Skytron Blog

When equipment in Sterile Processing fails, the impact is immediate and rarely contained. Throughput slows, backlogs form, and downstream teams absorb the consequences long before the issue is fully resolved.

What changes over time is not the equipment itself, but the systems surrounding it. As case volumes rise, instrument complexity increases, and documentation requirements expand, those supporting systems can quietly fall out of step with the work being asked of them. When performance issues eventually surface, the root cause is rarely obvious and is often misattributed.
 

Maintenance holds until documentation becomes the weak link

In most Sterile Processing departments, daily and weekly maintenance tasks continue long after equipment installation. Washers are verified using soil or cleaning indicators. Pre-vacuum steam sterilizers undergo daily air removal testing. Chambers, filters, spray arms, and strainers are cleaned and inspected per IFU requirements.

Where breakdowns tend to occur is not in execution, but in documentation. Many of these routine actions are warranty-critical, yet they are often tracked through paper logs, informal checklists, or technician memory. The work happens, but the record does not consistently follow.

Healthcare Purchasing News has reported that incomplete or inconsistent preventive maintenance documentation is a common contributor to avoidable downtime, warranty disputes, and delayed service response in sterile processing environments where manual tracking remains prevalent.¹

The consequences of this gap are rarely immediate. They surface later, during regulatory visits, warranty reviews, or service escalations, when leaders are asked to demonstrate compliance that can no longer be reconstructed with confidence. At that point, maintenance becomes reactive by necessity rather than by choice.

Workflow variability distorts how performance is perceived

As departments absorb higher volumes and additional reprocessing steps, workflow consistency becomes harder to maintain. Documentation that once occurred in real time begins to lag. Batch scanning replaces continuous tracking. Sets are recorded well after they move through the department.

These behaviors corrupt timestamp data and distort throughput metrics. Backlogs form that appear to reflect equipment limitations, when the underlying issue is often timing, staffing distribution, or workload imbalance.

In practice, sterile processing bottlenecks are frequently attributed to equipment constraints when the true limitation is rooted in workflow timing or staffing alignment. When this distinction is unclear, capital equipment becomes the visible point of friction, even when it is not the source of the constraint.

The risk is not a failure to recognize that something is wrong. It is the difficulty of identifying where the problem actually resides when data and workflow signals are misaligned.
 

When operational deficits masquerade as equipment failure

Equipment performance and operational performance are tightly intertwined. When throughput slows or inventory backs up, the distinction between mechanical failure and usage failure can blur quickly.

Operational deficits such as uneven shift coverage, congested decontamination workflows, or unbalanced workload distribution often surface as equipment concerns. Service calls are placed. Capacity is questioned. Capital solutions are explored.

Without a reliable way to separate equipment reliability from process reliability, departments risk misdirecting resources.

Washers, Sterilizers, etc., are serviced for operational issues. Capital is questioned for problems rooted in workflow. And underlying constraints remain unresolved.

This misattribution is not a leadership failure. It is the predictable outcome of complex systems operating without clear separation between mechanical performance and operational demand.
 

Data exists, but credibility erodes over time

Over time, manual documentation creates blind spots in where instruments actually are and what has already happened to them. A tray may appear available in the system while it is still cooling. A loaner set may be scanned as received but not fully processed. A specialty instrument may be recorded as complete without clarity on whether it is in a room, in the core, or waiting for inspection. Failed loads may be reprocessed correctly, but recall documentation becomes fragmented across shifts.

The result is data that exists but cannot be fully trusted. Leaders lose confidence in utilization reports, struggle to justify staffing adjustments, and find it difficult to defend capital requests because the underlying information does not consistently reflect operational reality.

The American Society for Health Care Engineering has emphasized that unreliable asset and utilization data undermines lifecycle planning and decision-making, particularly in environments where tracking depends heavily on manual inputs.² When data credibility erodes, improvement efforts stall, not due to lack of intent, but due to lack of defensible baselines.
 

Education declines after go-live

Education is typically strongest at installation and weakest over time.

Initial in-service training reaches the current staff, but as turnover occurs, institutional knowledge dissipates. New technicians inherit systems without context. Tracking and monitoring tools are often perceived as punitive rather than purposeful because the operational reasons behind the data are no longer reinforced.

AORN has consistently emphasized that sustained competency in Sterile Processing depends on continuous education and reinforcement rather than one-time training events.³ When education becomes informal and leader-dependent, variation increases and system use declines.

Over time, leaders absorb the burden of ongoing education while balancing production demands. Knowledge becomes uneven. Practices diverge. The system remains in place, but understanding fades.
 

Performance erosion is rarely isolated

Maintenance, workflow, data, and education do not fail independently. They compound.

Documentation gaps force service escalation to become reactive. Workflow variability distorts performance signals. Data integrity erodes. Education drift accelerates inconsistency. Even well-chosen equipment struggles when the surrounding systems fall out of alignment.

These breakdowns rarely announce themselves. They accumulate quietly until performance issues surface under pressure, long after the opportunity to intervene early has passed.

Skytron approaches Sterile Processing as a long-term operational environment, not a moment of installation. Through design and planning services, Skytron works alongside clinical and facilities teams with respect for the realities leaders manage after go-live. That perspective is also shaping how Skytron extends support beyond equipment alone. In the weeks ahead, Skytron will be sharing more about new partnerships. The goal is not to add complexity, but to better support the systems that equipment depends on long after installation.
 

 
References
1. Healthcare Purchasing News. “Preventive maintenance documentation challenges in sterile processing”
2. American Society for Health Care Engineering (ASHE). “Asset management and data integrity in healthcare facilities”
3. Association of periOperative Registered Nurses (AORN). “Guideline for sterile processing”