A Scoping Review of Electronic Health Records–Based Screening Algorithms for Familial Hypercholesterolemia

Osei, Jeffery; Razavi, Alexander C.; Otchere, Baffour; Bonful, Gracelove; Akoto, Natalie; Akyea, Ralph K.; Qureshi, Nadeem; Coronado, Fatima; Moonesinghe, Ramal; Kolor, Katherine; Mensah, George A.; Sperling, Laurence; Khoury, Muin J.

Abstract

Background
Familial hypercholesterolemia (FH) is a common genetic disorder that is strongly associated with premature cardiovascular disease. Effective diagnosis and appropriate treatment of FH can reduce cardiovascular disease risk; however, FH is underdiagnosed. Electronic health record (EHR)-based FH screening tools have been previously described to enhance the detection of FH.

Objectives
This scoping review explored the available literature on the performance and utility of existing EHR-based FH screening algorithms or tools.

Methods
We searched PubMed, CINAHL, and Embase from inception to October 2023 for relevant literature on the performance, utility, and/or implementation of EHR-based screening algorithms for FH.

Results
Of 14 screening algorithms and/or tools identified in the 27 studies included in this review, Familial Hypercholesterolemia Case Ascertainment Tool (1, 2, and ML), FIND FH algorithm, Mayo SEARCH, and TARB-Ex demonstrated the highest performance metrics for identifying patients with FH.

Conclusions
EHR-based screening tools hold great potential for improving population-level FH detection. Lack of established diagnostic criteria that can be applied across diverse populations and the lack of information about the performance, utility, and implementation of current EHR-based screening tools across diverse populations limit the current use of these tools.

Citation

Osei, J., Razavi, A. C., Otchere, B., Bonful, G., Akoto, N., Akyea, R. K., Qureshi, N., Coronado, F., Moonesinghe, R., Kolor, K., Mensah, G. A., Sperling, L., & Khoury, M. J. (2024). A Scoping Review of Electronic Health Records–Based Screening Algorithms for Familial Hypercholesterolemia. JACC: Advances, 3(12, Part 2), Article 101297. https://doi.org/10.1016/j.jacadv.2024.101297

• Journal Article Type: Article
• Acceptance Date: Sep 2, 2024
• Online Publication Date: Oct 14, 2024
• Publication Date: 2024-12
• Deposit Date: Sep 6, 2024
• Publicly Available Date: Sep 6, 2024
• Journal: JACC: Advances
• Electronic ISSN: 2772-963X
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 3
• Issue: 12, Part 2
• Article Number: 101297
• DOI: https://doi.org/10.1016/j.jacadv.2024.101297
• Keywords: familial hypercholesterolemia; electronic health record; machine learning; performance; utility
• Public URL: https://nottingham-repository.worktribe.com/output/39175218
• Publisher URL: https://www.jacc.org/doi/10.1016/j.jacadv.2024.101297