Promoting the Universal Medication Schedule Via Mobile and EHR Technologies

Type 2 Diabetes Clinical Trial

Official title:

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

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT02248857
• Other study ID #: STU00097744
• Status: Completed
• Phase: N/A
• Start date: December 2014
• Est. completion date: December 2016

Study information

• Verified date: December 2018
• Source: Northwestern University
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 452
• Est. completion date: December 2016
• Est. primary completion date: December 2016
• Accepts healthy volunteers: No
• Gender: All
• Age group: 30 Years and older

Eligibility

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

Related Conditions & MeSH terms

• Type 2 Diabetes

Intervention

Other:
• 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.

Locations

Country	Name	City	State
United States	Northwestern University	Chicago	Illinois

Sponsors (2)

Lead Sponsor	Collaborator
Northwestern University	Merck Sharp & Dohme Corp.

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	Changes in Blood Pressure	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
Other	Changes in Hemoglobin A1c (hbA1c)	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
Other	Changes in Low-density Lipoprotein Cholesterol (LDL)	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
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.	6 months after baseline
Secondary	Medication Knowledge	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
Secondary	Medication Adherence: Pill Count	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
Secondary	Medication Adherence: PMAQ	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
Secondary	Medication Adherence: Pharmacy Records	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