This thesis explores the spatial and temporal patterns of first referrals for Welsh-domicilled patients to the Cancer Genetics Service for Wales (CGSW) in order to establish what referral patterns exist. CGSW has a patient population of 10,878 first referrals over the eight year period, 1998 to 2006. These data are combined with data on deprivation, GP practices, postcode and administrative boundaries to produce a more complete dataset, enabling analyses to include factors beyond just the service database. This is a secondary analysis of a service database, using analyses performed by standard statistical techniques (partial correlation, chi square, Pearson’s r, Spearman’s rho) combined with a Geographical Information System (GIS). Ethical approval was granted by a multi-centre research ethics committee. Nearly 70% of referrals are for breast, ovarian or breast and ovarian cancer, which helps to explain why more than 90% of all referred patients are female. Female patients are more likely to be at greater than population risk. Referrals considered to be high risk patients are more likely to come from secondary care rather than primary care sources and vice versa for those at medium risk. Patients living in more deprived areas of Wales are less likely to be referred to CGSW than those living in less deprived areas. This inverse correlation between referrals and deprivation, shows that as deprivation decreases, referrals increase. One temporal trend that can be identified is an increase in referrals to the CGSW centre in Swansea, from a quarter to a third of all CGSW referrals, and a corresponding decrease to the other two centres in Cardiff and Rhyl. These results have not produced any evidence that referral guidelines influence referrals. This study has shown the value of quantitative and GIS techniques in the analysis of a cancer genetics database. They have shown an association between deprivation and referrals, the more deprived an area is, the less referrals will be made from that area. This has identified cancer genetics as a field that needs to adopt policies aimed at reducing health inequalities and target resources at meeting unmet needs for cancer genetics services
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