Sigma Metrics Assessment As Quality Improvement Methodology In A Clinical Chemistry Laboratory
Garg, M.; Sharma, N.; Das, S.
Show abstract
BackgroundThe concept of sigma metrics & lean six sigma is well known in the field of healthcare. However not many labs utilize the six sigma metrics for maintenance of high quality laboratory performance. A minimum value of 3 {sigma} is desired in any clinical laboratory & values of {sigma}[≥] 6 are regarded as gold standard for obtaining high quality lab reports. Aims &ObjectivesTo calculate bias, cv & sigma metrics from the IQC & EQC data in order to ascertain extent of quality management in our lab. Materials &MethodsAn extensive study of sample processing and quality practices was carried out in the Central Laboratory of Department of Biochemistry; PGIMER &Dr. RML Hospital, New Delhi; from Feb 2020 to July 2020. The IQC used(both level I & level II) were from Biorad Laboratories India (lyphochek assayed chemistry control) & the EQC used was from Randox Laboratories, UK. All the controls were run on Beckman Coulter clinical chemistry analyser AU 680. Total 14 clinical parameters were analysed & subsequently; Mean, S.D., CV, bias & {sigma} were calculated through their respective formulas. ResultsSigma level was more than 6 for both levels of IQC was observed for Amylase. It indicates world class performance. Total bilirubin, AST, Triglyceride & HDL depicted {sigma} values between 3.1 - 6 for both L1 & L2. Iron showed {sigma} value of 5.5 in L1 whereas it was 3.78 in L2. ConclusionSigma metrics in clinical laboratory is an essential technique to ascertain poor assay performance, along with assessment of the efficiency of existing laboratory process.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Enhancing pigment production by a chromogenic bacterium (Exiguobacterium aurantiacum) using tomato waste extract: A Statistical approach 94%
- Development and Evaluation of Two Rapid Indigenous IgG-ELISA immobilized with ACE-2 Binding Peptides for Detection Neutralizing Antibodies Against SARS-CoV-2 94%
- Evaluating diagnostic accuracies of Panbio ™ COVID-19 rapid antigen test and RT-PCR for the detection of SARS-CoV-2 in Addis Ababa, Ethiopia using Bayesian Latent-Class Models (BLCM) 94%
Similar papers in this journal
- Clinical and laboratory characteristics in outpatient diagnosis of COVID-19 in healthcare professionals in Rio de Janeiro, Brazil 91%
- Development of a qualitative real-time RT-PCR assay for the detection of SARS-CoV-2: A guide and case study in setting up an emergency-use, laboratory-developed molecular assay 90%
- Molecular point-of-care testing for influenza A/B and respiratory syncytial virus: comparison of workflow parameters for the ID Now and cobas Liat systems 88%
Similar papers in this journal
- A simple, cost-effective and extraction-free molecular diagnostic test for sickle cell disease in noninvasive buccal swab specimen for a limited-resource setting 92%
- Passive Microwave Radiometry (MWR) for diagnostics of COVID-19 lung complications in Kyrgyzstan 92%
- Near-infrared Spectroscopy evaluations for rapid differentiation of carbapenem resistant Enterobacteriaceae from susceptible strains 91%
Similar papers in this journal
- An Evaluation of Liver Function Tests in SARS-CoV-2 infection in the backdrop of chronic kidney disease 94%
- Experience from a COVID-19 screening centre of a tertiary care institution: A retrospective hospital-based study 92%
- Prevalence and effect of bacterial co-infections on clinical outcomes in hospitalized COVID-19 patients at a tertiary care centre of India 92%
Similar papers in this journal
- A Novel Maxillofacial Technology for Drug Administration-A Randomized Controlled Trial Using Metronidazole. 93%
- Prevalence of SARS-CoV-2 infection among COVID-19 RT-PCR laboratory workers in Bangladesh 93%
- Comparison of Efficacy of Dexamethasone and Methylprednisolone in Improving the Partial Pressure of Arterial Oxygen and Fraction of Inspired Oxygen Ratio among COVID-19 Patients 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.