We extend a mixture cure fraction model with random effects to allow estimation of relative survival of cancer patients by region in a country with a parsimonious number of parameters. The heterogeneity in the expected survival was taken into account such that the expected mortality rate was considered as a random quantity varying across regions. Two sets of random effects were used to describe regional variation, both in the cure fraction and in the relative survival of the non-cured patients. This hierarchical model was fitted in a Bayesian framework to the follow-up data of Finnish colon cancer patients diagnosed in 1975–2004. The public health importance of the regional differences was described by the extra survival time and avoidable deaths that could be gained, if the regional variation were eliminated and all the hospital districts in Finland achieved the most favourable level of relative survival. The differences in relative survival between the districts were quite small during the three decades. If all the districts had achieved the most favourable level of relative survival, the mean survival times of the female patients diagnosed in 1975–1984, 1985–1994 and 1995–2004 would have increased by 5%, 4% and 2% respectively.