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Joint HMA/EMEA Meeting On Promoting Prudent And Responsible Use of Antimicrobials In Veterinary Medicine, 19- 20 May, Marienbad, Czech Republic National experience on collection and analysis of data on Antimicrobial sales and use VetStat -


  1. Joint HMA/EMEA Meeting On Promoting Prudent And Responsible Use of Antimicrobials In Veterinary Medicine, 19- 20 May, Marienbad, Czech Republic National experience on collection and analysis of data on Antimicrobial sales and use VetStat - the Danish experience Vibeke Frøkjær Jensen National Food Institute, Technical University of Denmark

  2. EU conference The ’Antimicrobial Threat’ Copenhagen,1998 Recommendation: ”EU member states should implement monitoring of antimicrobial usage in addition to resistance monitoring” Because resistance data alone do not hold the key to well targeted intervention - resistance trends are the results of forces acting together

  3. 3 Govermental decisions: • 1996: Resistance monitoring - DANMAP • 1998: Decision to establish a drug consumption database based on ”end-user-data”

  4. 4 Data sources and detail of information Pharmaceutical companies (sales to wholesalers and feed mills), Imports National level Wholesalers Pharmacies Feedmills Prescription level Veterinarians End-user Farmer level

  5. 5 Data sources and detail of information - Denmark 1995-2001: Pharmaceutical companies (sales to wholesalers and feed mills) Collected annually by the National level Danish Medicines Agency 1986-1994: Retrospectively Danish Pharmacy Association VetStat, 2001: Pharmacies + Prescription level Feedmills + Veterinarians End-user Farmer level

  6. 6 Collection of veterinary usage data on prescription level - background All therapeutic drugs are prescription-only medicines (POM) (except for feedadditives as coccidiostats ) Vets and farmers can get POMs only through pharmacies (except for POM medicated feed – from the feed mills) Since mid-90’s pharmacies have reported individual sales to the Danish Medicines Agency (DMA) Principles for the foundation of VetStat: Mandatory reporting ”End user data” – in practice: prescription level data Using existing electronic data system – as far as possible! All therapeutic drugs

  7. Data transfer from veterinarians Vet Vet practice practice Vet Vet Vet Vet practice practice practice practice Invoice system company 1 Invoice system company NN VETSTAT Cattle database (industry owned) (+other species)

  8. 8 VetStat – data flow For each presription: Date Drug ID** Drug quantity Disease category ≈ 1.5% Prescriber ID* 0,3% Farm ID* Animal species 15% Age group *relation to other databases Danish 83%(98%) Medicine ≈ 13% Agency 13% 83% VETSTAT - 1-2% NVI 1-2%

  9. 9 Data quality - pharmacies – extracted auto-matically when the prescription is pro- cessed – Logical validation of drug code – Data used for billing => amounts correct • 99,9 % of sales is recorded (billing) – • Appr 1 % is missing farm ID, animal species etc. (2008) (2003: 5-7%) Future electronic prescriptions => extensive validation at entry Data quality - feed mills • Logical validation at data entry for medicated feed • Farm-ID, Species etc. are valid for all records • Some feedmills have been missing – historically. Veterinarians • Technical problem (private companies): – Multiplication errors in amount for individual veterinarians, – Data loss during transmission from vets to CDB

  10. 10 Trends in use of AM therapeutics for pigs, Denmark 2001-2007 Sows and piglets Weaner pigs Finisher pigs Sows and piglets 80 45 8.0 4.5 1.4 75 40 7.5 4.0 1.2 2.0 35 70 3.5 7.0 1.0 1.8 30 65 3.0 6.5 ADD kg /pig produced ADD 15 /pig produced ADD 50 /pig produced 0.8 25 1.6 60 2.5 20 2.0 0.6 15 1.5 0.4 10 1.0 0.2 5 0.5 0 0.0 0.0 2001 2002 2003 2004 2005 2006 2007 2001 2002 2003 2004 2005 2006 2007 2001 2002 2003 2004 2005 2006 2007 Macrolides Tetracyclines Macrolides Tetracyclines Macrolides Tetracyclines Pleuromutilins a) Lincosamides c) Pleuromutilins a) Lincosamides c) Pleuromutilins a) Lincosamides c) Penicillins, b-lact. sen. b) Penicillins, other Penicillins, b-lact. sen. b) Penicillins, other Penicillins, b-lact. sen. b) Penicillins, other Cephalosporins Aminoglycosides Cephalosporins Aminoglycosides Cephalosporins Aminoglycosides Sulfonam./trimeth. Penicillin/spectinomycin Sulfonam./trimeth. Penicillin/spectinomycin Sulfonam./trimeth. Penicillin/spectinomycin Total Total Total

  11. 11 Apramycin and gentamycin use and resistance in pigs (Jensen et al, JAC 2005) Consumption OR=1.6/50units, p<0.01 Time (year) OR=1.9/year, p<0.01 300 25 250 b / 1000 pig produced 20 % resistant isolates 200 15 150 10 ADD 15 100 5 50 * a * a * a 0 0 1998 1999 2000 2001 2002 2003 2004 1 A pram ycin Gentam ycin Clinical E .coli (gentam ycin) Indicator E.coli (gentam ycin) Clinical E .coli (apram ycin) Indicator E.coli (apram ycin+gentam icin)

  12. 12 Prescription by disease groups in calves, 2005 ADDkg (1000's) Tiamulin 1200 Penicill. /others Tetracycliner 1000 Sulf/trim 800 Penicill, narrow 600 Makrolider Lincosamider 400 KombinationsA 200 Fluorouinolon Colistin GI 0 Cephalosporin r s e y n r l n r e d a o o i h d n k i t t i a t U s c t O / s r u S i e d p Aminogl.GI N t s o n e C r i p o R / e r s t m R s a i Amfenikoler L G

  13. Association between price per ”course dose” 18.11.2008 and consumption 1

  14. 14 Regional variation in consumption 2002 2003 2004 Kilde: DANMAP 2004 ]11;12] 8] ]8;9] ]9;10] ]10;11] ]12;13] ]13 ADD kg per (1000 ”kg-live.pig-days per region)

  15. 15 Conclusions The VetStat vision: • optimisation of drug use and prudent use guide lines. – surveillance, research, follow National interventions – guidelines, control (Danish Food Agency) VetStat has given the potential of detailed multifactorial modelling of effect of usage on resistance ⇒ identification of consumption patterns/high risk herds. ⇒ valuable information on usage patterns and factors affecting usage The National Defined Animal Daily Dose is superior to kg active compound – both for surveillance and research An international DDDvet will be superior for international surveillance

  16. 16 Conclusions, continued • Using existing electronic data systems – cheap – potential high data quality if correlated with billing!!! many problems solved and lessons learnt!

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