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Statistical significance in the multivariable models was declared at P < 0.05.

The frequency of significance of each risk factor in multivariable models was also assessed to confirm their independence.

The mean variance inflation factor for all variables included in the multivariable models was 1.26, ranging from 1.03 to 1.68, ruling out high collinearity and indicating that the selected variables are independent from other predictors.

The strategy for building multivariable models was as follows.

The significance probability for the multivariable models was P < 0.05.

The selection of covariates included in multivariable models was informed by the literature.

Thus, the basis of more complex multivariable models is provided.

Multivariable models were developed to assess associations between referral hospital type and receipt and completeness of discharge communication.

Univariate and multivariable models were computed with the use of logistic regression models.

Variables with a p-value <0.05 in multivariable models were retained in the final model.

Multivariable models were adjusted for age, sex, history of alcohol abuse or depression, comorbidities, and medications.