Previous Versions

9th of April, 2008

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Primary Outcomes

1. Number of serious medication errors (see PILL-CVD definitions) per patient during the first 30 days after hospital discharge.
2. Number of preventable/ameliorable serious adverse drug events (ADEs) (see PILL-CVD definitions) per patient during the first 30 days after hospital discharge.
3. Number of potential serious ADEs (see PILL-CVD definitions) per patient during the first 30 days after hospital discharge.

Effect Modification (Interaction) Variables

• Level of health literacy
• Investigation site

Possible Confounders

• Number of Prescribed Medications
• Age
• Social support
• Educational attainment
• hospital service
• insurance
• income
• Cognitive function
• Primary language ( don't you think that cognitive function would account for primary language differences)
• Gender (including this variable won't do any harm, but doesn't have to be included if there is no evidence in the previous literature that gender is important and you see no reason why it should)
• Race (if you think that race is associated with income)

Not Confounders

• Number of Medication Changes During Hospitalization (Changes in prescription can be caused by intervention therefore this variable should not be included as a confounder)

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Secondary Outcomes

1. Number of actual severe ADEs
2. Disease-Specific Quality of Life / Disease Control
3. Health Care Utilization

Confounders

Confounders listed under Primary outcomes.

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ANALYSIS

Baseline Analysis

The following baseline variables are summarized for the control and intervention groups and compared using Wilcoxon's rank-sum (for continuous variables) and Chi-Square test (for categorical variables):

• Level of health literacy
• Cognitive function
• Educational attainment
• Primary language
• Gender
• Race
• Age
• Number of prescribed medications

Preliminary Statistical Summary

The following variables are summarized for the control and intervention groups and compared using Wilcoxon's rank-sum test:

• Number of serious medication errors per subject
• Number of preventable/ameliorable ADEs per subject
• Number of potential ADEs per subject
• Number of preventable/ameliorable ADEs by severity

Primary Analyses

In the analyses that follow, the effect of health literacy level on number of (or at least one) preventable/ameliorable serious ADE is tested by introducing an interaction term (intervention with literacy level).

1. We use logistic regression to assess the association between the presence of preventable/ameliorable serious ADE and intervention. The model controls for gender the confounders listed under Primary Outcomes.
2. Logistic regression is used to assess the association between the presence of potential ADE and intervention. The model controls for the confounders listed under Primary Outcomes.
3. Poisson regression (or proportional odds ordinal logistic regression) is used to assess the association between the number of preventable/ameliorable ADEs and intervention. The model controls for the confounders listed under Primary Outcomes.

Secondary Analysis

The effects of the intervention on quality of life, disease control are assessed using proportional odds ordinal logistic regression, controlling for baseline and the confounders listed under Primary Outcomes. The effect of the intervention on health care utilization is assessed using Cox proportional hazard model, controlling for the confounders listed under Primary Outcomes.

To Do

1. To think about few things for the studio: screening, enrollment, confounders (which ones to choose in advance, which ones to see according to the distribution), think about the choice of primary outcomes (to look at the composite outcome or analyze them separately), what to choose as a modification effect (interaction; it is obviously level of health literacy, but may be also investigation site; to check for that or assume it exists)

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