Data analyses
comorbidity
REGRESSION
Descriptive statistics were computed for all variables collected at study beginning and for all resident outcomes for both study beginning and end of follow-up. The main comparison was the difference in medication regimens between the intervention and control groups at these points in time. Mean numbers of medications were modeled using repeated measures mixed Poisson regression accounting for intra-subject correlated residual errors and random NH effects. Models included group, time, and group by time interaction effects. Difference in differences tests were computed to compare the difference of results between study beginning (at 0 month) and the last date of assessment (at 6 months) between exposed and control groups. Analyses used an intention-to-treat approach [The proportion of patients exposed to each of the three OptimaMed appropriateness of use categories were analyzed independently using repeated measure mixed logistic regression. Again, the statistical model included group, time, and group by time interaction effects as well as intra-subject correlated residual errors and random NH effects. CMAI and PACSLAC scores were modelled using linear repeated measures mixed regression models with group, time, and group by time interaction effects as well as intra-subject correlation residual errors and random NH effects. There were no data missing for medications, as electronic pharmaceutical records contain complete data of residents’ medications, including daily dosages. As per current practice in these NHs, all regular prescribed medications are reliably given to the residents. Cases of forgotten or lost medications must be reported as incidents. There were also little missing clinical data, therefore no imputation method was deemed necessary for our analyses. As a sensitivity analysis, all models were also adjusted for age, Charlson comorbidity index and time since NH admission. A significance level alpha of 0.05 was used. Data analyses were performed using SAS® software (SAS Institute, version 9.4, Cary, NC).