Controlled interrupted time-series analyses
REGRESSION
An additional analysis was performed for the same eight health outcomes using a controlled interrupted time-series (CITS) approach to understand temporal changes related to the intervention as distinct from the time-agnostic intention-to-treat approach. This was implemented within a generalised linear-mixed modelling framework by applying negative binomial regression to weekly level data spanning pre- and post-intervention periods for both the intervention and control groups. Data was also disaggregated by practice, allowing random intercepts at practice level. Variables included in the model were as follows: consecutively numbered weeks to capture a log-linear trend, intervention-control indicator, pre-post-intervention indicator and all two- and three-way interactions between these. Additional covariates included calendar month to capture seasonal effects and practice-level indicators such as area-level deprivation, median patient age and sex distribution represented as the proportion of females.