Search

Objective: To compare interactive fixed effects (IFE) and generalized synthetic control (GSC) methods to methods prevalent in health policy evaluation and re-evaluate the impact of the hip fracture best practice tariffs introduced for hospitals in England in 2010.Data Sources: Simulations and Hospital Episode Statistics.Study Design: Best practice tariffs aimed to incentivize providers to deliver care in line with guidelines. Under the scheme, 62 providers received an additional payment for each hip fracture admission, while 49 providers did not. We estimate the impact using difference-in-differences (DiD), synthetic control (SC), IFE, and GSC methods. We contrast the estimation methods' performance in a Monte Carlo simulation study.Principal Findings: Unlike DiD, SC, and IFE methods, the GSC method provided reliable estimates across a range of simulation scenarios and was preferred for this case study. The introduction of best practice tariffs led to a 5.9 (confidence interval: 2.0 to 9.9) percentage point increase in the proportion of patients having surgery within 48 hours and a statistically insignificant 0.6 (confidence interval: -1.4 to 0.4) percentage point reduction in 30-day mortality.Conclusions: The GSC approach is an attractive method for health policy evaluation. We cannot be confident that best practice tariffs were effective. [ABSTRACT FROM AUTHOR]

We study a pay-for-efficiency scheme that encourages hospitals to admit and discharge patients on the same calendar day when clinically appropriate. Since 2010, hospitals in the English NHS are incentivised by a higher price for patients treated as same-day discharge than for overnight stays, despite the former being less costly. We analyse administrative data for patients treated during 2006-2014 for 191 conditions for which same-day discharge is clinically appropriate - of which 32 are incentivised. Using difference-in-difference and synthetic control methods, we find that the policy had generally a positive impact with a statistically significant effect in 14 out of the 32 conditions. The median elasticity is 0.24 for planned and 0.01 for emergency conditions. Condition-specific design features explain some, but not all, of the differential responses. [ABSTRACT FROM AUTHOR]