Research Group: Antibiotic Stewardship

Addressing antibiotic resistance

Antibiotic overuse is highly prevalent in primary care and increases the risk of antimicrobial resistance in the population. We are working to address this issue by measuring routinely collected data from Swiss health insurance companies to evaluate the antibiotic prescribing practices of general practitioners.

Key Projects

Photo by Lukas: https://www.pexels.com/photo/close-up-photo-of-survey-spreadsheet-590022/

Antibiotic Prescribing Audit and Feedback in Primary Care

An randomized clinical trial investigating the effect of quarterly audit and feedback on antibiotic prescribing among primary care physicians in Switzerland. more

Photo by cottonbro studio: https://www.pexels.com/photo/white-and-orange-medication-pill-on-persons-hand-4661292/

Impact of the COVID-19 pandemic on antibiotic prescribing

Evaluating the effect of the pandemic on antibiotic prescribing by general practitioners in 2020 and assessing the impact of a two-year antibiotic stewardship program established prior to the pandemic. more

Antimicrobial resistance in urinary tract infections

Predictors of antimicrobial resistance in urinary tract infections in the community: A pilot linkage study of claims and laboratory data within a nationwide pragmatic intervention trial to lower antibiotic prescribing in primary care. more

Team

Dr. Soheila Aghlmandi - Group Lead

Prof. Dr. Heiner C. Bucher, MPH - Scientific Collaborator

PD Dr. med. Julia Belicki - Scientific Collaborator

Thomas Stojanov - PhD student

Other projects...

Swiss HIV Cohort Study

SHCS

A systematic longitudinal study enrolling HIV-infected individuals in Switzerland. The major goal is to provide optimal patient care, reduce HIV transmission and to conduct research. more

Prediction of Outcomes After an Arthroscopic Rotator Cuff Repair

ARCR_Pred

A multi-center cohort study of patients undergoing an arthroscopic rotator cuff repair in Switzerland and Germany. The major goal of the study is to develop and validate clinical prediction models for key surgical outcomes. more

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