Statistical Analysis Plan In the analysis stage, the effect of the agreement between the normative services and the actual services used by individual patient on the adverse outcomes of that patient will be inferred at each population segment. Separate models for each of the four adverse outcome variables will be considered. As A&E visits and readmission are count variables which can take values 0, 1, 2 …, there may be more patients with `0' value for these two outcome variables. To address this zero-inflated outcome, zero-inflated Poisson regression models will be considered, separately for each of these two outcomes, to see the effect of the agreement between the normative services and the actual services used by individual patient on the adverse outcomes of that patient. The other two adverse outcome variables nursing home placement and death are binary variables 1: yes and 0: no. Two logistic regression models will be used to find out the effect of above mentioned `agreement' on the two outcome variables separately. In all four regression models, the variable selection procedure will be considered to choose appropriate covariates from the baseline and follow-up data. In each of the four cases, p-values related to the coefficient of the `agreement' corresponding to the two sided test with null hypothesis that value of the coefficient is zero will be reported, together with confidence intervals of the coefficients. A statistically significant negative value of a coefficient will indicate lower `agreement' may increase the adverse outcomes.