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Monitoring outpatient antibiotic utilization using reimbursement and retail sales data: a population-based comparison in France, 2012-17.
Trinh, Nhung T H; Chalumeau, Martin; Bruckner, Tim A; Levy, Corinne; Bessou, Antoine; Milic, Dejan; Cohen, Robert; Lemaitre, Magali; Cohen, Jérémie F.
Afiliação
  • Trinh NTH; Université de Paris, Epidemiology and Statistics Research Center-CRESS, INSERM, Obstetrical, Perinatal and Pediatric Epidemiology research team, F-75004, Paris, France.
  • Chalumeau M; IQVIA, La Défense, France.
  • Bruckner TA; Université de Paris, Epidemiology and Statistics Research Center-CRESS, INSERM, Obstetrical, Perinatal and Pediatric Epidemiology research team, F-75004, Paris, France.
  • Levy C; Department of General Pediatrics and Pediatric Infectious Diseases, AP-HP, Hôpital Necker-Enfants malades, Université de Paris, Paris, France.
  • Bessou A; Program in Public Health, University of California, Irvine, CA, USA.
  • Milic D; Association Clinique et Thérapeutique Infantile du Val-de-Marne (ACTIV), Saint-Maur-des-Fossés, France.
  • Cohen R; Clinical Research Centre, Centre Hospitalier Intercommunal de Créteil, Créteil, France.
  • Lemaitre M; IQVIA, La Défense, France.
  • Cohen JF; IQVIA, La Défense, France.
J Antimicrob Chemother ; 76(9): 2446-2452, 2021 08 12.
Article em En | MEDLINE | ID: mdl-34120188
ABSTRACT

OBJECTIVES:

To assess whether a retail sales database could be used to monitor antibiotic utilization in the outpatient setting at the national level.

METHODS:

We extracted 2012-17 outpatient antibiotic extrapolated retail sales (IQVIA's Xponent) and reimbursement data from the National Health Insurance (SNDS) in metropolitan France. We compared estimates of antibiotic use and consumption [number of antibiotic drug deliveries (DrID) and defined daily doses (DID) per 1000 inhabitants per day]. We relied on relative differences, Pearson's r statistics and time series using autoregressive integrated moving average (ARIMA) modelling to study (i) differences in point estimates, (ii) correlation, and (iii) consistency in time trends between Xponent and SNDS. The analysis was conducted overall and in subgroups (age groups, therapeutic classes, major antimicrobial agents and regions).

RESULTS:

We analysed approximately 377 million antibiotic drug deliveries, comprising nearly 3.4 billion DDDs. Overall, Xponent slightly overestimated SNDS point estimates with yearly relative differences of +3.5% for DrID and +3.3% for DID. Peaks in relative differences were observed for July and August months. Relative differences were <5% in most subgroups, except for fosfomycin and three French regions. Overall and across most subgroups, the correlation between Xponent and SNDS monthly aggregated estimates was almost perfect (r ≥ 0.992 for all subgroups, except for one region). ARIMA modelling showed high consistency between Xponent's and SDNS's DrID time series, but detected timepoints where the series significantly diverged.

CONCLUSIONS:

IQVIA's Xponent and SNDS data were highly consistent. Xponent database seems suitable for monitoring outpatient antibiotic utilization in France.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pacientes Ambulatoriais / Antibacterianos Limite: Humans País/Região como assunto: Europa Idioma: En Revista: J Antimicrob Chemother Ano de publicação: 2021 Tipo de documento: Article País de afiliação: França

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pacientes Ambulatoriais / Antibacterianos Limite: Humans País/Região como assunto: Europa Idioma: En Revista: J Antimicrob Chemother Ano de publicação: 2021 Tipo de documento: Article País de afiliação: França