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This paper models access to and utilisation of primary care using data from the British Household Panel Survey for the period 1991-2001. A latent class panel data framework is adopted to model individual unobserved heterogeneity in a flexible way. Accounting for the panel structure of the data leads to a substantial improvement in fit, and permits the identification of latent classes of users of health care. Analysis by gender shows that men and women respond differently to some factors, in particular, to age and income. There is evidence of a positive impact of income on the probability of seeking primary care. This effect is especially significant in the case of women. For both genders, the marginal effect of income on the propensity to visit a GP is greater for individuals who are less likely to seek primary care. A latent class aggregated count data model for the number of GP visits classifies individuals in three latent classes and shows a positive income effect particularly amongst those with lower levels of utilisation.