Christina Åhren: Surveillance of antimicrobial resistance, antimicrobial use and health-care infections at a Swedish university hospital

1. Surveillance of antimicrobial resistance,
antimicrobial use and health-care infections
at a Swedish University hospital
Christina (Tinna) Åhrén
MD, PhD, Ass professor
Specialist in Infectious Diseases, Clin Microbiology, Infection Control
Head of Strama Västra Götaland
Patient Safety Unit, Region Västra Götaland
Sahlgrenska Academy, Gothenburg University, Sweden
christina.ahren@vgregion.se

2. The Swedish strategic programme against
antibiotic resistance
National collaboration network
against antibiotic resistance
with the goal to preserve the effectiveness
of available antibiotics.
“ tighten things up”

3. • 1,7 million inhabitants
• 49 counties
Region Västra Götaland (VGR)
• University hospital
• 3 major hospitals
• 13 minor hospitals
• 200 PHC Centers

4. 1700 beds
three sites
Sahlgrenska University Hospital

5. Outline of this presentation
Surveillance of:
• AMR
• AB-consumption
• Hospital acquired infections
Focus on experiences and pit-falls we have
encountered over the years from the
local perspective!

6. How do we perform AB susceptibility
testing in Sweden
How do we test
• Method and BP according to Eucast
• Very high compliance to guidelines
• Disc-diffusion in >90 % of cases
• Automated systems
• Gradient tests
• Broth microdilution
What antibiotics do we test
• Cascade testing: none  1-6 (12) AB/sample
• Depends on specie, sample type and patient data
• Very high freedom of choice and local algorithms in the lab.
• What to test
• What to report

7. We test and report 5-6 AB
in most urine samples
Clinicians culture a lot!
AB tested for E. coli in urine samples in European countries

8. Most labs only partially follow recommended
AB to be tested in all isolates
survey from 23 labs in Sweden
Sample from primary care (blue), hospital care (red)
S. aureus
wounds
Pneumococci H. influenzae
Respiratory samples
E. coli
urine
Diagnostic stewardship = fine Surveillance = ?

9. 50% tested at SU are PNSP
Respiratory samples Blood samples
Resistance in pneumococci
Beware of the denominator and local algorithms when
evaluating resistance rates
20-70 isolates/hospital

10. 95% confidence interval in relation to number of
samples tested at certain resistance levels
No of samples tested
Rate of R 5000 1000 300 200 100 50 30
15% R 14-16 13-17 11-19 10-20 8-22 5-25 2-28
10% R 9-11 8-12 7-13 6-14 4-16 2-18 0-21
5% R 4-6 4-6 3-7 2-8 1-9 0-11 0-13
2% R 1,6-2,4 1-3 0-4 0-4 0-5 0-6 0-7
O. Aspvall, HPA
blood samplesUrine samples
Beware of the denominator when evaluating changes in rates

11. www.who.int/glass
Local pathogens surveyed
(low-endemic setting)
Most GLASS-pathogens are rare in Sweden and/or with
low resistance rates in the local setting
H. influenzae, Pseudomas sp.
Respiratory samples
Wound samples

12. National agreement - test these AB for surveillance,
report those appropriate from clinical data
Blood, wound
Blood urine
Diagnostic
stewardship 
Quinolones
not reported to
Primary care

13. National agreement - test these AB for surveillance,
report those appropriate from clinical data
Blood resp.
sample
Blood resp.
sample

14. Gather and present data for action, E. coli in urine
National level, Yearly most lab. in Sweden, data from PHA (Swebar)
Regional level, yearly comparison from primary (red) and hospital (blue) care,
all 4 lab, VGR
TMP=20%

15. Gather and compare data for action, E coli in blood.
Comparison 4 major hospitals VGR
Yearly rates, Sahlgrenska University hospital

16. Sudden increase in ciprofloxacin-resistance
primarily in blood samples, an invasive clone?
Data from the 4 major hospitals
Blood samples Urine samples
Gather and compare data for action, E coli in blood, urine

17. Surveillance at ward/speciality level
Clinical samples
• To guide empirical treatment; often too low denominator
• Hematology, Urology: very high quinolone-resistance in E. coli
• Outbreak/transmission surveillance
• clinician or microbiologist becomes suspicious
• a particular resistance marker needed to draw attention
• HLAG resistant enterococci in, tracheostoma in one ICU
• TMP-resistant K. pneumoniae in blood in neonates
• AG-resistant S aureus in blood in neonates
• screen when suspect something
• several colonised patients when cluster of clinical cases appear
Screen samples to prevent/forsee outbreaks in selected
wards with high risk patients
• Weekly screen all neonates fore MDR bacteria as MRSA
• Admission screening in hematolgy etc

18. Reportable (MDR) resistant isolates surveyed
number of cases: screen + clinical samples
(HPA webbsite)
Eachcounty
cases/year
MDRGN with
ESBL (CPE)

19. National resistance rates based on clinical samples
Resistance (R) in E coli in
urinary samples
rather stable
Resistance (R) in S. aureus
in wound samples
rather stable and low

20. Resistance rates in sewage correlated rather well with
resistance rates in the clinical samples.
Hutinel M, Huijbers P, Fick J, Åhrén C, Larsson DGJ, Flach CF. Population-level surveillance of antibiotic
resistance in Escherichia coli through sewage analysis. Eurosurveillance 2019, 24(37).
Sewage analyses as a complement to
clinical surveillance?

21. Gather and present data for comparison – (outpatient) prescriptions
(prescriptions/1000 inhabitants and year)
Monthly comparison all regions in
Sweden, data from PHA
European level
Quarterly comparison all counties in VGR
data from Strama VG
2012  2019

22. Gather and present data for comparison – prescriptions, local data
What have they prescribed!
Quarterly comparison of
PHCC
Prescriptions/
patients registered
(patients- visits)
Quarterly comparison of
hospitals
Prescriptions/
patients admissions + visits

23. Gather and present data for comparison – inpatient care
(DDD/1000 inhabitants and year/day)
Quarterly comparison all regions
in Sweden, data from PHAEuropean level
Quarterly comparison of the
larger hospitals in VGR
• DDD/ 1000 inhabitants and year, day
• DDD/ 100 patient days
• continuous decrease in patient days
• DOT (days of therapy) ?

24. Gather and present data for comparison – inpatient care , local data
What have they prescribed!
Quarterly comparison of hospitals
DDD versus PDD (prescribed daily doses) / 100 patient days

25. Gather and present data for comparison – in patient care, local data
What type of AB have they prescribed- parenteral AB!
Narrow or broad spectrum antibiotics
penicillins cefalosporins

27. Data for action –audit and feedback from an ID specialist
Skåne University hospital
• 27 % reduction in AB
• 2300 less DOT
• Mortality, LOS,
readmission stable
• 1 hr twice weakly/ 20
patients
All patients with AB surveyed
• AB
• Shorten courses
• iv per oral
• Broad  narrow spectrum
• Knowledge exchange!
DOT
Third gen. Cefalosporins
Quinilones
Clindamycin
Nilholm H et al Open Forum Infect Dis. 2015 Mar 23;2(2)

28. DATA for ACTION – infection tool - inpatient care!
continously and almost in real time
treatment in relation to initially suspected diagnosis
Treatment for
community aquired pneumonia
% penicillins/total AB
Treatment for
community aquired cystitis
% quinolones/total AB

29. Infection tool - how does it work locally?
1. An antibiotic is prescribed in
the electronic medical
records system
2. A pop-up window appears 
three choices for AB-
prescription
- Hospital aqcuired infection
- Community aqcuired
infection
- Prophylaxis
3. Approx. 9 subchoices on type
of infection, ie UTI
4. The prescriber highlights one
and presses the send button
Ward level
AB prescribed
Diagnose for AB

30. Data for action – quartely incidens of HAI and type of HAI
Regional level to compare hospitals
Hospital and ward level
Incidence of HAI, hospitals
Incidence of HAI, surgery dept.Incidence of HAI, different specialties
Type of HAI, different hospitals

31. Misclassification of CAI and HAI  continuous education is needed!
Alternatives to infection tool
• study selected numbers of medical records
• yearly point prevalence survey by ID-specialist
• continuously recorded by Infection control specialist
Misclassification
• Primarily affects
incidence of HAI
• AB-prescribing is
correctly surveyedHAI
CAI
Proportion of admissions with HAI and CAI

32. Take home message
surveillance at the local level
AMR - survey
• Survey clinical isolates and most prevalent combinations
• (not only) blood and different specimens separately
• be aware of laboratory algorithms and denominators
• use screen samples for outbreak/transmission awareness
but not for survey to guide treatment guidelines
AMR, AB-prescribing and HAI -survey
• Always consider type of care and patients surveyed
• Compare findings with others, but not to often
• Data at ward/speciality level
• beware of denominator
• best for action, rise of attention

33. There are som dark clouds coming up
Hopefully data for action may help!
Thank you for the attention!