A comparison of methods for health policy evaluation with controlled pre-post designs

Health Serv Res. 2020 Apr;55(2):328-338. doi: 10.1111/1475-6773.13274. Epub 2020 Feb 12.

Abstract

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.

Keywords: difference-in-differences; interactive fixed effects; pay-for-performance; policy evaluation; synthetic control.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • England
  • Female
  • Health Policy*
  • Health Services / standards*
  • Health Services / statistics & numerical data*
  • Hip Fractures / therapy*
  • Humans
  • Male
  • Middle Aged
  • Models, Statistical
  • Practice Guidelines as Topic*
  • Quality of Health Care / standards*
  • Quality of Health Care / statistics & numerical data*