Composite example: Stopping medication selection errors in a small clinic

This illustrative case combines common patterns from outpatient clinics and small pharmacies. It shows how a short audit led to prioritized, testable changes.

What triggered the audit

Staff reported two near-misses where staff nearly prepared the wrong medication because two similar bottles were stored next to one another. No harm occurred, but staff were concerned.

What the audit found

• Observation: Two medication bottles with similar labels were stored side-by-side in the same drawer.
• Contributing factors: Low lighting in the drawer, similar packaging, and no secondary verification step because the technician assumed the drawer was organized.
• Data: Near-miss log showed this pattern twice in the past month during a busy morning shift.

Controls tested

1. Temporary visual separation: added colored tape to separate commonly confused bottles (2-week experiment).
2. Relocated high-risk medicines to a separate, clearly labeled bin within the drawer (administrative + visual control).
3. Introduced a brief two-step verification for the tech and supervisor: read-and-confirm the drug name aloud for morning rush (behavioral check during test).

Verification and learning

Verification: the clinic tracked near-miss reports and ran three direct observations over two weeks. Results: near-miss reports for that error mode dropped to zero during the test window. The team followed with a short huddle to discuss sustainability and decided to keep the separate bin and colored tape while exploring a design change to procurement (standardize bottle suppliers) as a longer-term fix.

Lessons

• Small, cheap experiments can reduce risk quickly while teams develop stronger, longer-term controls.
• Combining visual and administrative controls works better than either alone for quick wins.
• Capturing the observation and linking to a control owner and verification made it much more likely the change would stick.

Use this example as a template: capture the observation, propose a layered control approach, run a short experiment, verify with simple checks, and then plan a longer-term redesign if needed.