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To what extent does quality assurance/quality control contribute to managing studies or trials? Some staff feel that QA/QC is a watchdog put in place by management to unearth the goings-on during the conduct of clinical trials or studies.
I think this is a very interesting discussion!!
When I came back into research (clinical this time) my first job was QA/QC Coordinator. I had spent quite a substantial amount of time in industry, implementing quality management systems.
My experience is, Quality Management can make the difference between success and failure, data integrity and dishonesty or filthy data, protection of rights, safety and wellbeing of trial participants or violating the fundamental principles of research ethics, and registering a drug/device and not. Quality has become a way of life in all business processes, institutions and even schools.
The difference mainly is the approach taken to introduce and implement quality management; it’s the strategy rather than the concept that fails its success and importance. Let me start by confirming what the team has already pointed out by looking at the critical terms:
Definition of quality -
a. Fit for use.
b. The characteristics of a product or service that bear on its ability to satisfy stated or implied needs.
c. For a research lab quality can be defined as accuracy, reliability, and timeliness of the reported test results.
Quality Management System (QMS) – refers to the organizational structure, responsibilities, procedures, processes and resources necessary to manage quality. It is a comprehensive coordinated program designed to meet quality objectives; to direct and control a laboratory with regard to quality; developed to support efficient and effective, quality and appropriate laboratory services (e.g. accurate and precise results, appropriate test selection, timely reporting, and correct interpretation of results, clinical usefulness, and appropriate recommendations for further tests.
Quality Management refers to coordinated activities to direct and control an organization with regard to quality. (ISO 9000).
In a quality management system, all aspects of the trial, including the organizational structure, processes, and procedures, need to be addressed to assure quality. QMS encompasses quality assurance (QA) and quality control (QC).
Quality Assurance - All those planned & systematic actions necessary to provide adequate confidence that data will satisfy protocol requirements for data quality. It is part of a QMS. It is a process-driven approach with specific steps to help define and attain goals. This process considers design, development, production, and service.
Quality Control - The operational techniques & activities that are used to fulfill requirements for data quality. Quality control emphasizes testing of products/services to uncover defects, and reporting to management who make the decision to allow or deny the release, whereas quality assurance attempts to improve and stabilize production/services, and associated processes, to avoid, or at least minimize, issues that led to the defects in the first place. The most popular tool used to determine quality assurance is the Shewhart Cycle, developed by Dr. W. Edwards Deming. This cycle for quality assurance consists of four steps: Plan, Do, Check, and Act. These steps are commonly abbreviated as PDCA.
From a GCP point of View, we can go on to demonstrate what needs to be done:
Section 2.13 - Systems with procedures that assure the quality of every aspect of the trial should be implemented.
Section 4.1.3 - The investigator should be aware of, and should comply with, GCP and the applicable regulatory requirements.
Section 4.2.4 - The investigator should ensure that all persons assisting with the trial are adequately informed about the protocol, the investigational product(s), and their trial-related duties and functions.
Section 4.9.1 - The investigator should ensure the accuracy, completeness, legibility, and timeliness of the data reported to the sponsor in the CRFs and in all required reports.
Section 5.1.1 - The sponsor is responsible for implementing and maintaining quality assurance and quality control systems with written SOPs to ensure that trials are conducted and data are generated, documented (recorded), and reported in compliance with the protocol, GCP, and the applicable regulatory requirement(s).
Section 5.1.3 - Quality control should be applied to each stage of data handling to ensure that all data are reliable and have been processed correctly.
Section 5.20.1- Noncompliance with the protocol, SOPs, GCP, and/or applicable regulatory requirement(s) by an investigator/institution, or by member(s) of the sponsor's staff should lead to prompt action by the sponsor to secure compliance.
So, there are GCP elements supporting implementation of QA/QC. The problem as, I have experienced and fought it, is:
• Not adequately conducting quality awareness training for personnel before implementation;
• Inadequate reference to GCP standards for trial personnel to understand the bases, background and need;
• Using QA/QC report outcomes to victimize personnel or using outcomes for performance management;
• Carrying out inspections rather than audits;
• Inadequate awareness by staff that it is not management who own the system, that they own the QA/QC system. That it is a way to improve the system, not place blame and make the non-conformances/non-compliances identified a subject of mockery over tea;
• QA/QC must be identified with teams that to the job, not just a management tool to discipline personnel. Otherwise it will be a source on unending conflict and Professor Deming will turn in his grave!!
• The individuals privileged to conduct quality control/audit lack adequate training and personality traits to do the job professionally. Remember when you conduct QC activities of a system owned by another team, you are “invading” someone’s territory, space, system, pride and; treat their system with respect. Do not personalize the process, and mind your language. Remember you have a common objective and, no one is perfect.
Otherwise we have to implement QA/QC, as demonstrated in the GCP elements above, and, Warren Buffett said “It's only when the tide goes out that you learn who's been swimming naked." If we don’t do QA/QC we will be quoting Buffet!!
Hi, I fully agree with Moses: quality assurance is there to make sure that the question is answered correctly and reliably, while protecting the rights of the subjects recruited into the trials. Sometimes, unfortunately, the ultimate objective is a bit "lost of sight", and quality assurance becomes just checking/producing papers, without trying to understand what papers mean.
A classical exemple is the checking of written informed consent. The signatures must be there, of course, as a proof that the consent interview has taken place; but signatures alone are not sufficient to ensure that the patient has fully understood what's going on. To check this, one should talk to the team, to understand how the process is organized, to verify if the dialogue with the person is not challenged by the power unbalance ... and one could also look at indirect indicators (e.g., a high drop-our rate could be an indicator that the informed consent was done too quickly).
The same could apply to source data verification: it should be the basis to identify problems in the transfer of data from the source to the case report form, and to discuss with the team about how to improve it according to the findings, with a final objective of producing reliable data, and correctly orient guidelines and medical practices. However, sometimes or often it becomes just a "checks' process", which aims at checking a minimal percentage of fields, and is not followed by productive dialogue with the team.
So, quality assurance should not be an objective in itself, but an important tool to reach the objectives (quality and reliability of data, protection of patients). And this should be achieved by a reasoned approach (taking into account the kind of study, diseases, population, context, risk-benefit ratio...) and by a full involvement of the study team, as suggested by Moses. Any other ideas?
What a good point to discuss. In my view quality is important but it is important to ensure that quality processes are practical, implementable and appropriate to the risk and situation of the trial. Running a trial is about answering a question and in my view the quality element is about making sure that the question is answered correctly and reliably - as simple as that. So the things we should put in place should be checks and validation to make sure all the induvidual bits of data that contribute to the final outcome of the study can be relied upon. Staff should not feel they are being 'checked up on' or that things are going on around them that they are suspicious of. In fact they should all be involved in quality management and they should feel part of the process. If the team feel like this then something has gone wrong between the management and the staff that have made them disjointed. Clinical trial staff should feel engaged and involved and that it is their trial too - not just the 'management'. So my approach would be to involved all the team in planning for quality within studies and ensure that the team feel that it is their study and that they appreciate the importance of reliable data and the validity of the answer that the trial had given. What do others think?