RT Journal Article
SR Electronic
T1 Compared with what? Estimating the effects of injury prevention policies using the synthetic control method
JF Injury Prevention
JO Inj Prev
FD BMJ Publishing Group Ltd
SP injuryprev-2017-042360
DO 10.1136/injuryprev-2017-042360
A1 Carl Bonander
YR 2017
UL http://injuryprevention.bmj.com/content/early/2017/11/10/injuryprev-2017-042360.abstract
AB Introduction This paper discusses the application of the synthetic control method to injury-related interventions using aggregate data from public information systems. The method selects and determines the optimal control unit in the data by minimising the difference between the pre-intervention outcomes in one treated unit (eg, a state) and a weighted combination of potential control units.Method I demonstrate the synthetic control method by an application to Florida’s post-2010 policy and law enforcement initiatives aimed at bringing down opioid overdose deaths. Using opioid-related mortality data for a panel of 46 states observed from 1999 to 2015, the analysis suggests that a weighted combination of Maine (46.1%), Pennsylvania (34.4%), Nevada (5.4%), Washington (5.3%), West Virginia (4.3%) and Oklahoma (3.4%) best predicts the preintervention trajectory of opioid-related deaths in Florida between 1999 and 2009. Model specification and placebo tests, as well as an iterative leave-k-out sensitivity analysis are used as falsification tests.Results The results indicate that the policies have decreased the incidence of opioid-related deaths in Florida by roughly 40% (or −6.19 deaths per 100.000 person-years) by 2015 compared with the evolution projected by the synthetic control unit. Sensitivity analyses yield an average estimate of −4.55 deaths per 100.000 person-years (2.5th percentile: −1.24, 97.5th percentile: −7.92). The estimated cumulative effect in terms of deaths prevented in the postperiod is 3705 (2.5th percentile: 1302, 97.5th percentile: 6412).Discussion Recommendations for practice, future research and potential pitfalls, especially concerning low-count data, are discussed. Replication codes for Stata are provided.