Improving Diagnosis and Clinical Management of Familial Hypercholesterolemia Through Integrated Machine Learning, Implementation Science, and Behavioral Economics
Improving Diagnosis and Clinical Management of Familial Hypercholesterolemia Through Integrated Machine Learning, Implementation Science, and Behavioral Economics
The goal of this study is to identify individuals at high risk of FH, and to encourage the appropriate diagnosis and treatment of individuals at high risk of FH through the use of implementation science and behavioral economics principles.
Phase 1: Applying the FIND FH tool to the health system EHR and gathering data for pilot development; Phase 2: Pilot development and implementation; Phase 3: Conduct a large-scale pragmatic trial consistent with recommendations and learnings from the pilots in Phase 2
Phase 1:
Aim 1: Adjusting and refining the application of the FIND FH tool to the UPHS EHR database Aim 2: Identifying the barriers and facilitators to making a diagnosis of FH and initiating or intensifying therapy for individuals with FH through qualitative interviews with clinicians and patients and creating a behavioral roadmap to inform the implementation approaches to test in the pilots
Phase 2:
Aim 1: Co-design implementation strategies using behavioral economics in partnership with the Family Heart Foundation Aim 2: Pilot implementation strategies with an enrollment goal of 80 patients total (40 per pilot) who have been flagged by the FIND FH tool as having probable FH to ascertain feasibility, acceptability, and appropriateness
Phase 3: Conduct a large-scale pragmatic trial consistent with recommendations and learnings from the pilots in Phase 2
Inclusion Criteria:
Exclusion Criteria: