The use of quality of life data at the organization and systems level.

Dagnan et al. (2005) visited two US states to see how they use everyday quality-of-life data.

Workers collect short QOL surveys from adults with intellectual disability. States turn the answers into color dashboards.

The dashboards guide provider profiles, star ratings, and policy tweaks. No new experiment was run; the paper simply maps the routine.

The states already run living dashboards that update each quarter.

Provider scores are public, so families can pick services like they pick hotels.

Money and licenses ride on the scores, pushing agencies to fix weak spots fast.

Levin et al. (2014) give the blueprint. Their six-step QOL framework shows any state how to copy the dashboards D et al. describe.

Lam et al. (2011) add muscle. Their large survey proves group homes with good QOL plans beat other housing on five life domains.

Symons et al. (2005) wave a caution flag. They find objective living conditions and personal happiness scores do not match, so dashboards need both numbers and feelings.

Berástegui et al. (2021) echo the warning. Youth and parents rate the same life differently, so states should collect both voices before they label a provider "good" or "bad."

Together the papers say: build the dashboard, fund what works, but always check more than one view of quality.

You can lift the state model tomorrow. Add two QOL questions to your exit survey. Graph the answers each month. Share the graph with staff and families. Pick one low bar, set a 10% gain target, and rerun the survey in 90 days. You just started a mini-dashboard without new money or software.