Promoting the Universal Medication Schedule Via Mobile and EHR Technologies

Promoting the Universal Medication Schedule Via Mobile and EHR Technologies: A Physician-randomized Control Trial

Status

Completed

Phases

Study type

Interventional

Source

ClinicalTrials.gov

Registry ID

NCT02248857

Enrollment

452

Registered

2014-09-25

Start date

2014-12-31

Completion date

2016-12-31

Last updated

2019-03-25

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Type 2 Diabetes

Keywords

UMS, medication schedule, diabetes, drug labeling

Brief summary

The purpose of this study test the effectiveness of the Universal Medication Schedule (UMS), which was designed as a strategy to standardize and simplify medication instructions to support safe and effective prescription drug use among diabetic.

Detailed description

Research has shown the UMS (1) improves patients' understanding of how much to take of a medicine and when, and (2) reduces the number of times per day patients would take a multi-drug regimen. In this study, UMS tools will be exported into a second electronic health record platform to demonstrate ease of dissemination. Also, as patients may require assistance outside of clinic visits to adapt their prescription regimen to the UMS, this study will test the potential benefit of daily short message service (SMS) text reminders via cell phone. We will conduct a three-arm, provider-randomized controlled trial among English and Spanish-speaking adults taking three or more prescription drugs to evaluate the effectiveness of the UMS strategy, with and without SMS text reminders, to improve patient understanding, consolidation, and adherence compared to usual care.We will conduct a three-arm, provider-randomized trial at two community health centers in Chicago, IL to evaluate the UMS and UMS+SMS text reminder strategies compared to usual care. English and Spanish-speaking patients who are prescribed three or more medications will be recruited and assessed by phone at baseline, three months, and six months.

Interventions

OTHERUMS Strategy

Patients of providers randomized to the UMS arm will receive study-related educational tools at their primary care visit to support the understanding, regimen consolidation, and use of prescriptions.

OTHERSMS Texting Reminders

In addition to the components from the UMS strategy arm, patients will receive daily text reminders for 7 days, with the option of extending reminders, following a study medication prescription.

Study design

Allocation

RANDOMIZED

Intervention model

PARALLEL

Primary purpose

HEALTH_SERVICES_RESEARCH

Masking

NONE

Eligibility

Sex/Gender

ALL

Age

30 Years to No maximum

Healthy volunteers

Inclusion criteria

* diagnosis of type II diabetes * age 30 or older * taking 3 or more prescription medications for chronic conditions * English or Spanish speaking

Exclusion criteria

* self-reported severe, uncorrectable vision * hearing impairment * cognitive impairment * not responsible for administering his/her own medications * not able to receive text messages on their cell phone

Design outcomes

Primary

Measure	Time frame	Description
Prescription Understanding	6 months after baseline	Predictive probabilities of prescription understanding will be calculated based on patients' ability to correctly dose their prescription medications using unadjusted Generalized Estimating Equation models, specifying the binomial family and logit link, with medication as the unit of analysis. Correct dosing per medication will be scored as yes or no, reflecting having demonstrated all of the following: proper dose (# of pills), spacing (hours between doses), frequency (# of times per day), and total pills per day. Results are presented as predicted probabilities with 95% Confidence Intervals.

Secondary

Measure	Time frame	Description
Medication Adherence: Pill Count	6 months after baseline	Predictive probabilities of medication adherence will be calculated based on telephone pill counts using unadjusted Generalized Estimating Equation models, specifying the binomial family and logit link, with medication as the unit of analysis. Pills taken/pills prescribed will be calculated for each medication and scored as adherent for that medication if that score is between 80% and 120%. Results are presented as predicted probabilities with 95% Confidence Intervals.
Medication Knowledge	6 months after baseline	Predictive probabilities of medication knowledge will be calculated based on patients' ability to identify each medication's purpose and side effects, risks, warnings, and benefits using unadjusted Generalized Estimating Equation models, specifying the binomial family and logit link, with medication as the unit of analysis. Patients will be asked through a structured questionnaire about each of the above via structured, open-ended items. Each medication will be scored as correct/incorrect if the participant knew the purpose and could name at least 1 side effect, risk, or warning of the medication. Results are presented as predicted probabilities with 95% Confidence Intervals.
Medication Adherence: PMAQ	6 months after baseline	Predictive probabilities of medication adherence will be calculated based on a 4-item validated Patient Medication Adherence Questionnaire (PMAQ) using unadjusted Generalized Estimating Equation models, specifying the binomial family and logit link, with medication as the unit of analysis. The PMAQ assesses adherence behaviors by asking patients to self-report missed/wrong doses in past 4 days, scoring each medication as adherent for that medication if no missed doses were reported. Results are presented as predicted probabilities with 95% Confidence Intervals.
Medication Adherence: Pharmacy Records	6 months after baseline	Predictive probabilities of primary medication adherence will be calculated based on the proportion of days covered (PDC) with medication obtained from pharmacy records using unadjusted Generalized Estimating Equation models, specifying the binomial family and logit link, with medication as the unit of analysis. PDC is calculated by summing the number of days' supply obtained by a patient during a given time period and dividing by the number of days for which the patient was prescribed the medication. Each medication is scored as adherent if the patient was covered for that medication more than 80% of the time. Results are presented as predicted probabilities with 95% Confidence Intervals.

Other

Measure	Time frame	Description
Changes in Low-density Lipoprotein Cholesterol (LDL)	6 months before baseline to 1 year after baseline	An exploratory analysis will be conducted to investigate the impact of receiving the UMS in either intervention arm on biologic outcomes for these prevalent conditions. Low-density lipoprotein cholesterol (LDL) will be obtained from patients' electronic health records. Differences will be measured between the last clinical measurement prior to baseline assessment and the last measured value during the study period (closest to 6 month assessment).
Changes in Hemoglobin A1c (hbA1c)	6 months before baseline to 1 year after baseline	An exploratory analysis will be conducted to investigate the impact of receiving the UMS in either intervention arm on biologic outcomes for these prevalent conditions. Hemoglobin A1c (hbA1c) will be obtained from patients' electronic health records. Differences will be measured between the last clinical measurement prior to baseline assessment and the last measured value during the study period (closest to 6 month assessment).
Changes in Blood Pressure	6 months before baseline to 1 year after baseline	An exploratory analysis will be conducted to investigate the impact of receiving the UMS in either intervention arm on biologic outcomes for these prevalent conditions. Systolic blood pressure will be obtained from patients' electronic health records. Differences will be measured between the last clinical measurement prior to baseline assessment and the last measured value during the study period (closest to 6 month assessment).

Countries

United States

Participant flow

Participants by arm

Arm	Count
Usual Care Employ the current standard of care. No intervention.	157
UMS Strategy Patients of providers randomized to the UMS arm will receive study-related educational tools at their primary care visit to support the understanding, regimen consolidation, and use of prescriptions. 1. Prescription instructions will be adapted to UMS to establish four standard time intervals for prescribing and dispensing of medicine. UMS instructions also use simplified text and numeric characters instead of words to detail dose. 2. Single-page, plain language medication information sheets with content from a patient's perspective and following health literacy best practices. 3. A list of their current medications each corresponding to a set of instructions and a checkbox for morning, noon, evening, and bedtime medicine to help patients visually depict when to take their medicines.	168
UMS Strategy + SMS Texting Reminders In addition to the components from the UMS strategy arm, patients will receive daily text reminders for 7 days, with the option of extending reminders, following a study medication prescription. UMS Strategy: Patients of providers randomized to the UMS arm will receive study-related educational tools at their primary care visit to support the understanding, regimen consolidation, and use of prescriptions. SMS Texting Reminders: In addition to the components from the UMS strategy arm, patients will receive daily text reminders for 7 days, with the option of extending reminders, following a study medication prescription.	127
Total	452

Withdrawals & dropouts

Period	Reason	FG000	FG001	FG002
3 Month	Partially completed, unable to finish	2	2	1
3 Month	Unable to reach for 3 month	35	29	26
3 Month	Withdrawal by Subject	9	3	4
6 Month	Death	1	0	0
6 Month	Lost to Follow-up	27	26	15
6 Month	Partially completed, unable to finish	0	1	0
6 Month	Withdrawal by Subject	0	2	2

Baseline characteristics

Characteristic	Usual Care	UMS Strategy	UMS Strategy + SMS Texting Reminders	Total
Age, Categorical <=18 years	0 Participants	0 Participants	0 Participants	0 Participants
Age, Categorical >=65 years	26 Participants	26 Participants	32 Participants	84 Participants
Age, Categorical Between 18 and 65 years	131 Participants	142 Participants	95 Participants	368 Participants
Age, Continuous	56.5 years STANDARD_DEVIATION 9.4	56.4 years STANDARD_DEVIATION 9.3	57.5 years STANDARD_DEVIATION 9.9	56.7 years STANDARD_DEVIATION 9.5
Ethnicity (NIH/OMB) Hispanic or Latino	113 Participants	127 Participants	91 Participants	331 Participants
Ethnicity (NIH/OMB) Not Hispanic or Latino	43 Participants	41 Participants	36 Participants	120 Participants
Ethnicity (NIH/OMB) Unknown or Not Reported	1 Participants	0 Participants	0 Participants	1 Participants
Race (NIH/OMB) American Indian or Alaska Native	1 Participants	1 Participants	3 Participants	5 Participants
Race (NIH/OMB) Asian	3 Participants	6 Participants	1 Participants	10 Participants
Race (NIH/OMB) Black or African American	32 Participants	27 Participants	23 Participants	82 Participants
Race (NIH/OMB) More than one race	1 Participants	0 Participants	2 Participants	3 Participants
Race (NIH/OMB) Native Hawaiian or Other Pacific Islander	0 Participants	0 Participants	0 Participants	0 Participants
Race (NIH/OMB) Unknown or Not Reported	8 Participants	4 Participants	2 Participants	14 Participants
Race (NIH/OMB) White	112 Participants	130 Participants	96 Participants	338 Participants
Region of Enrollment United States	157 participants	168 participants	127 participants	452 participants
Sex: Female, Male Female	100 Participants	108 Participants	87 Participants	295 Participants
Sex: Female, Male Male	57 Participants	60 Participants	40 Participants	157 Participants

Adverse events

Event type	EG000 affected / at risk	EG001 affected / at risk	EG002 affected / at risk
deaths Total, all-cause mortality	— / —	— / —	— / —
other Total, other adverse events	0 / 157	0 / 168	0 / 127
serious Total, serious adverse events	0 / 157	0 / 168	0 / 127

Outcome results

Primary

Prescription Understanding

Predictive probabilities of prescription understanding will be calculated based on patients' ability to correctly dose their prescription medications using unadjusted Generalized Estimating Equation models, specifying the binomial family and logit link, with medication as the unit of analysis. Correct dosing per medication will be scored as yes or no, reflecting having demonstrated all of the following: proper dose (# of pills), spacing (hours between doses), frequency (# of times per day), and total pills per day. Results are presented as predicted probabilities with 95% Confidence Intervals.