Laboratory quality control (QC) strategies in resource-constrained settings in MSF–OCA programs Daniel Orozco, Pamela Hepple, Derryck Klarkowski Laboratory Specialists - MSF OCA

Basic health care laboratories Malaria/TB microscopy

Secondary level labs for TB/ HIV programs

High technology labs MDR - TB program Uzbekistan

Background Pre-2005 quality of lab performance within MSF OCA labs was unknown We identified the need to set up a standardized QC system Goals of the programme – Monitor performance – Identify poor performers – Provide clinical staff with information on the accuracy of laboratory results

Program design - Field/HQ input for practicality QC protocol implemented in 2005 Key element is the central reporting system, which enables effective management Immediate finding: – Wide diversity of performance – Unacceptable number of centers were performing poorly 2005 – 2007: Significant improvement across the lab network Background

Malaria, TB, Kala Azar, Cutaneous Leishmaniasis and HIV applying similar principles We also have a separate QC methodology for Chemistry, Hematology and CD4 testing Scope

QC Methodology

Monthly random selection Based on crosschecking Results are sent to Amsterdam Analyzed using % agreement, false positivity and false negativity

QC Methodology Based on a small sample size –5 weak positives + 5 negatives To limit workload for laboratory staff Limited reference laboratory capacity – The small sample size is compensated for by Targeting weak positives, where errors are most likely to occur 4-month cohort analysis (40 slides)

– % agreement – % false positives/false negatives – Quartile analysis – Compliance The statistical analysis has been validated by WHO (LSHTM). Analysis:

Results Between 2005 – 2007: QC monthly reports for malaria from 70 centres - 33,346 slides Currently, 40 centers centrally reporting (20 countries)

Results: Improvement QC alone does not improve performance, but is part of a package – auditing system: Standard Indicators, Equipment, reagents, Infrastructure,Training, in-situ support Progressively strengthening Quality Assurance (QA). E.g. malaria manual, Standard Indicators Reports (SIR), upgrading QC database software

Improvement Identification of weak performers and corrective action taken Our QC programme created a healthy “competition” by comparing centres against each other, which are working under similar circumstances

Conclusions Sustainable method for resource-constrained settings. Practical and with minimal investment Statistically valid Successful - e.g. for Malaria – Median increased from 90% to 100% –1 st quartile increased from 86% to 97% Supports accuracy of diagnosis and operational research

Demands commitment: from field staff for continuous operation lab specialists for central monitoring by issuing compliance and benchmarking reports Depends upon support from Medical Director, Head PHD and CMTs for its implementation and follow up. Conclusions