Longitudinal regional analyses of an1bio1c consump1on in statutory health care insured pa1ents in Germany since 2008
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1 Longitudinal regional analyses of an1bio1c consump1on in statutory health care insured pa1ents in Germany since 2008 Jörg Bätzing- Feigenbaum - Maike Schulz - Mandy Schulz - Jana Gisbert Miralles - Dominik Graf von S1llfried Wennberg Interna1onal Collabora1ve (WIC) Research Mee1ng London - September 2-4, 2015 Zentralinstitut für die Kassenärztliche Versorgung in Deutschland
2 Background Ø Increasing bacterial resistance against an1bio1c drugs is a major Public Health concern worldwide Ø In 2008 the Federal Government implemented a na1onal German An1bio1c Resistance Strategy ( Deutsche An1bio1ka- Resistenzstrategie, DART) Ø DART: latest 5- year- plan Update in 2013 Ø One priority of DART is: monitoring of an1bio1c consump1on in Germany Ø Surveillance of an1bio1c consump1on up to now is focusing on the hospital sector (Robert Koch- Ins1tute, Berlin) SEITE 2 von 24
3 An1bio1c consump1on in Europe (EU, Iceland, Norway) 2012 European Centre for Disease Preven1on and Control (ECDC). Surveillance of an1- microbial consump1on in Europe ECDC. Stockholm 2014 SEITE 3 von 24
4 Trends of cephalosporine prescrip1ons in Europe (EU, Iceland, Norway) European Centre for Disease Preven1on and Control (ECDC). Surveillance of an1- microbial consump1on in Europe ECDC. Stockholm 2014 SEITE 4 von 24
5 Why should we look at ambulatory (outpa1ent) an1bio1c prescrip1on data in Germany? Ø 85% of all an1bio1cs used in the ambulatory health care sector, however, surveillance s1ll focusing on hospital data Ø Above- average use of cephalosporins in Germany Ø Increasing role of cephalosporins in the last decade Ø S1ll important role of fluorchinolones SEITE 5 von 24
6 Main problems due to cephalosporins and fluorchinolones Ø Both, cephalosporins and fluorchinolones are suspected to promote bacterial resistance par1cularly in gram- nega1ve bacteria ( ESBL proper1es ) Ø Fluorchinolones are suspected to result more oden than other an1bacterials in intes1nal superinfec1on with C. difficile responsible for increased risk of severe disease and mortal1ty in elderly pa1ents Ø Use as second- line an1bio1cs SEITE 6 von 24
7 Previous publica1ons on regional varia1ons of an1bio1c prescrip1ons in Germany in Ø (1) Regional varia1on of popula1on- based an1bio1c prescrip1on rates in Germany in 2010 (published ) Ø (2) Regional varia1on of an1bio1c prescrip1on rates in certain infec1ous diseases in Germany in 2009 (published ) Ø (3) Regional varia1on of popula1on- based an1bio1c prescrip1on rates over 1me in Germany (published ) SEITE 7 von 24
8 (1) Popula1on- based an1bio1c prescrip1on rates in Germany in 2010 by regions % of all pa1ents with at least one an1bio1c prescrip1on per year (N = 69.5 million insurees) SEITE 8 von 24
9 (2) An1bio1c prescrip1on rates in certain infec1ous diseases in 2009 by regions (2a) Upper respiratory tract infec1ons: % of pa1ents with an1bio1c prescrip1on (led) Quality indicators (ECDC guidelines) recommand max. 30% and treatment with chinolones max. 5% % of physicians with <5% chinolone prescrip1ons in URT infec1ons (below) N = 17.3 million pa1ents included SEITE 9 von 24
10 (2) An1bio1c prescrip1on rates in certain infec1ous diseases in 2009 by regions (2b) Pharyngi1s & tonsilli1s: % of pa1ents with an1bio1c prescrip1on (led) Quality indicators (ECDC guidelines) recommand max. 20% and treatment with chinolones max. 5% % of physicians with <5% chinolone prescrip1ons in URT infec1ons (below) N = 3.4 million pa1ents included SEITE 10 von 24
11 (3) popula1on- based an1bio1c prescrip1on rates over 1me (3a) Descrip1ve: DDD per insurees, na1on- wide by age groups (3b) Descrip1ve: DDD per insurees, age group 0-14 years by regions N=70.0 (2008); 69.7 (2009); 69.5 (2010); 69.3 (2011); 69.4 million (2012) insurees SEITE 11 von 24
12 (3) popula1on- based an1bio1c prescrip1on rates over 1me (3c) Joinpoint Regression Model: Annual percent change (APC) of DDD per insurees, by age groups and regions N=70.0 (2008); 69.7 (2009); 69.5 (2010); 69.3 (2011); 69.4 million (2012) insurees SEITE 12 von 24
13 (3) popula1on- based an1bio1c prescrip1on rates over 1me (3d) Descrip1ve: Abs. and % of an1bio1c drug groups in DDD per insurees, na1onwide, age group 69 years N=70.0 (2008); 69.7 (2009); 69.5 (2010); 69.3 (2011); 69.4 million (2012) insurees SEITE 13 von 24
14 (3) popula1on- based an1bio1c prescrip1on rates over 1me (3e) Combined regional results: Prescrip1ons (led) and DDD per insurees (right) N=70.0 (2008); 69.7 (2009); 69.5 (2010); 69.3 (2011); 69.4 million (2012) insurees SEITE 14 von 24
15 Current work in progress: Popula1on- based development of the prescrip1on rates over 1me ( ) with focus on cephalosporins and chinolones Ø Na1onwide claims data bases containing 100% of the na1onwide statutorily insured pa1ents (~ 70 million, 86% of the total popula1on) Ø 100% of physician claims (~ 550 million cases p.a.) Ø 100% of filled prescrip1ons (~ 600 million prescrip1ons p.a.) SEITE 15 von 24
16 Results Total of an1bio1c drug prescrip1ons in DDD per insurees between 2008 and 2014, na1onwide by age groups SEITE 16 von 24
17 Results % of an1bio1c drug groups prescribed in 2008 and 2014, na1onwide by age groups SEITE 17 von 24
18 Results Fluorchinolones: Prescrip1ons in DDD per insurees by age groups (15-69 years above; <69 years below) in 2008 and 2014, and by regions (fluorchinolons by group 1-3) SEITE 18 von 24
19 Results Cephalosporins: Prescrip1ons in DDD per insurees by age groups (15-69 years above; <69 years below) in 2008 and 2014, and by regions (cephalosporins by genera1on 1-3) SEITE 19 von 24
20 Results Joinpoint Regression Model: Annual percent change (APC) and p- values of total an1bio1c, cephalosporin and fluorchinolone prescrip1ons in DDD per insurees by age groups and regions between 2008 and 2014 DDD je GKV- Versicherte (Antibiotika insgesamt) DDD je GKV- Versicherte (Cephalosporine) DDD je GKV- Versicherte (Fluorchinolone Alter (Jahre) <15 Jahre J. >69 Jahre gesamt <15 Jahre J. >69 Jahre gesamt J. >69 Jahre gesamt Bundesland APC p- Wert APC p- Wert APC p- Wert APC p- Wert APC p- Wert APC p- Wert APC p- Wert APC p- Wert APC p- Wert APC p- Wert APC p- Wert SH - 4,97 <0,001 1,32 0,05-0,29 0,85 0,63 0,23 0,52 0,66 9,34 <0,01 8,86 <0,001 7,39 <0,01-0,25 0,80-1,49 0,08-0,19 0,83 HH - 6,53 <0,001 1,39 0,10 0,39 0,75 0,42 0,52-2,73 0,15 11,98 <0,001 9,43 <0,001 7,93 <0,01-0,25 0,73-1,05 0,12-0,04 0,95 HB - 4,40 0,01 2,64 <0,05 2,06 0,17 1,84 0,12 0,39 0,50 8,65 <0,001 8,22 <0,001 6,45 <0,001 2,64 0,05 1,18 0,24 2,62 0,03 NI - 7,20 <0,001 0,47 0,51-1,41 0,37-0,51 0,45-1,54 0,22 9,34 <0,01 8,00 <0,01 6,93 <0,01-0,15 0,80-2,17 <0,01-0,35 0,52 NRW - 6,52 <0,01 0,40 0,59-0,63 0,54-0,57 0,41-1,02 0,53 10,25 <0,01 8,31 <0,01 7,33 <0,01-0,62 0,39-2,61 <0,01-0,63 0,39 HE - 6,30 <0,01 0,04 0,96-2,27 0,10-0,80 0,31 0,57 0,68 11,73 <0,01 8,04 <0,01 8,89 <0,01 0,12 0,89-2,11 <0,01-0,16 0,84 RLP - 5,93 <0,01 1,24 0,20-0,73 0,53 0,19 0,82-0,16 0,92 12,13 <0,01 9,95 <0,001 9,13 <0,01 0,52 0,67-1,92 <0,05 0,14 0,90 BW - 5,64 <0,01 0,08 0,91-1,89 0,20-0,64 0,41-0,50 0,73 9,22 <0,01 7,54 <0,01 6,63 <0,01-1,66 <0,01-3,14 <0,001-1,70 <0,01 BAY - 6,19 <0,01 0,27 0,73-1,47 0,28-0,52 0,49-0,84 0,47 10,63 <0,01 9,07 <0,001 8,04 <0,01-1,42 0,06-2,76 <0,0001-1,40 0,04 BE - 6,83 <0,001 0,48 0,48-0,34 0,64-0,53 0,41-3,90 0,09 12,56 <0,01 11,39 <0,001 8,36 <0,01-0,42 0,57-2,13 0,02-0,56 0,46 SL - 5,20 <0,01 1,19 0,21 0,14 0,86 0,01 0,99-0,12 0,93 9,20 <0,01 7,72 <0,001 6,10 <0,01 0,54 0,53-1,78 <0,01 0,23 0,76 MV - 8,27 <0,01 1,20 0,27-0,07 0,96-0,25 0,80-5,53 <0,1 12,83 <0,01 12,63 <0,001 8,10 0,01-1,38 0,23-3,12 <0,01-1,51 0,16 BB - 7,99 <0,001-0,86 0,49-2,52 0,11-1,95 0,12-4,16 0,13 10,55 0,01 8,25 0,01 6,84 0,04-2,20 0,07-3,98 <0,01-2,72 0,04 ST - 8,43 <0,001 1,14 0,25-3,69 <0,01-1,27 0,18-5,70 0,08 12,41 <0,01 5,59 0,01 6,37 0,02-0,23 0,79-4,61 <0,0001-1,39 0,07 TH - 9,79 <0,01 5,56 0,03-13,34 <0,01-1,32 0,22-4,00 0,18 18,39 <0,01-2,54 0,35 8,11 0,01 4,12 0,10-10,34 <0,001-2,14 0,05 SN - 8,84 <0,01 0,15 0,89-1,57 0,20-1,35 0,22-8,45 0,02 11,23 <0,01 7,49 <0,01 5,59 0,04-1,50 0,09-3,28 <0,001-1,67 0,06 Bund - 6,68 <0,01 0,60 0,42-1,60 0,18-0,52 0,46-1,52 0,31 10,74 <0,01 8,05 <0,01 7,57 <0,01-0,60 0,38-2,89 <0,001-0,95 0,16 SEITE 20 von 24
21 Limita1ons Ø Drug prescrip1on data up to now only available on regional level ( federal state ), not on District level Ø % statutory care insurees underlies a broad range of varia1on on regional and District levels between ~ 70 and ~ 97% of the total popula1on Ø An1bio1c prescrip1ons from den1sts are not included (es1mated ~ 10% of all an1bio1cs prescribed na1onwide) Ø Prescrip1on data only include those physicians prescrip1ons which have been claimed by the pa1ents; furthermore, we do not know, if pa1ents actually took their medica1on SEITE 21 von 24
22 Conclusions Ø Claims data may contribute with solid descrip1ve and analy1cal results to the surveillance of an1bio1c prescrip1ons and consump1on in ambulatory health care in Germany Ø The data can reasonably complement na1onal surveillance data Ø Results show regional varia1on and varia1on by age groups poin1ng to regions of best prac1ce Ø Declining trends of general an1bio1c prescrip1ons in children and young adults are significant in all German regions SEITE 22 von 24
23 Conclusions Ø Significant trends call for a na1onwide interven1on to reduce cephalosprin prescrip1ons in the future Ø Declining Fluorchinolone prescrip1ons in the elderly though mostly not significant reveal further need for ac1on Ø Best way of communica1on of the results to the prescribing physicians and how to get them on board is s1ll an unsolved challenge for SEITE 23 von 24
24 Thank you very much for your aren1on Central Research Institute of Ambulatory Health Care in Germany (Zi) Herbert-Lewin-Platz Berlin Germany Tel Fax zi@zi.de SEITE 24 von 24
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