Promoting the Universal Medication Schedule Via Mobile and EHR Technologies

December 10, 2018 updated by: Michael S. Wolf, Northwestern University

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

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.

Study Overview

Status

Completed

Conditions

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.

Study Type

Interventional

Enrollment (Actual)

452

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Illinois
      • Chicago, Illinois, United States, 60611
        • Northwestern University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

30 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Health Services Research
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
No Intervention: Usual Care
Employ the current standard of care. No intervention.
Experimental: 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.
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.
Experimental: 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.
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.
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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Prescription Understanding
Time Frame: 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.
6 months after baseline

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Medication Knowledge
Time Frame: 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.
6 months after baseline
Medication Adherence: Pill Count
Time Frame: 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.
6 months after baseline
Medication Adherence: PMAQ
Time Frame: 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.
6 months after baseline
Medication Adherence: Pharmacy Records
Time Frame: 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.
6 months after baseline

Other Outcome Measures

Outcome Measure
Measure Description
Time Frame
Changes in Blood Pressure
Time Frame: 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).
6 months before baseline to 1 year after baseline
Changes in Hemoglobin A1c (hbA1c)
Time Frame: 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).
6 months before baseline to 1 year after baseline
Changes in Low-density Lipoprotein Cholesterol (LDL)
Time Frame: 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).
6 months before baseline to 1 year after baseline

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Collaborators

Investigators

  • Principal Investigator: Michael Wolf, PhD, MPH, Northwestern University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start

December 1, 2014

Primary Completion (Actual)

December 1, 2016

Study Completion (Actual)

December 1, 2016

Study Registration Dates

First Submitted

September 22, 2014

First Submitted That Met QC Criteria

September 22, 2014

First Posted (Estimate)

September 25, 2014

Study Record Updates

Last Update Posted (Actual)

March 25, 2019

Last Update Submitted That Met QC Criteria

December 10, 2018

Last Verified

December 1, 2018

More Information

Terms related to this study

Other Study ID Numbers

  • STU00097744

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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