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Review
. 2025 Aug 22:23:101275.
doi: 10.1016/j.ajpc.2025.101275. eCollection 2025 Sep.

Novel strategies to FIND people living with genetic dyslipidemias: The family heart foundation flag, identify, network, and deliver (FIND) familial hypercholesterolemia collaborative learning network

Shoshana H Bardach  1 , George Blike  1 , Laurence Sperling  1   2 , Kain Kim  2   3 , Benjamin W Furman  2 , David R G Kulp  2 , Shivani Lam  2 , Danny Eapen  2 , Jennifer A Orr  4 , Kerrilynn C Hennessey  5 , Mary P McGowan  1   5 , Amit Khera  6 , Martha Gulati  7   8 , Zahid Ahmad  6 , Taylor Triana  6   9 , Brian S Mittman  10 , Katherine Wilemon  1
Affiliations
Review

Novel strategies to FIND people living with genetic dyslipidemias: The family heart foundation flag, identify, network, and deliver (FIND) familial hypercholesterolemia collaborative learning network

Shoshana H Bardach et al. Am J Prev Cardiol. .

Abstract

Background: Familial Hypercholesterolemia (FH) is among the most common genetic disorders. However, most people with FH are undiagnosed and many experience preventable premature cardiovascular disease. To improve identification of FH, the Family Heart Foundation established the Flag Identify Network Deliver™ Collaborative Learning Network (FIND FH™ CLN). This multi-year quality improvement initiative involves five healthcare systems, individuals with FH, and quality improvement/implementation scientists. This manuscript describes the methods and results of the FIND FH CLN.

Methods: The FIND FH CLN leveraged a machine learning model (MLM) run on de-identified data from each healthcare system, coupled with implementation/quality improvement methods to enhance FH diagnosis. Healthcare systems were supported in identifying care gaps, engaging patients in diagnostic assessment, locating improvement opportunities, and implementing feasible interventions. Tracked outcomes included outreach volume, completed appointments, and new diagnoses of FH. Improvement approaches, care process changes, and challenges/lessons learned were recorded.

Results: Across sites, 4476 individuals were flagged by the MLM; 847 patients were contacted following output review, 209 appointments were completed, and 175 diagnoses of definite, probable, or possible FH resulted. Two sites completed outreach to all patients deemed appropriate; three sites are still engaged in outreach. FH identification was facilitated by educational activities delivered to clinical teams, development of electronic health system-based features, and availability of web-based information targeting clinicians and patients.

Conclusion: This multifaceted initiative provides insights and methods that can inform efforts to accelerate identification and improve care of individuals with FH at other institutions as well as other under-diagnosed conditions.

Keywords: Collaborative learning; Familial hypercholesterolemia; Genetic dyslipidemias; Machine learning model.

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Conflict of interest statement

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Katherine Wilemon reports financial support was provided by Amgen Inc. Jennifer Orr reports financial support was provided by United States Department of Defense. Kerrilynn Hennessey & Mary P. McGowan reports financial support was provided by Susan & Richard Levy Health Care Delivery Incubator. Martha Gulati reports a relationship with Medtronic that includes: board membership. Martha Gulati reports a relationship with Bayer Corporation that includes: board membership. Martha Gulati reports a relationship with Merck & Co Inc that includes: board membership. Zahid Ahmad reports a relationship with US Department of Defense that includes: funding grants. Zahid Ahmad reports a relationship with Ionis Pharmaceuticals Inc that includes: funding grants. Zahid Ahmad reports a relationship with National Institute of Health that includes: funding grants. Zahid Ahmad reports a relationship with Amyrt that includes:. Mary P. McGowan reports a relationship with Novartis Pharmaceuticals Corporation that includes: consulting or advisory. George Blike reports a relationship with I-PASS Institute that includes: consulting or advisory. George Blike reports a relationship with Healthcare Data Analytics Institute that includes: consulting or advisory. Danny Eapen reports a relationship with Abraham J. and Phyllis Katz Foundation that includes: funding grants. Brian S. Mittman reports a relationship with Family Heart Foundation that includes: board membership. Martha Gulati and Laurence Sperling are serving as guest editors for the special issue. Dr. Sperling and Dr. Khera are also members of the AJPC editorial board. Given their editorial roles, they had no involvement in the peer review of this article and had no access to information regarding its peer review. Full responsibility for the editorial process for this article was delegated to another journal editor. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig 1
Fig. 1
THE FIND process.
Fig 2
Fig. 2
Process Flow. FH, Familial Hypercholesterolemia.
Unlabelled image
Central Illustration. Illustration depicts FH process and outcomes. FH, Familial Hypercholesterolemia.
See this image and copyright information in PMC

References

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