Abstract Body (Do not enter title and authors here): Introduction: Familial hypercholesterolemia (FH) is an under-diagnosed genetic disorder resulting in elevated LDL cholesterol from birth leading to premature atherosclerotic cardiovascular disease if untreated. To accelerate the identification of individuals living with FH the Family Heart Foundation launched the FIND FH Collaborative Learning Network (CLN). This multi-year quality improvement initiative involves 5 health systems, individuals living with FH, and quality improvement/implementation scientists.
Research Aim: To describe the methods and results of the FIND FH CLN.
Methods: The FIND FH CLN used a machine learning model (MLM) validated to identify individuals likely to have FH coupled with implementation/quality improvement methods to enhance patient outreach and follow-up. The MLM was run on de-identified data extracted from each system. Sites conducted chart reviews to validate the MLM output. Cycles of change were utilized to identify care gaps, engage patients in diagnostic assessment, locate improvement opportunities, and design feasible interventions. Outcomes included outreach volume, completed appointments, and number of new FH diagnoses. Summary statistics were used to compare site results. Debriefing interviews were conducted to document improvement approaches, care processes changes, and challenges and lessons learned.
Results: The 5 sites employed several methods to increase FH awareness, including educational activities to clinical teams, electronic health system-based features, and web-based information targeting clinicians and patients. Across all 5 sites, 4476 individuals were flagged by the MLM; 847 patients were contacted following MLM output review, and 209 appointments were completed (range 14-77/site), resulting in 175 new diagnoses of definite, probable, or possible FH (83.7% of all patients evaluated in appointments). Two sites have completed outreach to all patients deemed appropriate and three sites are still engaged in patient outreach (See Figure 1).
Conclusions: The FIND FH CLN produced significant increases in the proportion of patients living with FH who were identified and diagnosed, providing learnings and best practices that can be adopted by other institutions. This multifaceted Family Heart Foundation-led quality improvement initiative offers insights and methods to accelerate identification and improve care of individuals with FH as well as other under-diagnosed conditions.