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Integration of Patient-Based Real-Time Quality Control with Conventional Internal Quality Control: Improved Error
Mudasir Bashir Dandroo1, Devanatha Desikan V1, Ramesh Ramasamy1
1Department of Biochemistry, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India.
Background:
Internal Quality control (IQC) is essential as it ensures analytical accuracy. However, IQC may have certain limitations, for example, it may miss intermittent or matrix-related errors. Patient-Based Real-Time Quality Control (PBRTQC) can overcome this limitation by continuously monitoring the patient data and also aids in early detection of shifts. Hence, integration of PBRTQC with IQC enhances the error detection and the cost efficiency in clinical laboratories.
Aim:
To study the effect of integrating Patient-Based Real-time Quality Control with Conventional Quality Control for improved detection of errors, cost benefit and risk-based cost benefits.
Methods:
Four parameters, creatinine, urea, Aspartate Transaminase (AST), and Thyroid Stimulating Hormone (TSH), were selected based on low sigma value and high monthly sample load. Historical patient data was collected from the laboratory information system. Data was divided into training and validation sets. Truncation limits were calculated using the interquartile range method. Simple Moving Average (SMA) was calculated for various block sizes. Control limits were set using the maximum/minimum of the moving average or percentiles. A bias simulation study was performed by introducing bias from -50% to +50% to plot bias detection curves and determine the optimum block size and ANPed. Optimized PBRTQC parameters were validated. The optimized algorithm was applied to daily patient data and integrated with IQC. Moving average alarm rate and percentage increase in error detection were calculated. Potential cost-benefit and risk-based benefits were determined.
Results:
optimum block size and (ANPed) at TEa was 50 for creatinine (161), 25 for urea (207), 50 for AST (22), and 25 for TSH (68). The MA alarm percentage remained below 1% for all analytes. Integration improved error detection by 28.57% for creatinine, 25% for urea, and 20% for TSH. Net cost benefit demonstrated total savings of 426.92 through QC reductions (264.56) and avoided reanalysis costs (162.36).
Conclusion:
PBRTQC integration with IQC significantly improves error detection for low sigma performance assays, is cost-effective and provides a strong risk-based cost-benefit advantage.
