary eye care, optometry, ophthalmology, General Ophthalmic Services Contract, models of care Word count 3,000

This article is aimed primarily at eye care practitioners who are undertaking advanced clinical research, and who wish to apply analysis of variance (ANOVA) to their data. ANOVA is a data analysis method of great utility and flexibility. This article describes why and how ANOVA was developed, the basic logic which underlies the method and the assumptions that the method makes for it to be validly applied to data from clinical experiments in optometry. The application of the method to the analysis of a simple data set is then described. In addition, the methods available for making planned comparisons between treatment means and for making post hoc tests are evaluated. The problem of determining the number of replicates or patients required in a given experimental situation is also discussed.

The effect of pupil tested for statistical significance at the 95% level using one-tail paired t-tests.

Purpose: The purpose of this paper is to investigate the potential of using primary care optometry data to support ophthalmic public health, research and policy making. Methods: Suppliers of optometric electronic patient record systems (EPRs) were interviewed to gather information about the data present in commercial software programmes and the feasibility of data extraction. Researchers were presented with a list of metrics that might be included in an optometric practice dataset via a survey circulated by email to 102 researchers known to have an interest in eye health. Respondents rated the importance of each metric for research. A further survey presented the list of metrics to 2000 randomly selected members of the College of Optometrists. The optometrists were asked to specify how likely they were to enter information about each metric in a routine sight test consultation. They were also asked if data were entered as free text, menus or a combination of these. Results: Current EPRs allowed the input of data relating to the metrics of interest. Most data entry was free text. There was a good match between high priority metrics for research and those commonly recorded in optometric practice. Conclusions: Although there were plenty of electronic data in optometric practice, this was highly variable and often not in an easily analysed format. To facilitate analysis of the evidence for public health purposes a UK based minimum dataset containing standardised clinical information is recommended. Further research would be required to develop suitable coding for the individual metrics included. The dataset would need to capture information from all sectors of the population to ensure effective planning of any future interventions.

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