Norris Pauline, Funke Silvia, Becket Gordon, Ecke Denise, Reiter Lillian, Herbison Peter
School of Pharmacy, University of Otago, Dunedin.
N Z Med J. 2006 May 5;119(1233):U1951.
To determine the proportion of prescriptions for antibiotics which were unsubsidised, in one town in one year, and to use this to develop a model which could be used to estimate the number of unsubsidised prescriptions.
Data on all prescriptions for antibiotics during 2002 were extracted from pharmacy computers in one town. Data were obtained from PharmHouse database on all subsidised prescriptions from the town pharmacies during 2002. (The PharmHouse database is a subset of the New Zealand Health Information System database and contains records of all the claims for medicines dispensed within New Zealand.) These were compared and the proportion of unsubsidised prescriptions for each antibiotic calculated. Weighted linear regression was used to develop a model of the relationship between the percentage of each drug subsidised, and patient and prescription characteristics obtainable in PharmHouse.
64.4% of antibiotic dispensings in the study town were subsidised, and therefore captured by the PharmHouse database. The proportion varied substantially between different antibiotics. For particular drugs, the proportion of drugs unsubsidised could be predicted by the price of the drug, the number of days it was prescribed for, and the number of patients aged under six who received subsidised prescriptions.
Previous studies using PharmHouse data are likely to have significantly underestimated the extent of drug use. Further research is needed on whether this model can help to estimate the extent of unsubsidised prescriptions.