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Abstract

As antibiotic consumption rates between hospitals can vary depending on the characteristics of the patients treated, risk-adjustment that compensates for the patient-based variation is required to assess the impact of any stewardship measures. The aim of this study was to investigate the usefulness of patient-based administrative data variables for adjusting aggregate hospital antibiotic consumption rates. Data on total inpatient antibiotics and six broad subclasses were sourced from 34 acute hospitals from 2006 to 2014. Aggregate annual patient administration data were divided into explanatory variables, including major diagnostic categories, for each hospital. Multivariable regression models were used to identify factors affecting antibiotic consumption. Coefficient of variation of the root mean squared errors (CV-RMSE) for the total antibiotic usage model was very good (11%), however, the value for two of the models was poor (> 30%). The overall inpatient antibiotic consumption increased from 82.5 defined daily doses (DDD)/100 bed-days used in 2006 to 89.2 DDD/100 bed-days used in 2014; the increase was not significant after risk-adjustment. During the same period, consumption of carbapenems increased significantly, while usage of fluoroquinolones decreased. In conclusion, patient-based administrative data variables are useful for adjusting hospital antibiotic consumption rates, although additional variables should also be employed.

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/content/10.2807/1560-7917.ES.2016.21.32.30312
2016-08-11
2024-03-19
http://instance.metastore.ingenta.com/content/10.2807/1560-7917.ES.2016.21.32.30312
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References

  1. Dumartin C, L’Hériteau F, Péfau M, Bertrand X, Jarno P, Boussat S, et al. Antibiotic use in 530 French hospitals: results from a surveillance network at hospital and ward levels in 2007. J Antimicrob Chemother. 2010;65(9):2028-36.  https://doi.org/10.1093/jac/dkq228  PMID: 20581121 
  2. Blix HS, Hartug S. Hospital usage of antibacterial agents in relation to size and type of hospital and geographical situation. Pharmacoepidemiol Drug Saf. 2005;14(9):647-9.  https://doi.org/10.1002/pds.1080  PMID: 15700320 
  3. Consumption of antibiotics in public acute hospitals in Ireland data for first half of 2013. Dublin: Health Protection Surveillance Centre; [Accessed: 22 Aug 2015]. Available from: http://www.hpsc.ie/A-Z/MicrobiologyAntimicrobialResistance/EuropeanSurveillanceofAntimicrobialConsumptionESAC/SurveillanceReports/HospitalAntibioticUse/File,14350,en.pdf
  4. Iezzoni LI. Reasons for risk adjustment. In LI Iezzoni. Risk adjustment for measuring health care outcomes. 3rd ed. Chicago: Health Administration Press; 2003. Available from: http://intqhc.oxfordjournals.org/content/16/2/181
  5. Polk RE, Hohmann SF, Medvedev S, Ibrahim O. Benchmarking risk-adjusted adult antibacterial drug use in 70 US academic medical center hospitals. Clin Infect Dis. 2011;53(11):1100-10.  https://doi.org/10.1093/cid/cir672  PMID: 21998281 
  6. Rajmokan M, Morton A, Marquess J, Playford EG, Jones M. Development of a risk-adjustment model for antimicrobial utilization data in 21 public hospitals in Queensland, Australia (2006-11). J Antimicrob Chemother. 2013;68(10):2400-5. PMID: 23689029 
  7. Wiley MM. Using HIPE data as a research and planning tools: limitations and opportunities: A Response. Ir J Med Sci. 2005;174(2):52-7.  https://doi.org/10.1007/BF03169130 
  8. European Centre for Disease Prevention and Control (ECDC). Surveillance of antimicrobial consumption in Europe 2012. Stockholm: ECDC; 2014. Available from: http://ecdc.europa.eu/en/publications/Publications/antimicrobial-consumption-europe-esac-net-2012.pdf
  9. ATC/DDD Index 2016. Oslo: WHO Collaborating Centre for Drug Statistics Methodology; 2015. Available from: http://www.whocc.no/atc_ddd_index/
  10. Donlon S, Houlden M, Oza A. HPSC launches new web-based system to manage hand-hygiene compliance and antibiotic usage data. Epi Insight. 2013; 14(2):1. Available from: http://ndsc.newsweaver.ie/epiinsight/1hoijtrdr8f?a=1&p=31757935&t=17517774
  11. Health Atlas Ireland. Dublin: Health Intelligence Ireland. [Accessed: Mar 2016]. Available from: https://www.healthatlasireland.ie/
  12. R Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2015. Available from: http://www.R-project.org/
  13. Limpert E, Stahel WE, Abbt M. Log-normal distributions across the sciences: keys and clues. Bioscience. 2001;51(5):341-52.  https://doi.org/10.1641/0006-3568(2001)051[0341:LNDATS]2.0.CO;2 
  14. Australian Institute of Health and Welfare. Australian refined diagnosis-related groups (AR-DRG) data cubes. Canberra: Australian Institute of Health and Welfare. [Accessed; 22 Aug 2015]. Available from: http://www.aihw.gov.au/hospitals-data/ar-drg-data-cubes/
  15. Kuster SP, Ruef C, Blliner AK, Ledergerber B, Hintermann A, Deplazes C, et al. Correlation between case mix and antibiotic use in hospitals. J Antimicrob Chemother. 2008;62:(4):837-42.
  16. SARI Hospital Antimicrobial Stewardship Working Group. Guidelines for antimicrobial stewardship in hospitals in Ireland. Dublin; Health Protection Surveillance Centre; 2009. ISBN: 978-0-9551236-7-2.Available from: https://www.hpsc.ie/A-Z/MicrobiologyAntimicrobialResistance/InfectionControlandHAI/Guidelines/File,4116,en.pdf
  17. Oza A, Burns K, Cunney R. Carbapenem use in hospitals has doubled in the last five years. Epi Insight. 2014;15(11):1. Available from: http://ndsc.newsweaver.ie/epiinsight/i99up54i182?a=1&p=48078701&t=17517774
  18. Kanerva M, Ollgren J, Lyytikäinen O, Agthe N, Mottonen T, Kauppinen M, et al. Benchmarking antibiotic use in Finnish acute care hospitals using patient case-mix adjustment. J Antimicrob Chemother. 2011;66(11):2651-4.  https://doi.org/10.1093/jac/dkr333  PMID: 21846673 
  19. Amadeo B, Dumartin C, Robinson P, Venier AG, Parneix P, Gachie JP, et al. Easily available adjustment criteria for the comparison of antibiotic consumption in a hospital setting: experience in France. Clin Microbiol Infect. 2010;16(6):735-41.  https://doi.org/10.1111/j.1469-0691.2009.02920.x  PMID: 19778299 
  20. MacDougall C, Polk RE. Variability in rates of use of antibacterials among 130 US hospitals and risk-adjustment models for interhospital comparison. Infect Control Hosp Epidemiol. 2008;29(3):203-11.  https://doi.org/10.1086/528810  PMID: 18257689 
  21. Hubbard AE, Ahern J, Fleischer NL, Van der Laan M, Lippman SA, Jewell N, et al. To GEE or not to GEE: comparing population average and mixed models for estimating the associations between neighborhood risk factors and health. Epidemiology. 2010;21(4):467-74.  https://doi.org/10.1097/EDE.0b013e3181caeb90  PMID: 20220526 
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