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Hospital  Level  Resistance  Data   The  Cape  Town  Perspec7ve   Andrew  Whitelaw  


The  Hospitals  

•  Groote  Schuur   •  Ter7ary  level   –  893  beds   –  28  ICU  beds   –  Oncology,  transplant  

•  Red  Cross  Children’s   •  Ter7ary  level   –  –  –  – 

240  beds   22  ICU  beds   Burns  unit   Oncology,  transplant  


The  laboratory   •  Na7onal  Health   Laboratory    Service   •  SANAS  accredited  (ISO   15189)  since  2002   •  3  microbiologists,   24-­‐28  technologists  /   technicians   •  2000  BC  /  month   •  800  resp  /  month  


AST   •  Vitek  II  (BioMerieux)   with  expert  system   •  Disc  diffusion  (backup)   •  Etest  (S.  pneumo)   •  CLSI  criteria,  updated   annually   •  EQA  –  NHLS  and  NEQAS   •  IQC  on  all  reagents,   cards,  media  etc  


The  Laboratory  Informa7on   System   •  DISAlab  (SA    product)   •  All  samples  and  results  captured   •  Scope  for  inter-­‐laboratory  varia7on   –  Confusion…  

•  All  results  stored  centrally  (data  warehouse)   •  Searchable  –  within  reason   –  Locally   –  via  CDW  

•  NO  link  to  hospital  informa7on  system   •  NO  admission  /  outcome  data   •  NO  reliable  clinical  data  


The  new  LIS   •  Trak  Care  (LabTrak)   •  Run  off  central  server   •  A`empt  to  standardise  na7onal  repor7ng   –  Wait  and  see…  


Available  Data  –  Rou7ne  Lab   •  Suscep7bility  summaries   –  By  ward  (dependent  on  data  capture)   –  By  specimen  type  (dependent  on  data  capture)   –  By  organism  type   •  Genus,  group  (Enterobacteriaceae,  non-­‐fermenters  etc)  

–  By  month,  quarter,  half,  year   –  Duplicates  excluded  (same  pa7ent,  specimen,   organism,  within  2  week  window)  

•  Individual  pa7ent  level  data  extracts  more   difficult  (need  more  manual  cleaning  up)  


Available  data  –  Rou7ne  Pharmacy   •  Usage  /  ward   •  No/limited  individual   pa7ent  data  (as  yet)   –  Dura7on   –  Dose     –  Indica7on   –  Prescriber  


Available  data  –  Hospital  system   •  Admission  /   discharge   •  Death   •  Diagnosis   •  No  case  notes    


Available  data  -­‐  Other   •  Research  studies   –  HAI  surveys   –  Bacteraemia  surveys  

•  Surveillance  –  respiratory,  meningeal,  enteric   pathogens   –  S.  pneumoniae,  H.  influenzae,  N.  meningi7dis   –  Salmonella,  Shigella   –  Cryptococcus  


So  how  do  we  use  the  data?   •  •  •  • 

Monitor  current  /  emerging  resistance   Guide  empiric  choices   Review  interven7ons   Monitor  an7bio7c  usage  

•  Present    /  publish  


Monitor  Resistance   P.  aeruginosa  BCs   100   90   80   70  

%  R/I  

60   50  

2008_01-­‐06  (13)   2008_07-­‐12  (14)  

40  

2009_01-­‐06  (7)  

30  

2009_07-­‐12  (7)  

20   10   0  

2010_01-­‐06  (7)   2010_07-­‐12  (15)  


Monitor  Resistance   K.  pneumoniae  from  BCs   100   90   80   70  

%  R/I  

60   50   40   30  

2008_01-­‐06  (61)   2008_07-­‐12  (42)   2009_01-­‐06  (68)   2009_07-­‐12  (47)   2010_01-­‐06  (69)  

20   10   0  

2010_07-­‐12  (54)  


Guide  empiric  therapy   Enteric  GNB  from  BCs   100   90   80   70  

%  R/I  

60   50   40   30  

2008_01-­‐06  (121)   2008_07-­‐12  (93)   2009_01-­‐06  (135)   2009_07-­‐12  (113)  

20  

2010_01-­‐06  (164)  

10  

2010_07-­‐12  (95)  

0  


Monitor  an7bio7c  use   Defined  daily  dose   1200  

1000  

800  

DDDs  

B  wards   ICU  

600  

D  wards   E  wards  

400  

G1  

200  

0   Amikacin  

3rd  gen   cephalosporin  

Ertapenem  

Meropenem  

Piptazobactam  

Vancomycin  

Defined  daily  dose  calculated  using  dose  for  a  10kg  child,  assuming  no  wastage  


Interven7on   Ceph  R  and  use  at  GSH  

Oliver  S,  Poster  1291,  ECCMID  2008  


Oliver  S,  Poster  1291,  ECCMID  2008  


Surveillance   Classifica7on  of  Bacteraemia   •  Pos  BCs  no7fied   telephonically   •  Manually  entered   onto  excel     –  Demographics   –  Organism   –  Site  of  infec7on   –  Key  an7bio7cs  


Org  and  resistance  by  site  (2000)   Ward isolates

ICU isolates

Community isolates

Total

ESBL pos AmpC pos Quin Res Amik Res Gent Res Piptazo res Mero Res

19 19 14 14 32 10 6

20% 20% 15% 15% 34% 11% 6%

32 31 31 43 0 18 24

24% 24% 24% 33% 0% 14% 18%

15 19 9 4 26 3 2

7% 8% 4% 2% 11% 1% 1%

66 69 54 61 131 31 32

15% 15% 12% 13% 13% 7% 7%

MRSA Meth R Coag neg Staph E.coli K. pneumonia Enterobacter spp Klebsiella spp Proteus spp Serratia spp Citrobacter spp A. baumanii S. maltophilia P. aeruginosa Salmonella spp Pantoea spp Other Acineto Other Pseudomonas Total GNB S. aureus Coag neg Staph

19 6

44% 50%

7 6

47% 75%

9 4

15% 50%

35 16

30% 57%

17 13 12 0 5 8 1 15 4 9 0 2 6 1 93 43 12

5 29 20 4 0 10 2 24 16 14 2 2 2 1 131 15 8

108 38 17 4 14 4 5 3 1 5 29 0 0 2 230 59 8

130 80 49 8 19 22 8 42 21 28 31 4 8 4 454 117 28


Future  plans   •  Link  HIS  to  LIS   •  Ac7ve  surveillance  for  Klebsiella,  S.  aureus   bacteraemia   •  Capture  community  vs  health  care  associated   on  LIS  (bacteraemia)   •  Be`er  use  pharmacy  data  /  pharmacists  


THE  END   THANK  YOU  


Monitor  Resistance   A.  baumannii  from  BCs   100   90   80   70  

%  R/I  

60   50  

2008_01-­‐06  (17)   2008_07-­‐12  (28)  

40  

2009_01-­‐06  (38)  

30  

2009_07-­‐12  (32)  

20   10   0  

2010_01-­‐06  (38)   2010_07-­‐12  (45)  


Enteric  GNB  from  BCs  

In-­‐pa7ent  wards,  oncology  (2010,  n=124)   80.0   70.0   60.0   50.0   40.0   30.0   20.0   10.0   0.0  


/dr_andrew_whitelaw