Completion rates don’t make patients safer.

Your root-cause analysis keeps returning to the same issues – but competency measured by completion can’t show whether bedside behavior changed. Two health systems measured it.

60%

Fewer medication errors · Hoag

89%

Sepsis bundle compliance · Carle

Pre/Post

Measured against each baseline

See the evidence

Outcomes measured against baseline

The pattern

The same issues, on
every root-cause report.

Across systems, root-cause analysis keeps identifying the same competency gaps behind safety events. The education meant to close them is measured by completion – attendance, modules finished – not by whether the decision at the bedside actually changed.

Two systems treated training as a quality-improvement intervention instead: targeted at a named problem, measured against baseline. Hoag cut medication errors 60%. Carle took sepsis bundle compliance from 49% to 89%.

The reframe

This is quality-improvement evidence – not education evidence.

You don’t need another education platform. You need proof that training changed behavior in the competencies your incident data keeps naming. That’s a different standard – pre/post measurement, against your own baseline, held to research rigor.

What changes

Simulation built for the problem, measured like a study.

OMS builds scenarios around the specific clinical decisions where harm happens, then captures how clinicians reason and where they make errors. Run as a QI project – targeted endpoint, pre/post design – it produces the behavior-change evidence leaders can actually trust.

60%

Hoag Hospital – medication errors

Hoag worked with OMS to build scenarios around the medication-error patterns its own data flagged. Errors leading to harm fell 60% and this was repeated in year 2.

See the full Hoag case →

Common questions

Answered, plainly.

At Hoag, custom OMS scenarios targeting the hospital’s own medication-error patterns drove a 60% reduction in errors.

By designing it as a quality-improvement study in collaboration with OMS – a named clinical endpoint, measured pre and post against the organization’s own baseline – rather than tracking course completion.

Completion data shows who finished training. Outcomes data shows whether the clinical behavior or event rate changed. Quality leaders need the second; most education only produces the first.

More than one in five newly hired nurses leave within their first year, at about $60,090 each to replace (NSI, 2026) – plus the preceptor time lost with them. Readiness is a retention and safety issue, not only an education one.

At Carle Health, OMS sepsis scenarios were associated with bundle compliance rising from 49% to 89%.

Walkthrough

See how it holds up as QI evidence.

We’ll walk through the measurement design and the scenario-to-risk mapping with you – how it works as a QI project against your own baseline, targeting the competencies your incident data keeps naming.