Diabetes Care Transformation: Diabetes Data Registry and Intensive Remote Monitoring
| Status: | Active, not recruiting |
|---|---|
| Conditions: | Diabetes |
| Therapuetic Areas: | Endocrinology |
| Healthy: | No |
| Age Range: | 8 - 17 |
| Updated: | 2/4/2017 |
| Start Date: | September 2015 |
| End Date: | February 2017 |
With emerging mobile technology, sharing glucose, insulin and sensor data with the clinic
for frequent and timely monitoring is now feasible. The investigators propose to leverage
this new technology to provide children and families with appropriate interventions to help
manage their diabetes.
for frequent and timely monitoring is now feasible. The investigators propose to leverage
this new technology to provide children and families with appropriate interventions to help
manage their diabetes.
The investigators will collect insulin dosing via pump records, blood glucose meter,
continuous glucose sensor, activity, heart rate, and sleep data on a weekly basis from 100
children with diabetes. The investigators hypothesize that with the collection and analysis
of insulin, blood glucose, sensor, activity, heart rate and sleep data in children with
diabetes the investigators can identify glucose patterns and predictors of acute events.
The 100 children will be randomized to either conventional therapy (data upload group) or
intensive remote therapy (weekly review group). Conventional therapy will consist of routine
quarterly visits to the clinic and as-needed communication with the diabetes staff,
initiated by the family, between study visits. Intensive remote therapy will consist of
routine quarterly visits to the clinic along with weekly remote review of insulin and blood
glucose data by the research staff, and additional communication with the family, initiated
by the diabetes staff as needed, between visits. The investigators hypothesize that with
weekly, manual review of real-time insulin, glucose, and activity data in children with
diabetes, and recommended regimen changes based on the data, the investigators will be able
to lower HbA1c values in children in the weekly review group as compared to children in the
data upload group.
continuous glucose sensor, activity, heart rate, and sleep data on a weekly basis from 100
children with diabetes. The investigators hypothesize that with the collection and analysis
of insulin, blood glucose, sensor, activity, heart rate and sleep data in children with
diabetes the investigators can identify glucose patterns and predictors of acute events.
The 100 children will be randomized to either conventional therapy (data upload group) or
intensive remote therapy (weekly review group). Conventional therapy will consist of routine
quarterly visits to the clinic and as-needed communication with the diabetes staff,
initiated by the family, between study visits. Intensive remote therapy will consist of
routine quarterly visits to the clinic along with weekly remote review of insulin and blood
glucose data by the research staff, and additional communication with the family, initiated
by the diabetes staff as needed, between visits. The investigators hypothesize that with
weekly, manual review of real-time insulin, glucose, and activity data in children with
diabetes, and recommended regimen changes based on the data, the investigators will be able
to lower HbA1c values in children in the weekly review group as compared to children in the
data upload group.
Inclusion Criteria:
1. Type 1 diabetes, using an insulin pump (Medtronic, Omnipod, Animas)
2. Duration of diabetes >1 year
3. Age: 8-17 years of age, inclusive.
4. Hemoglobin A1c 8.0-10.0% at baseline visit, inclusive.
5. Seen in the McNeely Diabetes Clinic within the past 6 months.
6. The family/child is testing blood glucose at least 4 times a day.
7. The family has a smart phone and service.
Exclusion Criteria:
1. The child is not using insulin for management of diabetes.
2. The child uses multiple daily injections of insulin.
3. The child is unwilling to use the wearable device, or the family is unwilling or
unable to upload glucose and insulin data on a routine basis
4. The family is unwilling or unable to upload data from devices such as meter, pump,
sensor, wearable device.
5. Diagnosis of a mental health disorder.
6. Parent/child does not speak English as the device software is only available in
English.
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