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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Enrollment
764
The personalized CDS intervention evaluates clinician past prescribing patterns to determine whether prescribing misconceptions might exist and then conditionally present information to address those misconceptions. This is done through a nudge in the electronic health record that addresses common prescribing misconceptions for heart failure.
The traditional CDS is the usual care intervention, which is patient-specific but are not clinician-specific.
UCHealth Primary Care and Cardiology Outpatient Clinics
Aurora, Colorado, United States
Number of CDS alerts resulting in the prescription of a recommended medication
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.
Time frame: 6 months
Number of patients the CDS alerted for
This outcome evaluates the reach of the CDS by counting the number of patients that the CDS alerted for.
Time frame: 6 months
Number of alerts that were not outright dismissed
This outcome will help investigators understand if the CDS id being used or dismissed.
Time frame: 6 months
Number of prescription orders for guideline directed management and therapies (GDMT) for heart failure
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.
Time frame: 6 months
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