Evaluation of a Dashboard for Diabetes Care Integrated With the Electronic Health Record

NCT03826290 | Completed

• 1 other identifier: UUtah_00109162
• Study Type: interventional
• Target: 13,155
• Locations: 1 country
• Sites: 1

Brief 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 objective of this research is to evaluate a diabetes dashboard integrated with the electronic health record (EHR) that has been developed as a collaborative project between the University of Utah and Hitachi, Ltd. This dashboard tool provides a graphical overview of the patient's relevant data parameters as well as information on the impact of different treatment options on previous patients with similar characteristics. The different treatment options compare the predicted impact of relevant medication regimens as well as weight loss. Primary care clinics are randomized to either an intervention condition where the tool is available or to a control condition where the tool is not yet available. Patients' hemoglobin A1c levels (a measure of diabetes control) are the main outcome variable. Other secondary analyses will also be conducted. Use of the tool will be encouraged but optional. Following any suggestions made in the tool will also be optional and up to the discretion of the clinician.

Conditions

Diabetes Mellitus; Diabetes Mellitus, Type 2

Keywords

Decision Support Systems, Clinical; Machine Learning; Data Visualization

Outcome Measures

Primary Outcomes (1)

• Per-patient change in Hemoglobin A1c (HbA1c) levels from beginning to end of evaluation period

  Each patient's HbA1c level will be estimated for the beginning and end of the evaluation period. For each of these time points, the value at that time point will be estimated as follows. If a value exists for that date, use that. Otherwise, for the beginning date, first take the earliest value within the evaluation period (anchor value). If there are no values before the evaluation period, then use the anchor value. Otherwise, take the latest value before the evaluation period, and interpolate with the anchor value to estimate the value. For the value on the end date, first take the latest value within the evaluation period (anchor value). If there are no values after the evaluation period, then use the anchor value. Otherwise, take the earliest value after the evaluation period, and interpolate with the anchor value to estimate the value. Finally, calculate the change in values by comparing the end value to the beginning value.

  Assessed through study completion (estimated to be 1.5 years), for Day 1 and Day 365

Secondary Outcomes (2)

• Per-patient change in body mass index (BMI) from beginning to end of evaluation period

  Assessed through study completion (estimated to be 1.5 years), for Day 1 and Day 365

• Cost of diabetes medications prescribed

  Assessed through study completion (estimated to be 1.5 years), for Day 1 through Day 365

Other Outcomes (2)

• Use of the diabetes dashboard

  Assessed through study completion (estimated to be 1.5 years), for Day 1 through Day 365

• User opinions of the diabetes dashboard

  Assessed through study completion (estimated to be 1.5 years), for Day 1 through Day 365

Study Arms (2)

Intervention arm

EXPERIMENTAL

When patients are seen in clinics in this arm, the clinical providers will have access to the intervention (EHR-integrated diabetes dashboard).

Other: EHR-integrated diabetes dashboard

Control arm

NO INTERVENTION

When patients are seen in clinics in this arm, the clinical providers will not have access to the intervention (EHR-integrated diabetes dashboard). The providers will have access to the usual decision support tools and information sources.

Interventions

EHR-integrated diabetes dashboard OTHER

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.

Also known as: Pharmacotherapy decision support system (PDSS)

Intervention arm

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• \>= 18 years old
• Are being seen at a University of Utah primary care clinic
• Has diabetes mellitus

You may not qualify if:

• 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.

Sponsors & Collaborators

• University of Utah: lead
• Hitachi, Ltd.: collaborator

Study Sites (1)

University of Utah Health

Salt Lake City, Utah, 84132, United States

Location

Related Publications (3)

• American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2004 Jan;27 Suppl 1:S5-S10. doi: 10.2337/diacare.27.2007.s5. No abstract available.

  PMID: 14693921 BACKGROUND

• American Diabetes Association. Economic costs of diabetes in the U.S. in 2012. Diabetes Care. 2013 Apr;36(4):1033-46. doi: 10.2337/dc12-2625. Epub 2013 Mar 6.

  PMID: 23468086 BACKGROUND

• American Diabetes Association. 7. Approaches to Glycemic Treatment. Diabetes Care. 2016 Jan;39 Suppl 1:S52-9. doi: 10.2337/dc16-S010. No abstract available.

  PMID: 26696682 BACKGROUND

MeSH Terms

Conditions

Diabetes Mellitus; Diabetes Mellitus, Type 2

Condition Hierarchy (Ancestors)

Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases

Study Officials

• Kensaku Kawamoto, MD, PhD, MHS

  University of Utah

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor, Department of Biomedical Informatics

Model Details: Clinic randomized trial

Study Record Dates

• First Submitted: January 24, 2019
• First Posted: February 1, 2019
• Study Start: January 1, 2019
• Primary Completion: January 1, 2020
• Study Completion: July 1, 2020
• Last Updated: April 27, 2021

Record last verified: 2021-04

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)