Use of a concurrent treatment design to analyze the effects of a peer review system in a residential setting.

Reed et al. (1988) tested a simple fix in a residential home. Night-shift staff wrote short notes about errors they saw on the day staff's data sheets. The next morning the day staff read the notes and fixed their sheets.

The study ran across 11 clients. The researchers tracked how complete and accurate the daily data sheets were before and after the notes started.

The overnight notes worked fast. Data quality jumped for every case manager once the peer feedback began.

The gains held as long as the notes kept coming. When the notes stopped, accuracy slipped back.

Gil et al. (2016) swapped the handwritten notes for colorful graphs plus goal setting. They saw the same sharp lift in data collection across a large facility.

Guercio et al. (2025) tried a different route: let staff pick a small prize and make it contingent on turning in 80% of sheets. That also pushed completion up fast.

Fuesy et al. (2025) added self-monitoring to performance feedback. They got strong gains too, but only while an observer was clearly in the room. The 1988 study did not check for this observer effect.

You have choices. A nightly sticky note, a weekly graph, or a tiny reinforcer can each lift data quality. Pick the one your team will actually use. If you go with peer notes, keep them short and steady. If staff prefer visuals, try Gil's graph package. Either way, plan to keep the feedback loop alive; when it stops, accuracy drifts down.