BACKGROUND: The majority of medicines prescribed for children are prescribed in primary care for common acute and chronic conditions. This is in contrast to prescribing in secondary care where the population of children admitted is small but where a large number of different medicines are prescribed to treat more serious and less common conditions. METHODS: Data on prescribing was extracted from the General Practice Administration System for Scotland (GPASS) for the year November 1999 to October 2000 and prescribing patterns for children aged 0-16 years expressed as percentages. A comparison of age specific consultations for asthma, as an example of a common paediatric condition, was also made between two separate general practice data sets, the General Practice Research Database (GRPD) and the continuous morbidity recording (CMR) subset of GPASS. RESULTS: Of 214 medicines investigated for unlicensed and off-label prescribing no unlicensed prescribing was identified. Off-label prescribing due to age was most common among younger and older children. The most common reasons for off-label prescriptions were, in order of frequency, lower than recommended dose, higher than recommended dose, below the recommended age, and unlicensed formulation. Age and gender specific consultations for asthma were similar in the two representative databases, GPRD and CMR, both showing disappearance of the male predominance in the teenage years. CONCLUSIONS: Large primary care data sets available within a unified health care system such as the UK National Health Service (NHS) are likely to be broadly compatible and produce similar results. The prescribing of off-label medicines to children is common in primary care, most commonly due to prescribing out with the recommended dosage regimen.
BACKGROUND: The majority of medicines prescribed for children are prescribed in primary care for common acute and chronic conditions. This is in contrast to prescribing in secondary care where the population of children admitted is small but where a large number of different medicines are prescribed to treat more serious and less common conditions. METHODS: Data on prescribing was extracted from the General Practice Administration System for Scotland (GPASS) for the year November 1999 to October 2000 and prescribing patterns for children aged 0-16 years expressed as percentages. A comparison of age specific consultations for asthma, as an example of a common paediatric condition, was also made between two separate general practice data sets, the General Practice Research Database (GRPD) and the continuous morbidity recording (CMR) subset of GPASS. RESULTS: Of 214 medicines investigated for unlicensed and off-label prescribing no unlicensed prescribing was identified. Off-label prescribing due to age was most common among younger and older children. The most common reasons for off-label prescriptions were, in order of frequency, lower than recommended dose, higher than recommended dose, below the recommended age, and unlicensed formulation. Age and gender specific consultations for asthma were similar in the two representative databases, GPRD and CMR, both showing disappearance of the male predominance in the teenage years. CONCLUSIONS: Large primary care data sets available within a unified health care system such as the UK National Health Service (NHS) are likely to be broadly compatible and produce similar results. The prescribing of off-label medicines to children is common in primary care, most commonly due to prescribing out with the recommended dosage regimen.
Authors: C R Simpson; W J A Anderson; P J Helms; M W Taylor; L Watson; G J Prescott; D J Godden; R N Barker Journal: Clin Exp Allergy Date: 2002-01 Impact factor: 5.018
Authors: Daniel Kotz; Colin R Simpson; Wolfgang Viechtbauer; Onno C P van Schayck; Aziz Sheikh Journal: NPJ Prim Care Respir Med Date: 2014-05-20 Impact factor: 2.871
Authors: Colin R Simpson; Philip C Hannaford; Matthew McGovern; Michael W Taylor; Paul N Green; Karen Lefevre; David J Williams Journal: BMC Fam Pract Date: 2007-09-27 Impact factor: 2.497