Journal:Practical considerations for laboratories: Implementing a holistic quality management system

Full article title	Practical considerations for laboratories: Implementing a holistic quality management system
Journal	Frontiers in Bioengineering and Biotechnology
Author(s)	Pillai, S.; Calvery, J.; Fox, E.
Author affiliation(s)	Food and Drug Administration, Booz Allen Hamilton
Primary contact	Email: Segaran dot Pillai at fda dot hhs dot gov
Editors	Quemada, H.
Year published	2022
Volume and issue	10
Article #	1040103
DOI	10.3389/fbioe.2022.1040103
ISSN	2296-4185
Distribution license	Creative Commons Attribution 4.0 International
Website	https://www.frontiersin.org/articles/10.3389/fbioe.2022.1040103/full
Download	https://www.frontiersin.org/articles/10.3389/fbioe.2022.1040103/pdf (PDF)

Abstract

A quality management system (QMS) is an essential element for the effective operation of research, clinical, testing, or production/manufacturing laboratories. As technology continues to rapidly advance and new challenges arise, laboratories worldwide have responded with innovation and process changes to meet the continued demand. It is critical for laboratories to maintain a robust QMS that accommodates laboratory activities (e.g., basic and applied research; regulatory, clinical, or proficiency testing), records management, and a path for continuous improvement to ensure that results and data are reliable, accurate, timely, and reproducible. A robust, suitable QMS provides a framework to address gaps and risks throughout the laboratory's workflow that could potentially lead to a critical error, thus compromising the integrity and credibility of the institution. While there are many QMS frameworks (e.g., a model such as a consensus standard, guideline, or regulation) that may apply to laboratories, ensuring that the appropriate framework is adopted based on the type of work performed and that key implementation steps are taken is important for the long-term success of the QMS and for the advancement of science. Ultimately, a well-considered QMS ensures accurate results, efficient operations, and increased credibility, enabling protection of public health and safety. Herein, we explore QMS framework options for each identified laboratory category and discuss prerequisite considerations for implementation. An analysis of various frameworks’ principles and conformity requirements demonstrates the extent to which they address basic components of effective laboratory operations and guides optimal implementation to yield a holistic, sustainable framework that addresses the laboratory’s needs and the type of work being performed.

Keywords: quality, quality management system, laboratory, implementation, framework, total quality, reproducibility

Introduction

In order for laboratories to support the public health mission and better address emerging public health challenges, the need for a quality management system (QMS) that facilitates risk-based thinking and enhances assurance of data quality becomes more critical. With the worldwide shock of the coronavirus disease 2019 (COVID-19) outbreak, organizations have been forced to pivot and innovate to address new issues. The rapid response across industries towards COVID-19 and other crises illustrates business resilience and emphasizes the importance of quality management in the laboratory and its organizational culture. However, incidents stemming from gaps in quality management and affecting public health continue to occur. Laboratory errors have a reported frequency of 0.012%–0.6% of all test results, which in turn has huge impact on diagnosis, as 60 to 70% of all diagnoses are made based upon laboratory tests. [Agarwal, 2014] In addition, there is evidence of an observed data reproducibility crisis in the research community that would benefit from attention and improvement. A recent Nature survey of 1,576 researchers found that 52% of those surveyed agree that there is a crisis of reproducibility; the same survey found that over 70% have failed to reproduce another scientist’s data. [Baker, 2016]

A QMS has numerous benefits that contribute to managing risks in the laboratory, including errors, and mitigating reproducibility crisis concerns. One major benefit is enabling the laboratory to better identify, assess, and address risks faced in the laboratory at all levels of the organization. Poor data quality is one such risk. Some standards, such as the International Organization for Standardization's (ISO's) ISO 31000, are completely dedicated to risk management [International Organization for Standardization, 2018], while other more holistic quality management standards, guidelines, and regulations—such as ISO/IEC 17025—incorporate the concept of risk-based thinking throughout their respective frameworks. [International Organization for Standardization, 2017] In turn, risk management and other aspects of quality management can be built into all three phases of the workflow path (commonly referred to as the "total testing process") of a laboratory: pre-analytical, analytical, and post-analytical. [World Health Organization, 2011]

The pre-analytic phase of a laboratory’s workflow encompasses the activities that are completed prior to operational testing and research (e.g., sample collection and transport). These activities are performed to prepare and support the laboratory in its operations, research, and services. The analytic phase of a laboratory’s workflow encompasses the activities that are completed within the laboratory during operational testing and research. These activities are performed to directly execute the laboratory’s operations, research, and services (e.g., sample testing, experimental studies). Finally, the post-analytic phase of a laboratory’s workflow encompasses the activities that are completed after operational testing and research (e.g., reporting). These activities assure that processes are conducted in a manner that ensures compliance, accuracy, customer satisfaction, and continual improvement.

Each of these three phases must be addressed when implementing a QMS. While someone may suppose that the highest risk of error would occur in the analytic phase, there is now incontrovertible evidence that the majority of laboratory errors occur in the pre-analytical phase (61.9%–68.2%), which are followed by mistakes in the post-analytical phase (18.5%–23.1%) and analytical phase (13.3%–15%). [Mrazek et al., 2020] Within the path of workflow, laboratory processes and procedures can be organized into 12 management areas, known as quality system essentials (QSEs); the 12 QSEs are globally recognized principles that address all aspects of a QMS and cover the entire path of workflow of a laboratory. When all of the laboratory procedures and processes are organized into an understandable and workable structure, the opportunity to ensure that all are appropriately managed is increased. [World Health Organization, 2011] Moreover, as safety is a key QSE (QSE 2: Facilities and safety), laboratories such as those handling pathogens and other biosafety risks have the opportunity to evaluate the effectiveness of their biosafety procedures and implement improvements (e.g., take measures to reduce the risk of contamination). An integrated, robust QMS can help the laboratory cope with uncertainties that naturally occur in all laboratory environments.

In his 1993 book Preventing Chaos in a Crisis: Strategies for Prevention, Control, and Damage Limitation, Patrick Lagadec emphasizes that the response to an emergency cannot be developed unless the institution has prepared to adapt [Lagadec, 1993]:

...the ability to deal with a crisis situation is largely dependent on the structures that have been developed before chaos arrives. The event can in some ways be considered as an abrupt and brutal audit: at a moment’s notice, everything that was left unprepared becomes a complex problem, and every weakness comes rushing to the forefront.

Given the naturally complex operations of the modern laboratory, minimizing preventable problems and applying lessons learned should be a primary goal.

Notes

This presentation is faithful to the original, with only a few minor changes to spelling, grammar, and presentation. The PMCID and DOI were also added when they were missing from the original reference.