Consumption of antibiotics at the national level – human ... · Consumption of antibiotics at the national level – human medicine ... Nursing home (LTCF) 560 3,53 2 ... P01A Agents

Consumption of antibiotics at the national level – human medicineAnne IngenbleekMat GoossensNatacha ViseurSylvanus FonguhNaima HammamiMarie-Laurence LambertKarl MertensKatrien LatourBéatrice JansBoudewijn Catry*www.nsih.be

Anne IngenbleekMat GoossensNatacha ViseurSylvanus FonguhNaima HammamiMarie-Laurence LambertKarl MertensKatrien LatourBéatrice JansBoudewijn Catry*www.nsih.be

Rue Juliette Wytsmanstraat 14 | 1050 Brussels | BelgiumT +32 2 642 51 11 | F +32 2 642 54 10 | email: [email protected] | http://www.nsih.be

Causal relationship antibiotic consumption & resistance

Carb

apen

em-r

esis

tant

Pseu

dom

onas

aeru

gino

sa(%

)

Carb

apen

emus

e (D

DD

s)

Lepper PM et al., 2002 (Germany)

Intervention programmes (AST)

Causal relationship inadequatetherapy & mortality

The Influence of Inadequate AntimicrobialTreatment of Bloodstream Infections onPatient Outcomes in the ICU Setting*

Ibrahim et al., Chest 2000, 118 (1)

ObjectiveTo demonstrate at the individual patient level

associations between antibiotic (AB) consumption and antibacterial resistance

• Infections & colonisation (Pathogens & commensals)• Dosis/response effect (Defined Daily Dose, WHO)• Adjusting for covariates

Risk factors for antibacterial resistance at the individual level: a multicentric study (IARG)

Evidence: aggregated population level

Risk factors MRSA infection/colonisationmultivariate analysis (n= 6844)Variable Adjusted OR (95%CI) p-value

MRSA positive related to type of health care setting

No admission 1527 1 -

Acute hospital 4647 0,86 0,74 1,01 0,069

Nursing home (LTCF) 560 3,53 2,79 4,46 <0,001

Other setting 110 1,43 0,93 2,19 0,102

AB consumption prior to sampling (prescription prior or on the day of sampling)

Absent 1519 1 -

Ambulant (FARM) 3706 0,91 0,73-1,14 0,425

In hospital (HOSP) 1619 1,62 1,30 2,01 <0,001

Amount of AB use prior to sampling

per DDD 1,32 1,25 1,40 <0,001

Age category

0-14 757 1 -

15-54 1837 1,63 1,23 2,16 0,001

55-104 4250 4,32 3,32 5,63 <0,001

Monthly FQ consumption, expressed as DDD/1000 PD. Filled circles, pre-intervention period values; open circles, intervention period values; diamonds, post-intervention period values.

Lafaurie M et al. J. Antimicrob. Chemother. 2012;67:1010-1015

© The Author 2012. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: [email protected]

Monthly consumption of ABHR solution.



Change in monthly FQ-resistant P. aeruginosa rates, from 2002 to 2010.



Change in monthly MRSA rates, from 2002 to 2010.



Mission

To provide standardized definitions and tools for the containment of health care associated infections in hospitals and nursing

homes, and to establish national reference data on incidence of nosocomial infections and antimicrobial resistance.

SURVEILLANCE (1/2)SURVEILLANCE (1/2)

Four Mandatory Surveillances in Acute Care Hospitals

1. Methicillin resistant Staphylococcus aureus2. Clostridium difficile (optional: ribotyping)3. Antimicrobial use in hospitals4. One out of 4 optional surveillances:

• Septicaemias hospital wide• Surgical site infections • Intensive care units • Extended spectrum beta-lactamases

In progress: quality indicators

SURVEILLANCE (2/2)SURVEILLANCE (2/2)Volontary projects in Hospitals & Nursing homes

Hand hygiene campaigns (fifth in preparation, launch 2012)Point Prevalence survey on HCAI & AMMRSA, ESBL & VRE in Nursing homes (BAPCOC)

Other projects - Expertise

EARSS, ESAC, BelVet-SAC, ESVAC, PILGRIM…TATFAR, CODEX alimentarius (WHO/FAO/OIE)promotor Master Thesis, reviewing articles, parlementary questions

Point prevalence survey: PPS (photo)

Surveillance contineously (film)

&

Surveillances

&

FEEDBACKMRSA

Campagnes

IndicateursUSI & ISOSepticémies

C. difficile

Gram -

ABU

Rectangle = mandatory

Jaarlijks aantal doden

2000 in 2008(www.wiv-isp.be)

MRSA in ziekenhuizen: 6121 MRSA infecties in 2010 (www.nsih.be)Ongeveer 525 doden door nosocomiale MRSA infectie in 2007

944 in 2009 (bivv.be)

Courtesy: S. Vandendriessche

MRSA evolution

Portage connu 43,6%

Transfert d'un hôpital 14,1%

Transfert d'une MR/MRS 12,6%

Transfert d'un Hôpital et MR/MRS

6%

Communautaire 14,4%

Contacts inconnus9,3%

Jans & Denis, 2011Individual hospital/NH is client!

Carbapenemase producing enterobacteriaceae

SHC, 2012

Global evolution of hand hygiene compliance

4th campaignpreliminary results!



&

Materials & methodsSpecialities to be reported (WHO, ESAC,

pubMED) ATC classification:

A07A Antibiotics for gastro-intestinal useJ01, P01AB AntibioticsJ02, D01BA Antimycotics for systemic use J04A Tuberculostatics

AmphenicolsJ01B0Antifungals for systemic use D01BTetracyclinesJ01A3Agents against amoebiasis/protozoal diseasesP01AIntestinal anti-infectivesA07ASulfonamides and trimethoprimJ01EDrugs for treatment of tuberculosisJ04AAminoglycoside antibacterialsJ01GMacrolides, lincosamides and streptograminsJ01FAntimycotics for systemic use J02AOther antibacterialsJ01XQuinolone antibacterialsJ01MOther beta-lactam antibacterialsJ01D Beta-lactam antibacterials, penicillinsJ01C

Class ATC

Outils informatiques

SEP, SI (ICU), ISO (SSI), HH: NSIHwin (Application MS Access)

CDIF, MRSA … ABU (déc 07)…: NSIHweb• => comparaison immédiate avec les données nationales• => mise à jour « automatique »• => input & upload des données ( charge de travail)• Données communes (dénominateurs/mois,

charactéristiques des hôpitaux, services & unités)• Autres fonctions d’analyse etc (ex. détection des

épidémies) à définir avec groupe de travail

DATA MANAGEMENT

Upload Feedback

• ‘Tarification Units’• ljst TUC codes

• ‘molecules’• expressed as DDD

(Defined Daily Dose)

use (TUC) / Factor = use (DDD)

Example

Example : amoxicillin

J01CA04

J01CA04ATC code

20 units

40 unitsUse (TUC)

1000

1000

DDD202AMOXICILLINE TEVA

CAPS 1 X 500 MG744185

54AMOXICILLINE TEVA SIR 1 X 250MG/5ML

744433

Use (DDD)FactorLabelTUC

use (TUC) / Factor = use (DDD)

REALTIME FEEDBACK

FEEDBACKCompare own use with national mean

AUTOMATIC FEEDBACK Local follow up

FEEDBACK

OBJECTIVES MODULE

Hospitals• realtime feedback

• Automatic recalculation (TUC DDD)

• Local monitoring information for ABMT

Authorities• trend monitoring

DDD/1000 patient days

DDD/1000 admissions

J01: ANTIBACTERIALS FOR SYSTEMIC USE

Antibacterials for Systemic Use (JO1)

0

100

200

300

400

500

600

700

2006 2007 2008 2009 2010

DD

D/1

000

hosp

italis

atio

n da

ysNational meanmedian (p50)

Antibacterials for Systemic Use (J01)

0

1000

2000

3000

4000

5000

6000

2006 2007 2008 2009 2010

DD

D/1

000

adm

issi

ons

National meanmedian (p50)

Graph 1 ‐ Total AMD use ALL antimicrobials (DDD/1000 beddays), 2006‐2010J01 + J02 + J04A + A07A + P01AB + D01B

573570558565479p50

20102009200820072006

Graph 1 – use ANTIBACTERIALs (DDD/1000 beddays), 2006‐2010

ANTIBACTERIALS FOR SYSTEMIC USE J01

537545530527467p50

20102009200820072006

J01

Non Pediatric Wards

Stratified by ward: antibacterials

Stratified by ward: antimycotics

ESACNational level, all antimicrobials included

Year Participants Total DDD for the year DDD/1000 Nights

2008 121 7315319.20 579.734

2009 124 7273099.57 583.651

2010 120 6940067.65 585.087

2011* 106 6561559.15 581.215

2011*: The data collection for the year 2011* is on‐going.

HOSPITALS

Community

Hospitals

Evolution - long term



&

Point Prevalence Survey: Hai - ABU

Why? - A need to standardize protocols in EU- Measuring prevalence, not incidence short measuring period

less labor intensive

What is measured? AB use – Hai

Result:• estimate the total burden• describe patients

• invasive procedures• infections • antimicrobials prescribed

Point Prevalence Survey: Hai - ABU

Percentage patients with HAI: 7.0%

0%

5%

10%

15%

20%

25%

11 13 15 20 38 59 58 34 27 63 49 30 50 2 62 14 51 61 40 37 7 48 55 41 16 18 17 46 33 24 57 21 12 36 56 19 39 43 60 5 53 22 42 4 29 45 23 28 32 44 52 35 6 54 8 47 3 1 26 31 9 25 10

Hospital number

% p

atie

nts

with

HA

I

Mean prevalence: 7% [0%-23%]

Courtesy UA

Prevalence of AM use by Hospital

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

% on AM

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

10 17 44 7 19 20 8 13 6 60 28 4 23 18 9 5 12 3 22 21 11 59 25 45 26 43 47 16 34 36av

erag

e 61 52 54 39 32 40 46 49 35 42 41 24 33 58 1 37 27 56 62 2 63 29 50 51 48 53 57 31 55 14 38 30 15

Mean: 38% [2% – 100%] Net: 35%

Courtesy UA

Point Prevalence Survey: Hai - ABUOn antimicrobials: 36.6%

Mean antimicrobials for those on antimicrobials: 1.5

:acute hospital-acquire:community-acquired :acquired in NH:medical prophylaxis :unknown reason:single dose:one day:> 1 day

Surg

Les infections liées aux soins et la consommationd’antimicrobiens dans les institutions de soins chroniquesbelges (projet HALT, 2010)

Rue Juliette Wytsmanstraat 14 | 1050 Brussels | BelgiumT +32 2 642 51 11 | F +32 2 642 50 01 | email: [email protected] | www.wiv-isp.be

Résultats: Nursing homes

• 722 LTCF de 25 pays européens

• 111 établissements belges• 107 MRS

• 3 institutions Sp

• 1 institution de psychiatrie

chronique

• 12 727 résidents éligibles

Eligible residents:< 250250 ‐ 499500 ‐ 9991000 ‐ 4999> 5000

Courtesy: K. Latour

Résultats: caractéristiques des résidents

50% 85+ ans 25.7% masculin

8.1%3.4%0.2%2.6%

41.1%48.3%59.0%

020406080

100

Incontinence

Désorientation

Chaise roulanté ou alitée

Cathéter urinaire

Cathéter vasculaire

Plaie d'escarre

Autre plaie

Résultats: la consommation d’antimicrobiens

• 554 résidents, 578 molécules

• Prévalence: 4.7% (0‐15.7%)

• 96% antibactériens à usage systémique (classe ATC J01)

Aminoglycosides (J01G) 0,4%

Tétracyclines (J01A) 2,3%

Sulfamides (J01E) 3,2%

Autres beta‐lactams

(J01D) 4,1%Macrolides (J01F) 4,7%

Quinolones(J01M) 20,4%Beta‐lactam

pen. (J01C) 27,9%

Autres antibactériens(J01X) 36,9%

1

3

2

Résultats: la consommation d’antimicrobiens

• 68.5% prescriptions thérapeutiques• 31.5% prescriptions prophylactiques

48.7% 31.8% 10.8%

Résultats: les infections liées aux soins

•390 infections confirmées, 361 résidents

•Prévalence: 3.1% (0‐11.9%)

Infection GI; 21; 5%Fièvre; 3; 1%

BSI; 2; 1% Autre infection; 21; 5%

Nez/gorge/oreilles/yeux; 39;

10%

Infection respiratoire; 187; 48%

Infection cutanée; 81;

21%

Infection urinaire; 36; 9%1

3

2

4

Courtesy: Jans B. & Latour K.

Concluding remarksWithin hospital evolution >> bench marking

stratification: service (ICU), type, size, regionHospital evolution

MRSA, MRE, Cdiff, HH compliance… can be combined- Monthly introductin required

- Many have done this retrospectively!!!

Future: evolution i.f.v. DRG (project AMTABU)- hip/knee replacement & CAP

Nursing homes: less AB use profylaxis UTI can be improved

Links

• NSIH web• https://nsihweb.wiv-isp.be .

• Manual NSIHweb - AB• www.nsih.be > geneesmiddelen > download > handleiding

voor de webapplicatie• List TUC codes

• www.nsih.be > geneesmiddelen > download > geneesmiddelenregister

• Protocol• www.nsih.be > geneesmiddelen > download >

surveillanceprotocol

Acknowledgements

Slides available on: www.nsih.be

[email protected] (ABU, ESAC)

Dr. Stien Vandendriessche (LA-MRSA)

Drs. Katrien Latour (HALT)

Mevr. Beatrice Jans (MRSA, ESBL, CPE, HALT)

Participating hospitals

[email protected]

Consumption of antibiotics in veterinary medicine

Boudewijn Catry*Anne Ingenbleek Bart PardonStien VandendriesscheBea Janswww.nsih.be

Boudewijn Catry*Anne Ingenbleek Bart PardonStien VandendriesscheBea Janswww.nsih.be

Rue Juliette Wytsmanstraat 14 | 1050 Brussels | BelgiumT +32 2 642 51 11 | F +32 2 642 54 10 | email: [email protected] | http://www.iph.fgov.be

MRSA evolution

n. hôpitaux 29 34 44 48 41 43

Evolution of MRSA‐incidence upon admission

Vandendriessche et al, 2012

QUIZ: Prevalence Livestock associated MRSA

Veal calves farmer a 72% LA-MRSASwine farmer 38% LA-MRSAInpatient hospital 1.6-25% MRSANursing home resident 13% MRSAVeterinarians 7.5% LA-MRSA Poultry farmers a 3% LA-MRSAUpon hospital admission 1.6% MRSA General population 0.5% MRSA

a Samples from non-mixed farms

Livestock-associated MRSA

Gordts, 2007Denis, JAC 2010Denis, EID 2009

Vandendriessche, JAC 2012Garcia‐Graells, E&I 2011

Goossens et al., 2012

18 13

4

103

1

1

4

MRSA ST398 (infection + screening)

ReferentieLaboratoriumvoor Stafylokokken ‐MRSA

Courtesy: Vandendriessche S

Swine farms density

Ribbens, Prev Vet Med 2009

Veal calves density

E. Ducheyne and B. Pardon, 2012

Courtesy: Vandendriessche S

Consumption patterns across animal species

75

Persoons et al., 2012 Callens et al., 2012 Catry et al., under revision Pardon et al., 2012

Courtesy: B. Pardon

Indications and timing

BRD (53%)Arrival prophylaxis (13%), diarrhea (12%), dysbacteriosis (12%)

Pardon ea, JAC 2012

Which compounds are used?

Oxytetracycline (23,7%), amoxicillin (18,5%), tylosin (17,2%) and colistin (15,2%) were most frequently used

Pardon ea, JAC 2012

Resistentieprofiel LA-MRSA

Aminosides Macrolides, lincosamides

Co‐selectie van resistentie

MRSA huidinfecties bij de mens worden vaak behandeld met doxycyclineof clindamycine Niet aangewezen voor LA-MRSA infecties

Vandendriessche, JAC 2012

Possible outcomes of exposureto resistant bacteria

P.L. Geenen, M.G.J. Koene, H. Blaak, A.H. Havelaar, A.W. van de Giessen

Bacteria & Co-selection of Resistance

Evolution E. coli multiresistance




Vaporization: ceftiofur



www.BelVet-SAC.ugent.be

Among European countries 2010: Belgium is the 3rd highestconsumer of antimicrobials in veterinary medicine.

www.BelVet-SAC.ugent.be

Comparison Oral (Feed) vs Injection

Checkley e.a., CVJ / VOL 51 / AUGUST 2010

Resistance E. coli

Type period (N

herds)

N ARIa AMPb

AMC CEF TET TMP NEO GEN SPT STR NAL FLU ENR

Dairy I (10) 447 0.04 2.91 0.45 0.45 8.28 4.25 0.67 1.12 0.22 24.83 1.34 0.22 0 II (10) 396 0.01 2.02 0.25 0 3.79 0.25 1.52 0 0.25 4.55 0.76 0.25 0.25 III (10) 419 0.02 4.3 0.24 0 4.3 3.58 2.15 0.48 0 7.88 1.19 0.72 0.24

Beef I (10) 436 0.03 9.17 1.15 0 6.88 4.13 2.52 0.92 0.69 13.3 2.52 0.46 0.46

II (9) 346 0.06 12.14 1.45 0.58 17.05 5.49 4.91 2.31 0.87 18.21 8.67 4.33 2.89

Veal T1 (5) 276 0.62 93.12 4.71 0.36 94.93 92.75 83.33 45.29 22.46 89.49 79.00 73.13 64.23 T2 (5)

230 0.32 79.57 2.61 1.74 95.22 65.22 27.83 5.22 5.65 78.26 14.01 6.22 4.12

> 25%

Catry et al., 2008 National Report

Dense communities= hotspots for AB & ABR

Vulnerable populations

Co-selection = accumulation – persistence…

Acknowledgements: S Vandendriessche, C Garcia, O Denis,

B Jans, M Goossens, N Viseur, A IngenbleekB. Pardon, B Callens, J Dewulf, F Haesebrouck

the labs & hospitals & nursing homes & veterinarians

[email protected]@@wivwiv--isp.beisp.be

Documents

Consumption of antibiotics at the national level – human ... · Consumption of antibiotics at the national level – human medicine ... Nursing home (LTCF) 560 3,53 2 ... P01A Agents