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Approaches to quality management and accreditation in a genetic testing laboratory.

ABSTRACT: Medical laboratories, and specifically genetic testing laboratories, provide vital medical services to different clients: clinicians requesting a test, patients from whom the sample was collected, public health and medical-legal instances, referral laboratories and authoritative bodies. All expect results that are accurate and obtained in an efficient and effective manner, within a suitable time frame and at acceptable cost. There are different ways of achieving the end results, but compliance with International Organization for Standardization (ISO) 15189, the international standard for the accreditation of medical laboratories, is becoming progressively accepted as the optimal approach to assuring quality in medical testing. We present recommendations and strategies designed to aid genetic testing laboratories with the implementation of a quality management system, including key aspects such as document control, external quality assessment, internal quality control, internal audit, management review, validation, as well as managing the human side of change. The focus is on pragmatic approaches to attain the levels of quality management and quality assurance required for accreditation according to ISO 15189, within the context of genetic testing. Attention is also given to implementing efficient and effective quality improvement.

SUBMITTER: Berwouts S

PROVIDER: S-EPMC3327516 | biostudies-other | 2010 Sep

REPOSITORIES: biostudies-other

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Project description:Objective: To distinguish COVID-19 patients and non-COVID-19 viral pneumonia patients and classify COVID-19 patients into low-risk and high-risk at admission by laboratory indicators. Materials and methods: In this retrospective cohort, a total of 3,563 COVID-19 patients and 118 non-COVID-19 pneumonia patients were included. There are two cohorts of COVID-19 patients, including 548 patients in the training dataset, and 3,015 patients in the testing dataset. Laboratory indicators were measured during hospitalization for all patients. Based on laboratory indicators, we used the support vector machine and joint random sampling to risk stratification for COVID-19 patients at admission. Based on laboratory indicators detected within the 1st week after admission, we used logistic regression and joint random sampling to develop the survival mode. The laboratory indicators of COVID-10 and non-COVID-19 were also compared. Results: We first identified the significant laboratory indicators related to the severity of COVID-19 in the training dataset. Neutrophils percentage, lymphocytes percentage, creatinine, and blood urea nitrogen with AUC >0.7 were included in the model. These indicators were further used to build a support vector machine model to classify patients into low-risk and high-risk at admission in the testing dataset. Results showed that this model could stratify the patients in the testing dataset effectively (AUC = 0.89). Our model still has good performance at different times (Mean AUC: 0.71, 0.72, 0.72, respectively for 3, 5, and 7 days after admission). Moreover, laboratory indicators detected within the 1st week after admission were able to estimate the probability of death (AUC = 0.95). We identified six indicators with permutation p < 0.05, including eosinophil percentage (p = 0.007), white blood cell count (p = 0.045), albumin (p = 0.041), aspartate transaminase (p = 0.043), lactate dehydrogenase (p = 0.002), and hemoglobin (p = 0.031). We could diagnose COVID-19 and differentiate it from other kinds of viral pneumonia based on these laboratory indicators. Conclusions: Our risk-stratification model based on laboratory indicators could help to diagnose, monitor, and predict severity at an early stage of COVID-19. In addition, laboratory findings could be used to distinguish COVID-19 and non-COVID-19.

Project description:BACKGROUND:High quality diagnostic services are crucial for tuberculosis (TB) diagnosis, treatment and control. A strong laboratory quality management system (QMS) is critical to ensuring the quality of testing and results. Recent initiatives to improve TB laboratory quality have focused on low and middle-income countries, but similar issues also apply to high-income countries. METHODS AND FINDINGS:Using a multipronged approach reviews of facilities, equipment, processes (purchasing, pre-analytic, analytic and post-analytic), staff, health and safety, documentation, information management and organization based on the ISO 15189 and the twelve quality system essentials were conducted between October 2015 and January 2016 at the National TB Reference Laboratory in Germany. Outcome assessment included proportion of smear positive slides, proportion of contaminated liquid cultures and DNA contamination rates before and after implementation of QMS. The odds ratio for these outcomes was calculated using a before/after comparison. Reviews highlighted deficiencies across all twelve quality system essentials and were addressed in order of priority and urgency. Actions aimed at improving analytical quality, health and safety and information management were prioritised for initial implementation in parallel with each other. The odds ratio for a sample to be tested as microscopically positive increased by 2.08 (95%CI 1.41-3.06) comparing the time before with the time after implementation of quality managed fluorescence microscopy. Liquid culture contamination rates decreased from 23.6- 7.6% in April-July 2016 to <10% in November 2017-March 2018. The proportion of negative controls showing evidence of DNA contamination decreased from 38.2% in 2013 to 8.1% in 2017, the corresponding odds ratio was 0.14 (95%CI 0.07-0.29). CONCLUSION:This study showed marked improvement on quality indicators after implementation of a QMS in a National TB Reference Laboratory. The challenges and lessons learned in this study are valuable not just for high-income settings, but are equally generalizable to other laboratories.

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Approaches to quality management and accreditation in a genetic testing laboratory.

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