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CompletedNCT04928248Updated Nov 4, 2022

Design, Implementation and Evaluation of Scalable Decision Support for Diabetes Care

An interventional study of Diabetes Dashboard integrated with Disease Manager App in Diabetes Mellitus, Type 2 and Diabetes Mellitus, sponsored by University of Utah. Completed at 1 site in United States. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2022-11-04.

Sponsored by University of Utah · Not applicable, Interventional, and Treatment

Phase
Not applicable
Study type
Interventional
Enrollment
25,915
Allocation
Not applicable
Ages
18 Years and older
Sex
All
01

Study summary

Diabetes is a significant medical problem in the United States and across the world. Despite significant progress in understanding how to better manage diabetes, there is oftentimes still uncertainty in the optimal management strategy for a specific patient. As a result, providers and patients must often use a trial-and-error approach to identify an effective treatment regimen.

The project team has previously developed a Diabetes Dashboard that summarizes relevant patient information (e.g., medication history and recent hemoglobin A1c trend). This dashboard allows a clinician to select a target hemoglobin A1c level for the patient in 3 or 6 months, then compare and contrast different options for treatment, including weight loss and the use of different medication regimens. Included in this comparison are known benefits and side effects, as well as the likely chances of achieving the treatment target given the experience of past, similar patients. The Diabetes Dashboard is already available as an optional tab in the EHR system.

The project team has also previously developed the Disease Manager App for evidence-based chronic disease management and health maintenance. The Disease Manger Application is fully integrated with the EHR, and it provides care guidance via individual chronic disease modules as well as a unified module that encompasses all relevant modules for chronic diseases and health maintenance. The initial modules that have been developed are for chronic obstructive pulmonary disease, hypertension, diabetes mellitus, and health maintenance.

The objective of this research is to evaluate the Diabetes Dashboard integrated with the Disease Manager App. The Intervention consists of the diabetes module of the Disease Manager App, which incorporates content from the Diabetes Dashboard for pharmacotherapy prediction and provides a link to the Diabetes Dashboard.

Read the detailed description

This study is a pragmatic pre-post trial of the Diabetes Dashboard integrated with the Disease Manager App. The Disease Manager App is available as a tab in the EHR and enables clinicians to confirm relevant patient parameters. A link to the Diabetes Dashboard will be available from the Disease Manager App diabetes module. In the Diabetes Dashboard, providers can select treatment goals and review likely outcomes from alternative treatment strategies through an interactive graphical user interface. In the review process, the Diabetes Dashboard enables providers and patients to compare up to three potential therapies side-by side including weight-loss in terms of a) personalized, predicted probability of achieving treatment goals; b) general potential risks, benefits, and medication costs; and c) relevant financial information specific to the patient's insurance. The personalized prediction is performed by a predictive model developed by analyzing data sets of patients with diabetes mellitus. The Disease Manager App and the Diabetes Dashboard are seamlessly integrated with the EHR using an interoperability standard known as SMART on FHIR (short for Substitutable Medical Apps Reusable Technologies on Fast Healthcare Interoperability Resources).

The study is being conducted at University of Utah primary care clinics. In all primary care clinics, providers will be provided with access to the Diabetes Dashboard integrated with the Disease Manager App. Iterative enhancements will be made to the tool if warranted based on the results of a formative evaluation during the 1-year pragmatic implementation study. Use of the tool and associated suggestions will be optional and up to the discretion of the clinician. Use of the tool will be regularly monitored, and a mixed-methods evaluation will be conducted of the tool and its impact.

The primary outcome measure will be hemoglobin A1c (HbA1c) levels, which are an important physiological marker of diabetes control. Secondary measures will include body mass index (BMI) and the cost of diabetes medications prescribed. Other measures will include usage of the tool and clinical users' opinions of the tool.

The primary study analyses will be limited to adult patients who were seen at least twice in the primary care clinics during the evaluation period for office visits with a visit diagnosis of diabetes mellitus, who are known to have diabetes mellitus (but not type-1 diabetes mellitus), who had at least one HbA1c of >= 7.5% during the evaluation period, and who are not already on maximal diabetes therapy (as defined by the use of short-acting insulin) at the start of the study. Secondary study analyses will be conducted on patient subsets, including a per protocol analysis of cases where the tool was used.

02

Conditions studied

  • Diabetes Mellitus, Type 2
  • Diabetes Mellitus

Keywords

  • Digital Health Intervention
  • Clinical Decision Support
03

In context

Diabetes Mellitus

10,925 studies on the registry are indexed under Diabetes Mellitus; 1,319 are open to participants now.

This study's enrollment of 25,915 is above the median of 80 across 8,367 interventional studies indexed under Diabetes Mellitus.

Browse Diabetes Mellitus studies →

Lead sponsor

University of Utah is the lead sponsor of 969 studies on the registry; 178 are open to participants now.

Of its 107 completed or terminated interventional studies of FDA-regulated products, 62 (58%) have results posted.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Inclusion criteria

  1. >= 18 years old
  2. are being seen at a University of Utah primary care clinic
  3. has diabetes mellitus

Exclusion criteria

Exclusion Criteria:

None.

Note that the primary study analyses will be on a subset of these patients. See the Detailed Description subsection in the Study Description section for details.

05

Study design

Phase
Not applicable
Primary purpose
Treatment
Allocation
Not applicable
Intervention model
Single group
Masking
None (open label)
Enrollment
25,915 participants (actual)

Study arms

  • Experimental
    Diabetes Dashboard integrated with Disease Manager App

    When patients are seen in clinics in this arm, the clinical providers will have access to the intervention (EHR-integrated Diabetes Dashboard that is integrated with the diabetes module of the Disease Manager App).

    Other: Diabetes Dashboard integrated with Disease Manager App

Interventions

  • OtherDiabetes Dashboard integrated with Disease Manager App

    The Diabetes Dashboard is available as a tab in the electronic health record (EHR) system and enables clinicians to confirm relevant patient parameters, select treatment goals, and review likely outcomes from alternative treatment strategies through an interactive graphical user interface. The Diabetes Dashboard is integrated within the diabetes module of the EHR-integrated Disease Manager App, which uses key information from the Diabetes Dashboard and provides a link to the Diabetes Dashboard.

06

What researchers measure

Primary outcomes

  1. Change in hemoglobin A1c (HbA1c) levels

    Each patient's HbA1c level will be estimated for day 15 of each month, calculated as follows. If a value exists for that date, use that. Otherwise, estimate the value on that date based on the values immediately before and after that date.

    Time frame: Through study completion, an average of 12 months for the intervention period and 12 months for the baseline period

Secondary outcomes

  1. Change in body mass index (BMI) levels

    The BMI values will be estimated in a manner similar to HbA1c estimation.

    Time frame: Through study completion, an average of 12 months for the intervention period and 12 months for the baseline period

Other outcomes

  1. Rate of use of the Disease Manager's diabetes module

    The rate of use of the Disease Manager's diabetes module will be measured. The usage will be measured through system logs and data from the enterprise data warehouse.

    Time frame: Through study completion, an average of 12 months for the intervention period

07

Study locations

1 site
  • University of Utah Health
    Salt Lake City, Utah 84132, United States
08

References and documents

Publications

  • Tarumi S, Takeuchi W, Chalkidis G, Rodriguez-Loya S, Kuwata J, Flynn M, Turner KM, Sakaguchi FH, Weir C, Kramer H, Shields DE, Warner PB, Kukhareva P, Ban H, Kawamoto K. Leveraging Artificial Intelligence to Improve Chronic Disease Care: Methods and Application to Pharmacotherapy Decision Support for Type-2 Diabetes Mellitus. Methods Inf Med. 2021 Jun;60(S 01):e32-e43. doi: 10.1055/s-0041-1728757. Epub 2021 May 11. PubMed 33975376 ↗

Individual participant data

Plan to share: No

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Nov 4, 2022, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT04928248
Lead sponsor
University of Utah
Collaborators
Hitachi, Ltd.
Responsible party
Kensaku Kawamoto, MD, PhD, MHS (Associate Professor of Biomedical Informatics, University of Utah) — Principal investigator
First posted
Jun 16, 2021
Start date
Sep 23, 2021
Primary completion
Sep 22, 2022
Completion
Nov 1, 2022
Last update
Nov 4, 2022

Study contacts

Kawamoto Kensaku, MD, PhD, MHS
principal investigator · University of Utah

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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This study is completed, as verified in Nov 2022. You cannot join it, but the record below documents what was studied.

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