Quasi-Experimental Methods

Preparation

Comparisons

Evidence quality

Highlighted claims

• A total of 1,304 discharged CLICS patients were matched to 5,216 controls. — Can social prescribing intervention reduce unplanned hospital usage in an ethnically diverse and deprived population: a quasi-experimental study using a dynamic staggered difference-in-differences approach
• The study used a quasi-experimental dynamic staggered difference-in-differences design on a propensity-matched cohort because a randomized controlled trial was unavailable and treatment timing varied. — Can social prescribing intervention reduce unplanned hospital usage in an ethnically diverse and deprived population: a quasi-experimental study using a dynamic staggered difference-in-differences approach
• The matched control group came from adults registered with participating GP practices before 1 September 2020 who did not receive CLICS. — Can social prescribing intervention reduce unplanned hospital usage in an ethnically diverse and deprived population: a quasi-experimental study using a dynamic staggered difference-in-differences approach
• Nearest-neighbour matching used a 1:4 CLICS-to-control ratio based on demographics, deprivation, and clinical risk factors. — Can social prescribing intervention reduce unplanned hospital usage in an ethnically diverse and deprived population: a quasi-experimental study using a dynamic staggered difference-in-differences approach
• The Callaway and Sant’Anna estimator was used to estimate treatment effects when treatment timing varied and to avoid biases from standard two-way fixed-effects methods. — Can social prescribing intervention reduce unplanned hospital usage in an ethnically diverse and deprived population: a quasi-experimental study using a dynamic staggered difference-in-differences approach