[Factors determining antibiotic prescription in primary care]

Enferm Infecc Microbiol Clin. 2011 Mar;29(3):193-200. doi: 10.1016/j.eimc.2010.09.012. Epub 2011 Feb 22.
[Article in Spanish]

Abstract

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.

Publication types

  • English Abstract

MeSH terms

  • Adolescent
  • Adult
  • Age Distribution
  • Aged
  • Aged, 80 and over
  • Anti-Bacterial Agents / therapeutic use*
  • Comorbidity
  • Drug Prescriptions / statistics & numerical data*
  • Drug Utilization
  • Female
  • Humans
  • Male
  • Middle Aged
  • Office Visits / statistics & numerical data
  • Physicians, Primary Care / statistics & numerical data
  • Practice Patterns, Physicians' / statistics & numerical data
  • Primary Health Care / statistics & numerical data*
  • Rural Population
  • Sampling Studies
  • Sex Distribution
  • Spain
  • Urban Population
  • Workload
  • Young Adult

Substances

  • Anti-Bacterial Agents