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Decision Support for Heart Failure Prescribing

Not Applicable
Not yet recruiting
Conditions
Heart Failure
Decision Support Systems, Clinical
Interventions
Other: Personalized Clinical Decision Support (CDS)
Other: Traditional Clinical Decision Support (CDS)
Registration Number
NCT06293794
Lead Sponsor
University of Colorado, Denver
Brief Summary

Clinical decision support (CDS) tools can 'nudge' clinicians to make the best decisions easy. Although required by "meaningful use" regulations, more than 40% of CDS lead to no change and the remaining lead to improvements that are modest at best. This is because CDS tools often ignore contextual factors and present irrelevant information. Although many tools have undergone patient-specific optimization, 'traditional CDS' are rarely clinician-specific. For example, a traditional CDS tool for beta blockers and heart failure with reduced ejection fraction (HFrEF) addresses common prescribing misconceptions by stating asthma is not a contraindication and providing a safe threshold for blood pressure. For clinicians without these misconceptions, these statements are irrelevant and distract from key information. A 'personalized CDS' would evaluate clinician past prescribing patterns to determine whether prescribing misconceptions might exist and then conditionally present information to address those misconceptions. The objective of this research is to create personalized clinician-specific CDS that overcome shortcomings of traditional CDS. The central hypothesis is a personalized CDS that minimizes irrelevant information will lead to a higher rate of prescribing guideline-directed management and therapy (GDMT) for HFrEF compared to a traditional CDS.

Detailed Description

Not available

Recruitment & Eligibility

Status
NOT_YET_RECRUITING
Sex
All
Target Recruitment
1075
Inclusion Criteria
  • The study subjects are potential users of the CDS, specifically clinicians with prescribing privileges who practice at one of the health system's (UCHealth) outpatient cardiology or primary care clinics. Because we are observing their prescribing behaviors, we are also evaluating patient characteristics which could influence their prescribing decisions.
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Exclusion Criteria
  • Clinicians who do not practice in cardiology or primary care clinics or do not practice within UCHealth system.
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Study & Design

Study Type
INTERVENTIONAL
Study Design
PARALLEL
Arm && Interventions
GroupInterventionDescription
Personalized Clinical Decision Support (CDS)Personalized Clinical Decision Support (CDS)-
Traditional Clinical Decision Support (CDS)Traditional Clinical Decision Support (CDS)-
Primary Outcome Measures
NameTimeMethod
Number of CDS alerts resulting in the prescription of a recommended medication6 months

The primary outcome is number of CDS alerts that resulted in the prescription of the medication recommended by the CDS alert. Recommended medications include either evidence-based beta blockers, sacubitril/valsartan, mineralocorticoid receptor antagonists or sodium/glucose cotransport 2 inhibitors. Prescriptions will be based on actual prescription orders instead of clinician-stated responses, given the latter may overestimate effectiveness.

Secondary Outcome Measures
NameTimeMethod
Number of patients the CDS alerted for6 months

This outcome evaluates the reach of the CDS by counting the number of patients that the CDS alerted for.

Number of prescription orders for guideline directed management and therapies (GDMT) for heart failure6 months

This outcome measures the number of prescriptions for each of the four categories of GDMT: evidence-based beta blockers, sacubitril/valsartan, mineralocorticoid receptor antagonists or sodium/glucose cotransport 2 inhibitors.

Number of alerts that were not outright dismissed6 months

This outcome will help investigators understand if the CDS id being used or dismissed.

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