Medical laboratories are often described as some of the most digitalized environments in healthcare. LIS, automation, analyzers and integrations support large parts of the daily work. On paper, much of the process is already digital. Still, manual work tends to return.
Not because laboratories resist technology, but because systems and daily practice do not always move forward together.
When systems meet everyday pressure
Laboratory systems are usually implemented through well-structured projects. Configuration, validation and go-live are handled carefully. Once the system is stable, attention shifts back to operations. Daily work continues to evolve.
As time passes, work volumes increase, staffing changes and expectations from both clinicians and reporting bodies continue to evolve. Small adjustments are made to keep things running. Often these adjustments happen around the system, not inside it:
- A spreadsheet here.
- A local list there.
- A manual check added “just to be safe”.
None of this is planned. It is simply what works in the moment.
Manual work is rarely the real problem
When manual routines appear, it is easy to interpret it as poor use of technology. In practice, it is usually a sign that the system has not been revisited in a long time. Laboratory staff build workarounds to protect quality and continuity. These are not careless shortcuts. They are usually created by experienced people who know where things can fail.
The issue is not that manual steps exist. It is how easily they become part of everyday work.
What parallel routines do over time
Manual routines introduced quietly tend to stay that way. Over time they add complexity. Knowledge becomes tied to individuals rather than shared workflows. Controls move out of the system and into documents and memory.
The risk is not always obvious. It often shows up indirectly as delays, reduced flexibility or vulnerability when key people are absent. And manual work consumes time, time laboratories rarely have to spare.
Systems that are introduced once
Many laboratory systems are implemented once, but rarely reintroduced. Training focuses on go-live. Years later, the system may contain functionality that could replace several manual steps, but awareness has faded. People work the way they learned to work.
This is not about lack of competence. It is about lack of continuity. Digital systems need more than technical maintenance. They need periodic reflection on how they are actually used and why certain tasks have moved outside the system.
Keeping digital work digital
Highly digital laboratories are not defined by advanced systems alone. They work well when digital workflows are maintained, adjusted and aligned with real practice over time.
Preventing the quiet return of manual work is not about enforcing stricter rules. It is about keeping systems relevant as work evolves. Because when manual work returns unnoticed, it is rarely because technology failed. It is because the system around it stopped being actively shaped.
