A Universal Medication Schedule to Promote Adherence to Complex Drug Regimens

Pill Count is conducted for all pill form medications using an electronic pill counter at baseline and 6 months. The proportion of pills taken over pills prescribed (PT/PP) will be calculated for each medication at each time point. Pills taken will be calculated by subtracting the number of pills from the total quantity prescribed. Pills prescribed will be calculated by multiplying the number of pills prescribed each day by the number of days since the medication was filled. A proportion of pills taken over pills prescribed (PT/PP) of 80% or more is considered adherent.

Analyses were performed using 2-level Generalized linear models (PROC GENMOD), with medications nested in participants and with a logit link.

Confounding variables, such as adherence at baseline, gender, age, language, health status and medication regimen complexity index (MRCI) were included as fixed effects in the models. Results are presented as predicted probabilities with 95% Confidence Intervals.

Participants are asked questions about their 24 hour recall of medication use for each of their medications; they are asked to specify the amount taken (dose), the number of times the med was taken (frequency), the total number of pills taken, and when the doses were taken (to calculate spacing: hours between doses). Proper Use will be scored as yes or no, reflecting having demonstrated all of the following: correct dose, frequency, total and spacing based on the medication bottle instructions. Results are presented as predicted probabilities with 95% Confidence Intervals.

Analyses were performed using 2-level Generalized linear models (PROC GENMOD), with medications nested in participants and with a logit link.

Confounding variables, such as recruitment time, clinic, health status, gender, age, time effect, and medication regimen complexity index (MRCI) were included as fixed effects in the models.

Participants completed the ASK-12 questionnaire, a brief measure of adherence that cover three key domains: inconvenience/forgetfulness, treatment beliefs and behavior.

The ASK-12 is scored by summing the selected responses (with scores ranging from 12 to 60) with higher scores indicating greater barriers to adherence.

Analyses were performed using Generalized linear models (PROC GENMOD), with a repeated subject effect, and an identity link.

Confounding variables such as health status, gender, age, health activation (CHAI), language, time effect and number of chronic conditions were included as fixed effects in the models. Results are presented as predicted probabilities with 95% Confidence Intervals.

Systolic blood pressure will be collected on all participants at baseline and 6 months.

Change of Systolic blood pressure from baseline will be measured, only in those who are diagnosed with hypertension. Negative Least Square Means indicate a decrease of systolic blood pressure, whereas a positive Least Square Means indicate an increase of systolic blood pressure by 6 Months.

Analyses were performed using Generalized linear models (PROC GENMOD), with an identity link.

Confounding variables, such as mean systolic blood pressure at baseline, gender, age, race, and number of prescribed medications were included as fixed effects in the models. Results are presented as adjusted least square means with 95% Confidence Intervals.

Hemoglobin A1c (hbA1c) will be collected on diabetic patients only, at baseline and 6 months.

Change of hbA1c from baseline is modelled. A positive Least Square Mean indicates an increase of hbA1c at 6 months, whereas a negative Least Square Mean indicates a decrease of hbA1c.

Analyses were performed using Generalized linear models (PROC GENMOD), with an identity link.

Confounding variables, such as hbA1c at baseline, gender, age, health status, language, medication regimen complexity index (MRCI), and health literacy (Newest Vital Sign) were included as fixed effects in the models. Results are presented as adjusted least square means with 95% Confidence Intervals.