How to measure hospital antibiotic consumption: comparison of two methods from data surveillance in France

Author:

Stordeur Florence1ORCID,Miliani Katiuska2,Lacavé Ludivine3,Rogues Anne-Marie45,Dumartin Catherine46,Alfandari Serge7,Astagneau Pascal28,L’Hériteau François2,Bertrand X,Boussat S,Crémieux A-C,Dugravot L,Ingels A,Jarno P,Machut A,Péfau M,Rémy E,Schlemmer B,Touratier S,Vaux S,Bajolet O,Bernet C,Bervas C,Coignard B,Dégéfa M,Gautier C,Garreau N,Giard M,Jarno P,Hoff O,Lamy M,Léon L,Machut A,Migueres B,Péfau M,Simon L,Thiolet J-M,Vaux S,Verjat-Trannoy D,

Affiliation:

1. Centre hospitalier intercommunal de Poissy St Germain, 10 rue du champ Gaillard, 78100 Poissy, France

2. Centre d’appui pour la prévention des infections associées aux soins (CPias) Ile-de-France, Paris, France

3. Assistance Publique – Hôpitaux de Paris (AP-HP), délégation à la recherche clinique et à l’innovation (DRCI), Paris, France

4. Université Bordeaux, Inserm, Bordeaux Population Health Research Center, Team Pharmacoepidemiology, UMR 1219, F-33000 Bordeaux, France

5. CHU Bordeaux, Hygiène hospitalière, F-33000 Bordeaux, France

6. CHU Bordeaux, CPias Nouvelle Aquitaine, F-33000 Bordeaux, France

7. Centre Hospitalier de Tourcoing, 59208 Tourcoing, France

8. Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique, F-75013 Paris, France

Abstract

Abstract Background Antibiotic use (ABU) surveillance in healthcare facilities (HCFs) is essential to guide stewardship. Two methods are recommended: antibiotic consumption (ABC), expressed as the number of DDD/1000 patient-days; and prevalence of antibiotic prescription (ABP) measured through point prevalence surveys. However, no evidence is provided about whether they lead to similar conclusions. Objectives To compare ABC and ABP regarding HCF ranking and their ability to identify outliers. Methods The comparison was made using 2012 national databases from the antibiotic surveillance network and prevalence study. HCF rankings according to each method were compared with Spearman’s correlation coefficient. Analyses included the ABU from entire HCFs as well as according to type, clinical ward and by antibiotic class and specific molecule. Results A total of 1076 HCFs were included. HCF rankings were strongly correlated in the whole cohort. The correlation was stronger for HCFs with a higher number of beds or with a low or moderate proportion of acute care beds. ABU correlation between ABC or ABP was globally moderate or weak in specific wards. Furthermore, the two methods did not identify the same outliers, whichever HCF characteristics were analysed. Correlation between HCF ranking varied according to the antibiotic class. Conclusions Both methods ranked HCFs similarly overall according to ABC or ABP; however, major differences were observed in ranking of clinical wards, antibiotic classes and detection of outliers. ABC and ABP are two markers of ABU that could be used as two complementary approaches to identify targets for improvement.

Publisher

Oxford University Press (OUP)

Subject

General Medicine

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