Estimation of Population Average Treatment Effects in the Trial: Application of a Propensity Score‐Based Stratification Approach

Objective/Study Question

To estimate and compare sample average treatment effects () and population average treatment effects () of a resident duty hour policy change on patient and resident outcomes using data from the Flexibility in Duty Hour Requirements for Surgical Trainees Trial (“ Trial”).

Data Sources/Study Setting

Secondary data from the National Surgical Quality Improvement Program and the Trial (2014–2015).

Study Design

The Trial was a cluster‐randomized pragmatic noninferiority trial designed to evaluate the effects of a resident work hour policy change to permit greater flexibility in scheduling on patient and resident outcomes. We estimated hierarchical logistic regression models to estimate the of a policy change on outcomes within an intent‐to‐treat framework. Propensity score‐based poststratification was used to estimate .

Data Collection/Extraction Methods

This study was a secondary analysis of previously collected data.

Principal Findings

Although estimates suggested noninferiority of outcomes under flexible duty hour policy versus standard policy, the noninferiority of a policy change was based on estimates due to imprecision.

Conclusions

Propensity score‐based poststratification can be valuable tools to address trial generalizability but may yield imprecise estimates of when sparse strata exist.