Category: Practice & Regulation | Estimated reading time: 8 minutes
Is Detecting Problems As Best As Possible Enough?
A solid QC system — from pre-analytical testing to Sigma Metrics, from Levey-Jennings charts to Westgard rules — is an essential foundation. But there is one question that has not been fully answered:
Is detecting problems as best as possible enough?
The answer is: no — and this is not a criticism of QC. QC is a very powerful detection system. But detection, no matter how sophisticated, always works after something has already happened. It responds. It does not prevent.
This is why Quality Assurance (QA) exists — and why it is not just another name for QC.
Two Systems, Two Roles, One Goal
The relationship between QA and QC is not hierarchical — QA is not "higher" than QC. They are two layers that work at different times and in different dimensions within an integrated quality system.
QA works before measurement happens. It builds the conditions — ensuring SOPs are correct, laboratory personnel are trained, instruments are calibrated, and reagents are verified. If QA runs well, measurement conditions are always optimal before the first control material is measured in the morning.
QC works during and after measurement happens. It verifies — checking whether the conditions built by QA are still maintained by measuring control materials and evaluating the results against established limits.
One sentence sums this up sharply: "Poor QA cannot be saved by strict QC." If laboratory personnel are not trained, SOPs are not followed, or reagents are stored incorrectly — QC will just keep rejecting without providing a solution.
Why That Sentence Is So Important
That sentence is not rhetoric — it is an accurate description of the situation occurring in many laboratories, which causes great frustration for everyone involved.
Imagine this scenario: QC rejects almost every day. The instrument has been checked, recalibrated, and reagents have been replaced — but the problem keeps recurring. The supervisor is frustrated. Laboratory personnel are frustrated. Patient samples are held up. No one knows what is wrong.
In many cases like this, the root cause is not in QC — it is in QA. Perhaps the control material was not stored correctly because there was no clear storage SOP. Perhaps there is one technician whose method of reconstitution differs from others because there was never any standard training. Perhaps calibration was performed but not with the correct calibrator because there is no calibrator verification system.
QC detects all of this as a rejection — but QC cannot fix it, because the root cause is not in the measurement process itself.
Plebani (2017) asserts that investment in QA is far more cost-effective than tightening QC — because QA prevents problems from occurring, while QC only catches the consequences after they happen. Laboratories that continuously invest resources into solving QC problems without fixing the underlying QA system are in a never-ending cycle.
Six Components of QA — An Initial Overview
These six components are interconnected in one workflow:
SOP Design → Laboratory Personnel Training → Scheduled Calibration → Reagent Management → Internal Audit → CAPA (Corrective and Preventive Action)
The six are not an independent list. They are one interdependent system:
- Good SOPs are useless if laboratory personnel are not trained to follow them.
- Good training is useless if the instrument is not calibrated so that measurement results are unreliable.
- Scheduled calibration is useless if the reagents used have degraded.
- Good reagent management is useless if there is no audit to verify that all procedures are being executed.
- Audits without CAPA only produce findings that are never followed up on.
These six components must run together as one system — not cherry-picked based on ease or resource availability.
QA in the Context of Indonesian Laboratories
There is a reality that must be acknowledged: not all laboratories in Indonesia have the same resources to build a comprehensive QA system. Type A hospital laboratories in large cities have very different capacities than Community Health Centers (Puskesmas) in remote areas — and between the two is a very wide spectrum of various levels of resources and capacities.
But this is not an excuse for not building QA — it is a reason to prioritize the QA components that have the most impact based on the specific conditions of each laboratory.
For laboratories with very limited resources, even the two most fundamental components — followed SOPs and trained laboratory personnel — already provide a huge impact. Without these, all other technical investments will not provide optimal results. Research on the role of laboratory personnel in primary care in Indonesia (Marsudi, affiliated with Wiyata Husada Samarinda Institute of Health Technology and Sciences) emphasizes that laboratory quality improvement does not have to start from a sophisticated system — it can start from simple consistency: existing SOPs are followed, not ignored; training is conducted periodically, not just upon initial employment.
Questions to Ponder
QA elements may already be very familiar in daily practice for laboratory personnel who have worked for years. What may not be familiar is how to view those elements as one integrated system — not as separate activities that each have their own checklists.
Questions worth pondering:
"In my lab, out of the six QA components — which ones are running well? Which ones exist but are not consistent? And which ones do not exist at all?"
An honest answer to this question is the most practical roadmap for improving your laboratory quality system — far more actionable than any theory.
Closing
QA and QC are not competitors. They are partners — two layers of one protection system that, if both run well, provide much stronger quality assurance than either standing alone.
QA builds optimal conditions. QC verifies that those conditions are still maintained. And when QC detects a problem, QA is where we look to — and fix — the root cause.
Without solid QA, strict QC is just a system that constantly finds problems that are never fully resolved. With solid QA, QC becomes a verification system that rarely needs to sound an alarm — because problems are prevented before they have a chance to occur.