Pre-Diabetes Cardiovascular (CV) Care (Pre-Diabetes Wizard)
Improving Prediabetes Cardiovascular Care With EHR-Based Decision Support
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Nearly one in three adults in rural communities has prediabetes, a condition that increases the risk of heart attacks and stroke but can be managed by use of metformin, lifestyle interventions, and control of major cardiovascular (CV) risk factors. However, current prediabetes care is characterized by: (a) delayed recognition of prediabetes; (b) patient unawareness of effective treatment options for prediabetes; (c) poor control of concomitant major CV risk factors; (d) very low rates of metformin initiation; and (e) low rates of follow up to assess ongoing effectiveness of prediabetes management.1-3 Increased use of electronic health records (EHR) in rural communities now provides a new opportunity to improve awareness and management of prediabetes and to reduce these patients' significant CV risk burden. In this project, we implement and evaluate an EHR-linked, Web-based clinical decision support (CDS) system that identifies patients with prediabetes and provides patients and their primary care providers personalized, evidence-based CDS and follow up to reduce risk of heart attacks or stroke. To accomplish this objective, we randomly allocate 30 primary care clinics with their 450 primary care providers and estimated 17,000 prediabetes patients to one of two intervention arms: Usual Care; or else the prediabetes CDS to optimize management and follow up of prediabetes patients with uncontrolled CV risk factors. Random-effects models assess intervention impact on: (a) American College of Cardiology/American Heart Association (ACC/AHA) pooled CV risk; (b) major CV risk factors (blood pressure, lipids, HbA1c, smoking, and BMI); (c) use of evidence-based drugs, including metformin, and lifestyle interventions to manage prediabetes; and (d) patient and provider satisfaction with the intervention strategy. We also conduct a state-of-the-art cost and a cost-effectiveness analysis of the interventions relative to usual care. The Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework, supplemented by the Consolidated Framework for Implementation Research (CFIR), is used to assess implementation processes and outcomes in a rural/urban health system.
The results of the project will provide a template for implementation of personalized CDS tools in rural and urban health settings, resulting in more efficient and effective rural healthcare that can be broadly applied across many clinical domains, incorporates patient treatment preferences, and has the potential to substantially improve the quality of CV care and clinical outcomes of millions of Americans with prediabetes residing in medically underserved areas.
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Locations
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Minnesota
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Duluth, Minnesota, United States, 55805
- Essentia Health
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-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- Pre-Diabetes Diagnosis or Clinical Lab Values and
- One or more of the following CV risk factors: Current smoking, Hypertension, elevated LDL, or BMI not within normal range, AND
- at least one subsequent primary care visit to a randomized clinic 12 to 24 months after the index visit.
Exclusion Criteria:
- Evidence of Diabetes in the previous 12 months
- Pregnant
- Hospice care or Chemotherapy
Study Plan
How is the study designed?
Design Details
- Primary Purpose: TREATMENT
- Allocation: RANDOMIZED
- Interventional Model: PARALLEL
- Masking: SINGLE
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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EXPERIMENTAL: Clinical Decision Support (CV Wizard)
In the Intervention arm, primary care providers will be provided with an EHR-linked, Web-based clinical decision support system that identifies patients with prediabetes and provides patients and their primary care providers personalized, evidence-based CDS and follow up to reduce risk of heart attacks or stroke, optimizing management and follow up of pre-diabetes patients with uncontrolled CV risk factors.
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an EHR-linked, Web-based clinical decision support (CDS) system that identifies patients with prediabetes and provides patients and their primary care providers personalized, evidence-based CDS and follow up to reduce risk of heart attacks or stroke
Other Names:
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NO_INTERVENTION: Usual Care
In the No Intervention arm, patients receive usual care from their primary care clinic and care providers.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Predicted Annual Rate of Change in 10 Year Risk of Fatal or Nonfatal Heart Attack or Stroke
Time Frame: Index visit to 12 months post index visit
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10-year cardiovascular risk was calculated at the index and all post-index patient encounters.
A comparison of the difference in model-estimated annual rate of change in cardiovascular risk in Clinical Decision Support versus Usual Care clinics tested the primary efficacy hypothesis.
The American College of Cardiology/American Heart Association (ACC/AHA) pooled CV risk calculator provides sex- and race-specific 10-year risk estimates for the first ASCVD event for black & white men & women aged 40-79 years.
Variables included in risk assessment equations: age, total cholesterol, high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP) diabetes mellitus (diabetes), and current smoking status.
10-year risk for ASCVD categorized as: Low (<5%), Borderline (5% to 7.4%), Intermediate (7.5% to 19.9%), High (≥20%).
Numerator: Rate of change in Clinical Decision Support.
Denominator: Rate of change in Usual Care.
Relative Risk < 1 supports primary hypothesis.
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Index visit to 12 months post index visit
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Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: Daniel Saman, PhD, Essentia Institute of Rural Health
Publications and helpful links
General Publications
- Karve A, Hayward RA. Prevalence, diagnosis, and treatment of impaired fasting glucose and impaired glucose tolerance in nondiabetic U.S. adults. Diabetes Care. 2010 Nov;33(11):2355-9. doi: 10.2337/dc09-1957. Epub 2010 Aug 19.
- Saman DM, Allen CI, Freitag LA, Harry ML, Sperl-Hillen JM, Ziegenfuss JY, Haapala JL, Crain AL, Desai JR, Ohnsorg KA, O'Connor PJ. Clinician perceptions of a clinical decision support system to reduce cardiovascular risk among prediabetes patients in a predominantly rural healthcare system. BMC Med Inform Decis Mak. 2022 Nov 19;22(1):301. doi: 10.1186/s12911-022-02032-z.
- Pratt R, Saman DM, Allen C, Crabtree B, Ohnsorg K, Sperl-Hillen JM, Harry M, Henzler-Buckingham H, O'Connor PJ, Desai J. Assessing the implementation of a clinical decision support tool in primary care for diabetes prevention: a qualitative interview study using the Consolidated Framework for Implementation Science. BMC Med Inform Decis Mak. 2022 Jan 15;22(1):15. doi: 10.1186/s12911-021-01745-x.
Study record dates
Study Major Dates
Study Start
Study Start
Primary Completion (ACTUAL)
Primary Completion
Study Completion (ACTUAL)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (ESTIMATE)
First Posted
Study Record Updates
Last Update Posted (ACTUAL)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- HL128614-01
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
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