ANALYSIS OF RIFAMPICIN INDETERMINATE RESULTS USING SHEWHART CONTROL CHARTS: IMPLICATIONS FOR PATIENTS AND TUBERCULOSIS CONTROL Programs

BackgroundAntimicrobial resistance is a growing global public health concern, and multidrug-resistant tuberculosis is responsible for roughly one-quarter of all antimicrobial-resistant infection-related deaths worldwide. GeneXpert is a rapid, automated molecular test that detects multi-drug-resistant tuberculosis using rifampicin as a predictor. It was recommended by the World Health Organization (WHO) in 2010 for national tuberculosis programs in developing countries; however, it has limitations. Indeterminate results for Mycobacterium tuberculosis indicate that the test was unable to determine whether the bacteria were resistant to rifampicin. This study used Shewhart Control Chart, which has action limits, to investigate the causes of indeterminate results. MethodsThe control limits on the Shewhart chart are central, upper, and lower. GeneXpert indeterminate results obtained between January 2017 and December 2020 in a tertiary hospital in a low and middle-income country were plotted. Points above the upper control limit were used to determine whether or not the process was under control. ResultThe proportion of GeneXpert results that were indeterminate varied, with 58% exceeding the upper limit. Only 42% were within the control limit, in comparison. The majority of the laboratory results revealed an out-of-control signal by displaying points outside the control limits or non-random patterns of points known as special-cause variation, according to this study. ConclusionsGeneXpert indeterminate results have an impact on patient management by preventing accurate diagnosis and delaying the start of anti-tuberculosis medication. Machine malfunctions, insufficient bacterial load, poor quality samples, operator errors, or faulty laboratory materials could all be to blame. Regular equipment checks by laboratory personnel, program sponsors, or leadership will be extremely beneficial in achieving the desired results and initiating appropriate treatment. Statistical process control is widely used in hospital performance monitoring and improvement, and it is becoming more popular in public health surveillance.