ArticleCureus2025
Streamlining Molecular and Serology Laboratory Operations: A Lean Six Sigma Approach.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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10 authors.
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Abstract
Background The Lean Six Sigma tools are widely used in various industries, including healthcare, to reduce waste and improve quality. This study investigated how Lean Six Sigma might be used to improve quality control procedures in virology and molecular laboratories. The study intended to minimize errors, expedite laboratory procedures, and shorten turnaround times (TATs). Methods A prospective cross-sectional study was conducted at a tertiary care hospital located in India to assess the quality indicators for the processes in a virology laboratory and identify the wastes in those processes. By using the Define, Measure, Analyze, Improve, Control (DMAIC) strategy, the research quantified quality indicators like defects per million opportunities (DPMO) and six-sigma metrics. Subsequently, corrective measures were implemented to reduce the errors. A paired t-test was done by taking the sigma values of pre- and post-intervention phases. Results In the pre-analytical phase, a total of 6925 test requisition forms and 12,236 samples were considered, and the sigma value showed drastic improvement after the implementation of the DMAIC strategy. Similarly, in the analytical phase, out of a total of 61 samples, random errors showed an increase in sigma value from 1.71 to 2.47, and reagent contamination showed an increase in sigma value from 1.29 to 2.17. The type of error non-conformity with quality controls showed an increase in sigma value from 1.93 to 2.65, and systemic error showed an increase in sigma value from 2.88 to 3.7. A total of 126 samples were taken in the post-analytical phase, where transcription errors and TAT sigma value drastically increased (transcription error improved from a sigma value of 3.03 to a sigma value of 3.65, and TAT improved from a sigma value of 3.29 to a sigma value of 3.48) by DMAIC strategy. The two-tailed p-value was found to be 0.0269 (p < 0.05), which was statistically significant. Conclusions The study highlighted that error reduction directly correlated with a decrease in diagnostic mistakes. Misdiagnoses often lead to alternate treatment methods, causing delays in patient treatment management. Further, the errors reduce the efficiency of the hospital in terms of time and cost. Reducing unnecessary delays in the test process allows clinicians to focus on patient care. The statistical significance of the study showed the effectiveness of the interventions implemented in the study to practical outcomes like reduced misdiagnoses, cost savings, operational improvements, and strengthening the clinical relevance of the study. Further research is needed on these quality improvement steps for the adoptive process flow for the operation process of the laboratories in healthcare setups.
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