NCT03138447

Brief Summary

The digital health tool is an application ("app") available on iOS and Android enabled mobile phones. Health Care Providers ("HCPs") configure algorithms which can be tailored to individual patient's needs and then prescribe the app to support optimal basal insulin titration and dosing. In this study, participants will be recruited from a medical practice in which an HCP has prescribed a once-daily basal insulin. Participants will be trained on the use of the app utilizing their own mobile phone. During training, a brief self-assessment survey will be administered. After 90 days of usage, a telephone survey will be conducted. The baseline A1C results and the end of study A1C results will be collected from the patients' routine clinical care records. Data from the retrospective control group will be collected from a chart review of the same practice.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
30

participants targeted

Target at below P25 for not_applicable diabetes-mellitus-type-2

Timeline
Completed

Started Mar 2017

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

March 30, 2017

Completed
1 month until next milestone

First Submitted

Initial submission to the registry

May 1, 2017

Completed
2 days until next milestone

First Posted

Study publicly available on registry

May 3, 2017

Completed
1.7 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

January 30, 2019

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

January 30, 2019

Completed
Last Updated

March 13, 2019

Status Verified

March 1, 2019

Enrollment Period

1.8 years

First QC Date

May 1, 2017

Last Update Submit

March 11, 2019

Conditions

Keywords

insulinbasaltitrationdigital health

Outcome Measures

Primary Outcomes (1)

  • Basal Insulin Dose

    Change in basal insulin dose from entry into study to completion of study.

    90 days

Secondary Outcomes (7)

  • Change in Fasting Glucose

    90 days

  • Fasting Glucose in Target

    90 days

  • Titration Adherence

    90 days

  • Change in A1C

    90 days

  • Change in Diabetes Distress

    90 days

  • +2 more secondary outcomes

Study Arms (2)

Prospective Cohort

EXPERIMENTAL
Device: Basal Insulin Titration Application

Retrospective Cohort

NO INTERVENTION

Interventions

Healthcare Providers ("HCP") and the principal investigator ("PI") will use an HCP portal to initiate a basal insulin titration algorithm. HCPs can customize the titration algorithm for every participant. Once a participant is prescribed an algorithm, they can download a mobile app on their phone with their HCPs corresponding titration plan. The app will prompt participants to enter their fasting glucose daily. Based on their fasting glucose and their HCPs titration plan, the application will display the participants daily basal insulin dose.

Prospective Cohort

Eligibility Criteria

Age21 Years+
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • \- Prospective cohort: The participants will be patients with type 2 diabetes mellitus who are not at goal on their current dose of prescribed basal insulin (e.g. Lantus, Toujeo, Levemir, Tresiba, or Basaglar). Participants shall be age 21 or older, prescribed basal insulin within the past 18 months, own a compatible mobile phone, able to receive/make calls and read messages on their phone. There is no predefined gender or ethnic group. Participants should be generally healthy and not expected to be hospitalized for surgery or other medical care during the study period.
  • \- Retrospective cohort: This will be a chart review. Participants will be matched to the prospective cohort for age, gender and baseline A1C. Patients should have been prescribed one of the basal insulins above.

You may not qualify if:

  • \- Prospective cohort: Participants with stage 4 or 5 kidney disease, active malignancies, variable glucocorticoid doses during the study period, severe visual impairment, or dementia will be excluded. Also, participants prescribed rapid-acting or premixed insulins (any insulin not on the above list) will be excluded.
  • \- Retrospective cohort: Same as above.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

MODEL Clinical Research

Towson, Maryland, 21204, United States

Location

MeSH Terms

Conditions

Diabetes Mellitus, Type 2Insulin Resistance

Condition Hierarchy (Ancestors)

Diabetes MellitusGlucose Metabolism DisordersMetabolic DiseasesNutritional and Metabolic DiseasesEndocrine System DiseasesHyperinsulinism

Study Design

Study Type
interventional
Phase
not applicable
Allocation
NON RANDOMIZED
Masking
NONE
Purpose
TREATMENT
Intervention Model
PARALLEL
Model Details: The design of this protocol involves a prospective and retrospective cohort. The prospective cohort includes 30 participants. In the retrospective chart review, participants will be matched to the prospective group for age, gender, and baseline A1C. (For this study, the use of the word 'matched' means that the retrospective patient charts will be matched as close as possible from available patient data within the Bay West Endocrinology medical record database and may not always be an exact match to the prospective group for age, gender, and baseline A1c.) The chart review will thus be conducted after the last subject is enrolled in the prospective arm of the study.
Sponsor Type
INDUSTRY
Responsible Party
SPONSOR

Study Record Dates

First Submitted

May 1, 2017

First Posted

May 3, 2017

Study Start

March 30, 2017

Primary Completion

January 30, 2019

Study Completion

January 30, 2019

Last Updated

March 13, 2019

Record last verified: 2019-03

Data Sharing

IPD Sharing
Will not share

Locations