Feedback

Kinetic Patterns of Antibiotic Consumption in German Acute Care Hospitals from 2017 to 2023

Affiliation
Healthcare-Associated Infections, Surveillance of Antimicrobial Resistance and Antimicrobial Consumption, Robert Koch Institute, 13353 Berlin, Germany;(N.W.);(D.R.);(T.E.);
Schweickert, Birgitta;
ORCID
0000-0003-0827-4543
Affiliation
Healthcare-Associated Infections, Surveillance of Antimicrobial Resistance and Antimicrobial Consumption, Robert Koch Institute, 13353 Berlin, Germany;(N.W.);(D.R.);(T.E.);
Willrich, Niklas;
Affiliation
Methods Development, Research Infrastructure and Information Technology, Koch-Institute, 13353 Berlin, Germany;(M.F.);(M.S.)
Feig, Marcel;
Affiliation
Methods Development, Research Infrastructure and Information Technology, Koch-Institute, 13353 Berlin, Germany;(M.F.);(M.S.)
Schneider, Marc;
Affiliation
Institute for Hygiene and Environmental Medicine, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humbold-Universität zu Berlin and Berlin Institute for Health, 12203 Berlin, Germany(L.A.P.D.);
Behnke, Michael;
ORCID
0000-0001-6798-7872
Affiliation
Institute for Hygiene and Environmental Medicine, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humbold-Universität zu Berlin and Berlin Institute for Health, 12203 Berlin, Germany(L.A.P.D.);
Peña Diaz, Luis Alberto;
ORCID
0000-0003-3047-6416
Affiliation
Institute for Hygiene and Environmental Medicine, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humbold-Universität zu Berlin and Berlin Institute for Health, 12203 Berlin, Germany(L.A.P.D.);
Geffers, Christine;
Affiliation
Healthcare-Associated Infections, Surveillance of Antimicrobial Resistance and Antimicrobial Consumption, Robert Koch Institute, 13353 Berlin, Germany;(N.W.);(D.R.);(T.E.);
Wieters, Imke;
Affiliation
Healthcare-Associated Infections, Surveillance of Antimicrobial Resistance and Antimicrobial Consumption, Robert Koch Institute, 13353 Berlin, Germany;(N.W.);(D.R.);(T.E.);
Gröschner, Karin;
Affiliation
Healthcare-Associated Infections, Surveillance of Antimicrobial Resistance and Antimicrobial Consumption, Robert Koch Institute, 13353 Berlin, Germany;(N.W.);(D.R.);(T.E.);
Richter, Doreen;
ORCID
0000-0001-8775-4224
Affiliation
Healthcare-Associated Infections, Surveillance of Antimicrobial Resistance and Antimicrobial Consumption, Robert Koch Institute, 13353 Berlin, Germany;(N.W.);(D.R.);(T.E.);
Hoffmann, Alexandra;
Affiliation
Healthcare-Associated Infections, Surveillance of Antimicrobial Resistance and Antimicrobial Consumption, Robert Koch Institute, 13353 Berlin, Germany;(N.W.);(D.R.);(T.E.);
Eckmanns, Tim;
Affiliation
Healthcare-Associated Infections, Surveillance of Antimicrobial Resistance and Antimicrobial Consumption, Robert Koch Institute, 13353 Berlin, Germany;(N.W.);(D.R.);(T.E.);
Abu Sin, Muna

Background: Antimicrobial consumption (AMC) patterns, besides prescribing behaviors, reflect the changing epidemiology of infectious diseases. Routine surveillance data have been used to investigate the development of AMC from 2017 to 2023 and the impact of COVID-19 within the context of the framing time periods. Methods: Data from 112 hospitals, continuously participating from 2017 to 2023 in the national surveillance system of hospital antimicrobial consumption based at the Robert Koch Institute, were analyzed according to the WHO ATC (Anatomical Therapeutic Chemical)/DDD (Defined Daily Dose) method and categorized according to the WHO AWaRe-classification. AMC was quantified by consumption density (CD) expressed in DDD/100 patient days (PD) and DDD/100 admissions (AD). The time period was subdivided into three phases: pre-pandemic phase (2017–2019), main pandemic phase (2020–2021) and transition phase (2022–2023). Linear regression models have been used to determine the presence of an overall trend, the change in intra-phasic trends and phase-specific mean consumption levels over time. Results: From 2017 to 2023 total antibiotic consumption decreased by 7% from 57.1 to 52.9 DDD/100 PD. Four main kinetic patterns emerged across different antibiotic classes: Pattern 1 displays a decreasing pre-pandemic trend, which slowed down throughout the pandemic and transition phase and was exhibited by second-generation cephalosporins and fluoroquinolones. Pattern 2 reveals a rising pre-pandemic trend, which decelerated in the pandemic phase and accelerated again in the transition phase and was expressed by aminopenicillins/beta-lactamase inhibitors, beta-lactamase sensitive pencillins, azithromycin and first-generation cephalosporins. Pattern 3 shows elevated mean consumption levels in the pandemic phase exhibited by carbapenems, glycopeptides, linezolid and third-generation cephalosporins. Pattern 4 reveals a rising trend throughout the pre-pandemic and pandemic phase, which reversed in the transition phase without achieving pre-pandemic levels and was expressed by beta-lactamase resistant penicillins, daptomycin, fosfomycin (parenteral) and ceftazidime/avibactam. Conclusions: Kinetic consumption patterns across different antibiotic classes might reflect COVID-19-related effects and associated changes in the epidemiology of co-circulating pathogens and health care supply. Broad-spectrum antibiotics with persisting elevated consumption levels throughout the transition phase require special attention and focused antimicrobial stewardship activities.

Cite

Citation style:
Could not load citation form.

Access Statistic

Total:
Downloads:
Abtractviews:
Last 12 Month:
Downloads:
Abtractviews:

Rights

License Holder: © 2025 by the authors.

Use and reproduction: