OBJECTIVES: We use the Chronic Disease Score methodology to estimate the prevalence of a number of chronic conditions in the Republic of Ireland from routinely available prescribing data, which we then compare with epidemiological estimates. METHODS: Using automated outpatient pharmacy data, measures of chronic disease severity called Chronic Disease Scores were constructed. We use these to measure disease prevalence. Since many drugs have multiple indications, incidental users and the chronically ill must be distinguished. Any person receiving four or more prescriptions within a 12-month period for a chronic disease category is identified as suffering from that chronic disease. Prevalence estimates are compared with estimates for these conditions based on a review of the epidemiology literature. Data refer to the General Medical Services (GMS) scheme in Ireland. The GMS provides free primary care to those on low income and to other hardship cases, covering approximately 31% of the Irish population. Data on drugs prescribed to all individuals on the GMS scheme in four health board areas were collected for the period from September 1999 to August 2000, representing a total of 415,271 people or approximately 37% of the GMS population. RESULTS: Estimates of prevalence based on the Chronic Disease Score are similar to epidemiological estimates. This is especially true for conditions such as diabetes, epilepsy and asthma, and less so for depression and other mental illness, where under-diagnosis is commonplace. CONCLUSIONS: The results suggest that prescribing data is a rich source of information on morbidity in the community. It is locally sensitive, timely and cheap to collect. As long as certain caveats are applied, this type of information has many uses in the surveillance of the public’s health.