OBJECTIVE: To identify factors influencing volume, quality and power of antibiotic prescription in primary care. DESIGN: Descriptive, crossover study. SETTING: Sanitary Region Coast of Ponent, 1992. PARTICIPANTS: They were studied 468 practitioners of primary care attention. 68 practitioners were excluded by various reasons. MEASUREMENTS AND MAIN RESULTS: The factors studied were: factors coming from the practitioner, the centre, and the assisted population. The following parameters were analysed: amount of prescribed antibiotics in DDDs, election level ("antibiotic power") and percentage of DDDs of low intrinsic value. It was used for the comparison of means, Student-Fisher t test and the confidence intervals of the difference. Also it was used the step-wise multiple regression analysis. Greater use of antibiotics. The variability can be explained through regression in a 45.7% in function of the doctors factors, not integrated in a team, older, doctor who works in a rural centre, of young population and of smaller revenue. Greater antibiotic power. It's explained in a 5.09% by the medical factors like man, that works in a not educational centre and of greater population revenue. Greater percentage of DDDs of low intrinsic value. It's greater in doctors not specialized in family care, permanent job, of greater age, men, not reformed professional and not of an educational centre. CONCLUSIONS: The volume of prescription of antibiotics and in minor extent its quality of prescription are in some part justified by variables coming from the practitioner, the centre and the assisted population. The antibiotic power mainly doesn't.
OBJECTIVE: To identify factors influencing volume, quality and power of antibiotic prescription in primary care. DESIGN: Descriptive, crossover study. SETTING: Sanitary Region Coast of Ponent, 1992. PARTICIPANTS: They were studied 468 practitioners of primary care attention. 68 practitioners were excluded by various reasons. MEASUREMENTS AND MAIN RESULTS: The factors studied were: factors coming from the practitioner, the centre, and the assisted population. The following parameters were analysed: amount of prescribed antibiotics in DDDs, election level ("antibiotic power") and percentage of DDDs of low intrinsic value. It was used for the comparison of means, Student-Fisher t test and the confidence intervals of the difference. Also it was used the step-wise multiple regression analysis. Greater use of antibiotics. The variability can be explained through regression in a 45.7% in function of the doctors factors, not integrated in a team, older, doctor who works in a rural centre, of young population and of smaller revenue. Greater antibiotic power. It's explained in a 5.09% by the medical factors like man, that works in a not educational centre and of greater population revenue. Greater percentage of DDDs of low intrinsic value. It's greater in doctors not specialized in family care, permanent job, of greater age, men, not reformed professional and not of an educational centre. CONCLUSIONS: The volume of prescription of antibiotics and in minor extent its quality of prescription are in some part justified by variables coming from the practitioner, the centre and the assisted population. The antibiotic power mainly doesn't.