INTRODUCTION: To determine patient and physician-related factors associated with variability in antibiotic prescription. MATERIAL AND METHODS: Observational study of the prevalence of antibacterial medication prescription >14 years old. DATA SOURCE: official prescriptions, clinical histories and individual health cards. Patient-related variables were: age, sex, number of medical visits-year, comorbidity, antibacterials dispensed with prescription. Physician-related variables were age, sex, number of patients assigned, place of work and rurality. Variables associated with prescription were studied by estimating the odds ratio (OR) from the fit of the multilevel logistic regression models. RESULTS: The rate of antibiotic prescription-year in the population was 31.4%. Factors associated with prescription were high rate of visits (users with more than 5 annual visits multiply the probability of receiving antibiotics, compared to those who madeno visits: OR=10.8), age (non-linearly, with a greater likelihood in the young and the elderly) and sex, with a higher rate in women (OR=1.5). No association was found between prescription and age and sex of the physician, but an association was found with workload: the higher the physician's workload, the higher the likelihood of antibiotic prescription. CONCLUSIONS: The most important factor associated with the increase in prescription rate was the frequency of visits. In addition, women, the young and the elderly receive more antibiotics. A multi-factor intervention focusing on demand, patients, and physicians should be carried out to reduce prescription rates.
INTRODUCTION: To determine patient and physician-related factors associated with variability in antibiotic prescription. MATERIAL AND METHODS: Observational study of the prevalence of antibacterial medication prescription >14 years old. DATA SOURCE: official prescriptions, clinical histories and individual health cards. Patient-related variables were: age, sex, number of medical visits-year, comorbidity, antibacterials dispensed with prescription. Physician-related variables were age, sex, number of patients assigned, place of work and rurality. Variables associated with prescription were studied by estimating the odds ratio (OR) from the fit of the multilevel logistic regression models. RESULTS: The rate of antibiotic prescription-year in the population was 31.4%. Factors associated with prescription were high rate of visits (users with more than 5 annual visits multiply the probability of receiving antibiotics, compared to those who madeno visits: OR=10.8), age (non-linearly, with a greater likelihood in the young and the elderly) and sex, with a higher rate in women (OR=1.5). No association was found between prescription and age and sex of the physician, but an association was found with workload: the higher the physician's workload, the higher the likelihood of antibiotic prescription. CONCLUSIONS: The most important factor associated with the increase in prescription rate was the frequency of visits. In addition, women, the young and the elderly receive more antibiotics. A multi-factor intervention focusing on demand, patients, and physicians should be carried out to reduce prescription rates.
Authors: Victoria Palin; Anna Mölter; Miguel Belmonte; Darren M Ashcroft; Andrew White; William Welfare; Tjeerd van Staa Journal: J Antimicrob Chemother Date: 2019-08-01 Impact factor: 5.790
Authors: L Calle-Miguel; G Modroño Riaño; A I Iglesias Carbajo; M A Alonso Álvarez; C Vicente Martínez; G Solís Sánchez Journal: Rev Esp Quimioter Date: 2021-01-26 Impact factor: 1.553