Cardiomyopathies, Cardiotoxicity, Coronary Artery Disease, Diabetes Mellitus, Heart Failure, Hypertension, Ischemia, Peripheral Artery Disease
Conditions
Keywords
clinical decision aid, cancer, cardiac dysfunction, cardio-oncology, artificial intelligence, machine learning, adverse events
Brief summary
This is a single-center, double-arm, open-label, randomized feasibility study that will determine whether a novel clinical decision aid accessed via the electronic health record will be acceptable to both cancer survivors and their cardiologists, will favorably impact appropriate medication use and cardiac imaging surveillance, and will improve clinician and patient decision-making, perception, and behavior towards cardioprotective medication usage and cardiovascular disease imaging utilization.
Detailed description
For this feasibility study, the researchers will create the clinical decision aid and test the central hypothesis that this novel clinical decision aid accessed via the electronic health record will be acceptable to both cancer survivors and their cardiologists and will favorably impact appropriate medication use and cardiac imaging surveillance. The hypothesis is supported by preliminary data suggesting that an initial and rudimentary version of the clinical aid increases appropriate medication use and imaging follow-up in cardio-oncology patients. Success will be determined by ≥85% of clinic visits using the clinical decision aid resulting in pursuit of medication use and cardiac imaging surveillance patterns commensurate with recommendations specific to cancer survivors, with overall rates the same or higher than the group without the clinical decision aid, as well as overall favorable patient and physician focus group comments and survey responses.
Interventions
The clinical decision aid tool will be used at the subject's first visit (Week 0), Week 12 and Week 24.
OTHERStandard Care
Cardiology clinic visits will take place at the subjects first visit (Week 0), Week 12 and Week 24.
Sponsors
Medical College of Wisconsin
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Inclusion criteria
1. Patients ≥18 years with a history of cancer. 2. Have not previously visited a cardiologist to assess cardiovascular risk after cancer diagnosis. 3. Clinically at intermediate, high, or very high risk for cardiovascular diseases determined based on imprecise clinical risk models, such as those used for cardiac dysfunction. 4. Ability to understand a written informed consent form, and willing to sign it prior to study registration.
Exclusion criteria
1. Patient \<18 years. 2. Without a personal history of cancer. 3. Existing cardiomyopathy diagnosed after cancer diagnosis. 4. Documented cognitive impairment. 5. Patient or patient representative who is unable and unwilling to sign the informed consent form.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Medication use | Week 0 | The number of subjects in which medication use pursued is consistent with current medical society recommendations appropriate for the subject. |
| Imaging surveillance | Week 0 | The number of subjects in which imaging surveillance pursued is consistent with current medical society recommendations appropriate for the subject. |
Countries
United States
Contacts
Primary ContactYee Chung Cheng, MD
Outcome results
None listed