methods for amr surveillance in communities – lessons from the durban site gray al and essack sy...
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Methods for AMR Surveillance in Communities – lessons from the Durban site
Gray AL and Essack SY
Department of Pharmacology, Nelson R Mandela School of Medicine and School of Pharmaceutical Sciences, University of KwaZulu-Natal, Durban, South Africa
Summary of the Durban pilot project Objective
To investigate the association between antibiotic use and resistance over time in respiratory tract infections in the Inner West metropolitan area of Durban
Methods Sputum specimens from consenting patients with self-
reported cough, with or without fever, at 4 convenience sampled sites
Retrospective prescription audit (2 weeks’ Rx per month) from 7 randomly selected private pharmacies, 7 convenience sampled private dispensing practitioners and 7 randomly selected primary health care clinics
Results No direct relationship between resistance levels and
antimicrobial usage; feasibility of establishing a system to generate data of this sort demonstrated
Methodological issues - resistance
Grand aim: “to determine the incidence of resistant infections among the total number of infections in a population” Overcome biases of hospital-based and
treatment failure associated data Need to choose a common infection with easily
accessed clinical material – in our case: respiratory tract infections sputum specimens (vs. oropharyngeal swab) -
minimally invasive ? carriage vs. infection
Problems encountered Negotiating access in both the public and
for-profit private sectors had to use convenience sample
Low return small % of positive sputa (521/3556) – 14.7% preponderance of some isolates - M. catarrhalis
resistance could not be characterised over time H. influenzae – 387/570 (67.9%) S. pneumoniae – 137/570 (24.0%) M. catarrhalis – 46/570 (8.1%)
Time consuming and expensive 3 fieldworkers, travelled 9 945km in 12 months
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No
. o
f p
os
itiv
e s
pu
ta
Q4 '02 Q1 '03 Q2 '03 Q3 '03 Q4 '03 (Q1 '04)
Quarters (Oct 2002 to January 2004)
Reasons for declining returns …
Fieldworker motivation- repetitive task, dealing with difficult patients
Refusal by some patients to give repeated specimens when no immediate clinical benefit was discerned
Potential solutions Rotating sites – difficult to negotiate Community feedback – easier in public sector? Different target infection/carriage
Methodological issues - usage Grand aim: enable “early action to optimize
prescribing patterns and to reduce inappropriate use” move beyond hospital-level utilisation reviews cover all possible sources of community access:
informal (markets) – assumed not to be a major source in South Africa
formal – on-prescription sales by retail (community) pharmacies on-prescription sales by dispensing medical
practitioners issues by state-operated primary health care clinics
(largely nurse practitioners)
Initial challenges – negotiating access (1)
Negotiating access - pharmacies willing to co-operate – allowed random sampling stratified by socio-economic status of area
Data source – original prescriptions;
computerised accessible, good data
on the prescription – allnecessary details
sparse clinical data
Initial challenges – negotiating access (2)
Negotiating access – dispensing doctors Initially reluctant to co-operate – had to resort to
convenience sampling ongoing policy battles around the “right” to dispense currently sell prescription data – source of income for
the independent practitioner association (IPA) stratified by socio-economic
status of area
Data source – clinical records variable quality of data
Initial challenges – negotiating access (3)
Negotiating access – PHC clinics protracted negotiations with provincial and local
authorities – allowed random sampling stratified by size to include 2 large community
health centres (CHCs) mixed medical practitioner and nurse
prescribers
Data source – daily clinic registers
(“tick registers”) Sparse data
Data sources - clinics
Problems encountered …
Small numbers of antimicrobial prescriptions in smaller pharmacies, practices and clinics
Large number of “tick registers” in larger clinics (CHCs) – inability to access all data accurately
Solutions implemented returned to collect extra week of data per site (2
weeks’ Rx) deleted all AM usage data from one
problematic CHC (left with 20 sites)
Further concerns …
Missing data - clinics usually dispense original packs, so quantities could be
assumed – difficult when practices change e.g. increased prescribing of cotrimoxazole for PCP prophylaxis
Choice of denominator usually as DDD/1000 pop/unit time not possible without a “catchment population” or complete
coverage mobile population no “registration” with a provider using both sectors interchangeably
Used Defined Daily Doses (DDD) per 100 patients seen (doctors/clinics) or prescriptions dispensed (pharmacies)
Antimicrobial use - cotrimoxazole
0
5
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35
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Months (from Q4 '02)
Co
trim
oxa
zole
DD
D/1
00p
t
Pharmacies Clinics Doctors
Time and expense
2 fieldworkers (full-time M.Pharm student, ½ day nurse) for medicine utilisation review travelled 15 578km (from Mar ’03 to Feb ’04)
3 fieldworkers for sputum collection travelled 9 945km
Feasibility as an ongoing venture? commitment of health authorities viability of the District Health Systems model routine data vs. periodic (survey) approach
Possible alternative sources of medicine use data (problems) Pharmacies
Wholesaler and distributor sales records Wide range of possible sources, locally and across the
country/ direct purchase from manufacturers – impact of new pricing regulations?
Doctors IPA data (currently revenue generating) Impact of dispensing license regulations and data
privacy regulations? Clinics
Depot issue records Clinic (CHC) to clinic supplies – impact of the DHS and
nature of future contracts with local authorities (municipal health services)?
Conclusions Although no direct relationship between resistance
levels and antimicrobial usage could be shown, the feasibility of establishing a system to generate data of this sort was demonstrated
Given the differences in antimicrobial use patterns in different settings, interventions to contain the development of resistance will have to be carefully tailored for each setting
Choose a different target infection or site of carriage; rotate collection between different sites; need to characterise resistance separately for different settings?
Need to measure AM usage in different settings; could perhaps limit to a few selected months of the year (some seasonal variation)
Acknowledgements
WHO/EDM for funding this pilot project Kathy Holloway (WHO, Geneva) and
Thomas Sorenson (Statens Serum Institut, Denmark) for technical advice and support
Our co-investigators (Wim Sturm, Fathima Deedat), the fieldworkers and laboratory staff, for their hard work and insights into the process
The staff at the facilities, for allowing us access to patients and/or data
The patients, for providing us with sputum specimens
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