Contextual factors influencing physicians’ perception of antibiotic prescribing in primary care in Germany — a prospective observational study

DDD-costs have a strong influence on antibacterial drug prescription in Germany: a differentiated correlation analysis from 1985 to 2022

Antibacterial drugs are vital in modern medicine, and understanding the factors influencing their prescriptions is essential for maintaining their effectiveness and accessibility. This study investigates the hypothesis that costs significantly impact the prescriptions of antibacterial drugs, a factor previously underrecognized. To investigate this, we conducted correlation analyses on defined daily dose (DDD-) prescriptions and DDD-costs for the 15 most prescribed antibacterial drugs in Germany in 2022, using data from the Arzneimittelverordnungsreport (Drug Prescription Report) (1985-2022). The analysis focused on the periods 1985-2022, 1985-2011, and 2012-2022. Our findings revealed significant correlations between DDD-prescriptions and -costs for nearly all drugs over the entire period (1985-2022), with strong negative correlations for amoxicillin (- 0.941), cefuroxime axetil (- 0.900), clindamycin (- 0.800), nitrofurantoin (- 0.895), and cefaclor (- 0.819). From 1985 to 2011, only significant negative correlations were observed. In 2012-2022, significant correlations included both negative and positive, with strong positive correlations for ciprofloxacin (0.950) and clarithromycin (0.962). Overall, DDD-costs showed a persistent and strong correlation with DDD-prescriptions, particularly in the earlier period. This influence appears to diminish slightly in recent years, suggesting other factors might become more significant as DDD-costs plateau. Notably, amoxicillin, amoxicillin clavulanic acid, and nitrofurantoin consistently exhibited strong cost-prescription correlations throughout the entire period. While correlation does not imply causation, the significant and strong correlations, coupled with logical explanations, support the hypothesis that costs are a primary factor in prescribing patterns. Further research is needed to establish causality and examine other potential systemic factors affecting antibacterial drug prescriptions.

Factors contributing to the variation in antibiotic prescribing among primary health care physicians: a systematic review

BACKGROUND

Antibiotic resistance is growing globally. The practice of health professionals when prescribing antibiotics in primary health care settings significantly impacts antibiotic resistance. Antibiotic prescription is a complex process influenced by various internal and external factors. This systematic review aims to summarize the available evidence regarding factors contributing to the variation in antibiotic prescribing among physicians in primary healthcare settings.

METHODS

This systematic review was conducted based on PRISMA guidelines. We included qualitative, quantitative and mixed methods studies that examined factors influencing prescription practice and variability among primary healthcare physicians. We excluded editorials, opinions, systematic reviews and studies published in languages other than English. We searched studies from electronic databases: PubMed, ProQuest Health and Medicine, Web Science, and Scopus. The quality of the included studies was appraised using the Mixed Methods Appraisal Tool (Version 2018). Narrative synthesis was employed to synthesize the result and incorporate quantitative studies.

RESULTS

Of the 1816 identified studies, 49 studies spanning 2000-2023 were eligible for review. The factors influencing antibiotic prescription practice and variability were grouped into physician-related, patient-related, and healthcare system-related factors. Clinical guidelines, previous patient experience, physician experience, colleagues' prescribing practice, pharmaceutical pressure, time pressure, and financial considerations were found to be influencing factors of antibiotic prescribing practice. In addition, individual practice patterns, practice volume, and relationship with patients were also other factors for the variability of antibiotic prescription, especially for intra-physician prescription variability.

CONCLUSION

Antibiotic prescription practice in primary health care is a complex practice, influenced by a combination of different factors and this may account for the variation. To address the factors that influence the variability of antibiotic prescription (intra- and inter-physician), interventions should aim to reduce diagnostic uncertainty and provide continuous medical education and training to promote patient-centred care.

Effects of a feedback intervention on antibiotic prescription control in primary care institutions based on a Health Information System: a cluster randomized cross-over controlled trial

OBJECTIVES

Overuse and misuse of antibiotics are major factors in the development of antibiotic resistance in primary care institutions of rural China. In this study, the effectiveness of a Health Information System-based, automatic, and confidential antibiotic feedback intervention was evaluated.

METHODS

A randomized, cross-over, cluster-controlled trial was conducted in primary care institutions. All institutions were randomly divided into two groups and given either a three-month intervention followed by a three-month period without any intervention or vice versa. The intervention consisted of three feedback measures: a real-time pop-up warning message of inappropriate antibiotic prescriptions on the prescribing physician's computer screen, a 10-day antibiotic prescription summary, and distribution of educational manuals. The primary outcome was the 10-day inappropriate antibiotic prescription rate.

RESULTS

There were no significant differences in inappropriate antibiotic prescription rates (69.1% vs. 72.0%) between two groups at baseline (P = 0.072). After three months (cross-over point), inappropriate antibiotic prescription rates decreased significantly faster in group A (12.3%, P < 0.001) compared to group B (4.4%, P < 0.001). At the end point, the inappropriate antibiotic prescription rates decreased in group B (15.1%, P < 0.001) while the rates increased in group A (7.2%, P < 0.001). The characteristics of physicians did not significantly affect the rate of antibiotic or inappropriate antibiotic prescription rates.

CONCLUSION

A Health Information System-based, real-time pop-up warnings, a 10-day prescription summary, and the distribution of educational manuals, can effectively reduce the rates of antibiotic and inappropriate antibiotic prescriptions.