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Research · 02 of 05

Pended orders and patient reminders lifted annual lung screening from 47% to 76%

Use system-level recall with pre-pended orders for repeat screening; information leaflets alone do not get people back.

Design
Pragmatic 2 × 2 factorial randomised trial
Population
1,837 adults due for annual repeat low-dose CT after a normal first scan
Primary outcome
Repeat screening CT completed 9–15 months after index scan
Effect
Stepped reminders 75.5% vs 47.4% (RR 1.59, 1.47–1.72); education 59.2% vs 63.3% (RR 0.93)

This pragmatic 2 × 2 factorial trial at Kaiser Permanente Washington enrolled 1,837 people with a normal first screening low-dose CT who were due for their annual repeat. Mean age was 66; nearly half still smoked.

The stepped-reminder arm, in which a coordinator pended the scan order for the primary care physician and contacted the patient to book, raised on-time screening from 47.4% to 75.5% (RR 1.59, 95% CI 1.47 to 1.72). The gain was larger among current smokers (32 percentage points) than former smokers (24 points). Print and video education alone slightly lowered adherence (59.2% vs 63.3%, RR 0.93).

The finding is simple: making the order easy for the physician and the booking easy for the patient worked; telling patients more did not. It comes from one integrated US health system with an electronic registry, and lung screening programmes in India are not yet widespread, but the principle applies to any recall-based programme.

  • Build recall into the system rather than relying on patients to remember annual screening.
  • Pending the order for the physician removed a step that often fails.
  • Current smokers gained most from reminders and were least likely to return unaided.
  • Education materials alone did not improve adherence and may have slightly reduced it.

Why it matters

It shows that adherence failures are mostly logistical, not a lack of patient knowledge.

The statistics, in plain English

A relative risk of 1.59 means screening was about 60% more common with reminders; in absolute terms, about 28 more people per 100 came back on time. The factorial design tests each intervention against not receiving it, across the whole trial.

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