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Examination of the Synthetic Control Method for Evaluating Health Policies with Multiple Treated Units


Kreif, Noémi; Grieve, Richard; Hangartner, Dominik; Turner, Alex James; Nikolova, Sylviya (2016). Examination of the Synthetic Control Method for Evaluating Health Policies with Multiple Treated Units. Health Economics, 25(12):1514-1528.

Abstract

This paper examines the synthetic control method in contrast to commonly used difference-in-differences (DiD) estimation, in the context of a re-evaluation of a pay-for-performance (P4P) initiative, the Advancing Quality scheme. The synthetic control method aims to estimate treatment effects by constructing a weighted combination of control units, which represents what the treated group would have experienced in the absence of receiving the treatment. While DiD estimation assumes that the effects of unobserved confounders are constant over time, the synthetic control method allows for these effects to change over time, by re-weighting the control group so that it has similar pre-intervention characteristics to the treated group.
We extend the synthetic control approach to a setting of evaluation of a health policy where there are multiple treated units. We re-analyse a recent study evaluating the effects of a hospital P4P scheme on risk-adjusted hospital mortality. In contrast to the original DiD analysis, the synthetic control method reports that, for the incentivised conditions, the P4P scheme did not significantly reduce mortality and that there is a statistically significant increase in mortality for non-incentivised conditions. This result was robust to alternative specifications of the synthetic control method.

Abstract

This paper examines the synthetic control method in contrast to commonly used difference-in-differences (DiD) estimation, in the context of a re-evaluation of a pay-for-performance (P4P) initiative, the Advancing Quality scheme. The synthetic control method aims to estimate treatment effects by constructing a weighted combination of control units, which represents what the treated group would have experienced in the absence of receiving the treatment. While DiD estimation assumes that the effects of unobserved confounders are constant over time, the synthetic control method allows for these effects to change over time, by re-weighting the control group so that it has similar pre-intervention characteristics to the treated group.
We extend the synthetic control approach to a setting of evaluation of a health policy where there are multiple treated units. We re-analyse a recent study evaluating the effects of a hospital P4P scheme on risk-adjusted hospital mortality. In contrast to the original DiD analysis, the synthetic control method reports that, for the incentivised conditions, the P4P scheme did not significantly reduce mortality and that there is a statistically significant increase in mortality for non-incentivised conditions. This result was robust to alternative specifications of the synthetic control method.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Political Science
Dewey Decimal Classification:320 Political science
Uncontrolled Keywords:synthetic control method, difference-in-differences, policy evaluation, pay-for-performance
Language:English
Date:December 2016
Deposited On:15 Feb 2017 12:10
Last Modified:16 Feb 2017 18:45
Publisher:Wiley-Blackwell Publishing, Inc.
ISSN:1057-9230
Free access at:Official URL. An embargo period may apply.
Publisher DOI:https://doi.org/10.1002/hec.3258
Official URL:http://onlinelibrary.wiley.com/doi/10.1002/hec.3258/pdf
Related URLs:http://onlinelibrary.wiley.com/doi/10.1002/hec.3258/full

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