Closing the gap: Identification and management of familial hypercholesterolemia in an integrated healthcare delivery system

Birnbaum, Richard; Horton, Brandon; Gidding, Samuel S.; Brenman, Leslie Manace; Macapinlac, Brian A.; Avins, Andrew L.

doi:10.1016/j.jacl.2021.01.008

Cited by 18 publications

(14 citation statements)

References 35 publications

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“…The SB criteria predict the risk of an individual having FH based on clinical and genetic factors and family history (Supplementary Table S2). MEDPED determines the probability of a patient having FH based on age, family history, and total cholesterol levels (Birnbaum et al, 2021) (Supplementary Table S3).…”

Section: Diagnostic Criteria For Familial Hypercholesterolemiamentioning

confidence: 99%

Familial Hypercholesterolemia Prevalence Among Ethnicities—Systematic Review and Meta-Analysis

2022

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Background: Heterozygous familial hypercholesterolemia (FH) is a common genetic disorder leading to premature cardiovascular disease and death as a result of lifelong high plasma low-density lipoprotein cholesterol levels, if not treated early in life. The prevalence of FH varies between countries because of founder effects, use of different diagnostic criteria, and screening strategies. However, little is known about differences in FH prevalence according to ethnicity. We aimed to investigate the ethnic distribution of FH in diverse populations and estimate the prevalence of FH according to ethnicity.Methods: We performed a systematic review and meta-analysis, searching PubMed and Web of Science for studies presenting data on the prevalence of heterozygous FH among different ethnicities in non-founder populations. Studies with more than 100 individuals, relevant data on prevalence, ethnicity, and using the Dutch Lipid Clinical Network Criteria, Simon Broome, Making Early Diagnosis Prevents Early Death, genetic screening, or comparable diagnostic criteria were considered eligible for inclusion.Results: Eleven general population studies and two patient studies were included in a systematic review and 11 general population studies in a random-effects meta-analysis. The overall pooled FH prevalence was 0.33% or 1:303 in 1,169,879 individuals (95% confidence interval: 0.26–0:40%; 1:385–1:250). Included studies presented data on six ethnicities: black, Latino, white, Asian, brown, and mixed/other. Pooled prevalence was estimated for each group. The highest prevalence observed was 0.52% or 1:192 among blacks (0.34–0.69%; 1:294–1:145) and 0.48% or 1:208 among browns (0.31–0.74%; 1:323–1:135) while the lowest pooled prevalence was 0.25% or 1:400 among Asians (0.15–0.35; 1:500–1:286). The prevalence was 0.37% or 1:270 among Latino (0.24–0.69%; 1:417–1:145), 0.31% or 1:323 among white (0.24–0.41%; 1:417–1:244), and 0.32% or 1:313 among mixed/other individuals (0.13–0.52%; 1:769–1:192).Conclusion: The estimated FH prevalence displays a variation across ethnicity, ranging from 0.25% (1:400) to 0.52% (1:192), with the highest prevalence seen among the black and brown and the lowest among the Asian individuals. The differences observed suggest that targeted screening among subpopulations may increase the identification of cases and thus the opportunity for prevention.

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Section: Diagnostic Criteria For Familial Hypercholesterolemiamentioning

confidence: 99%

Familial Hypercholesterolemia Prevalence Among Ethnicities—Systematic Review and Meta-Analysis

2022

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“…Four studies implemented the existing clinical diagnostic criteria into their healthcare system electronic health records (EHRs) as a screening tool to identify previously unrecognized individuals with FH. Similar rates of individuals requiring additional diagnostic screening for FH were found: 1 in 245 (7468/1 831 658) met the Make Early Diagnoses Prevent Early Deaths (MEDPED) criteria [20], 1 in 150 (303/45 123) met the Simon Broome (SB) Criteria [21], and 1 in 183 (269/49 321) [21] and 1 in 119 (351/41 937) [22] met the Dutch Lipid Clinic Network Criteria (DLCN). The screening positive rate for FH was higher, 1 in 5 (84/469), when the DLCN criteria were applied to EHRs of those with known severe hypercholesterolemia [23].…”

Section: Develop and Organize Quality Monitoring Systemsmentioning

confidence: 60%

Applying implementation science to improve care for familial hypercholesterolemia

Jones¹,

Brownson

Williams³

2021

Current Opinion in Endocrinology, Diabetes &Amp; Obesity

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Purpose of reviewImproving care of individuals with familial hypercholesteremia (FH) is reliant on the synthesis of evidence-based guidelines and their subsequent implementation into clinical care. This review describes implementation strategies, defined as methods to improve translation of evidence into FH care, that have been mapped to strategies from the Expert Recommendations for Implementing Change (ERIC) compilation.Recent findingsA search using the term ‘familial hypercholesterolemia’ returned 1350 articles from November 2018 to July 2021. Among these, there were 153 articles related to improving FH care; 1156 were excluded and the remaining 37 were mapped to the ERIC compilation of strategies: assess for readiness and identify barriers and facilitators [9], develop and organize quality monitoring systems [14], create new clinical teams [2], facilitate relay of clinical data to providers [4], and involve patients and family members [8]. There were only 8 of 37 studies that utilized an implementation science theory, model, or framework and two that explicitly addressed health disparities or equity.SummaryThe mapping of the studies to implementation strategies from the ERIC compilation provides a framework for organizing current strategies to improve FH care. This study identifies potential areas for the development of implementation strategies to target unaddressed aspects of FH care.

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“…There are a variety of reasons for the underdiagnosis of FH 19 ; current work in the field is focused on using automated methods to identify individuals with FH by combining various data sets including clinical, claims, and genetic data. [20][21][22] However, after the return of the genomic risk result for FH, clinicians documented the FH diagnosis (International Classification of Diseases, Tenth Revision, code E78.01) in 29% of their participants, which, while an improvement, still means over two-thirds do not have the diagnosis documented in the electronic health record. Further exploration of clinician reluctance to modify the problem list, a key resource for care coordination, is warranted.…”

Section: Discussionmentioning

confidence: 99%

Impact of a Population Genomic Screening Program on Health Behaviors Related to Familial Hypercholesterolemia Risk Reduction

Jones

Chen

Hassen

et al. 2022

Circ: Genomic and Precision Medicine

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BACKGROUND: Limited information is available regarding clinician and participant behaviors after disclosure of genomic risk variants for familial hypercholesterolemia (FH) from a population genomic screening program. METHODS: We conducted a retrospective cohort study of MyCode participants with an FH risk variant beginning 2 years before disclosure until January 16, 2019. We analyzed lipid-lowering prescriptions (clinician behavior), medication adherence (participant behavior), and LDL (low-density lipoprotein) cholesterol levels (health outcome impact) pre- and post-disclosure. Data were collected from electronic health records and claims. RESULTS: The cohort included 96 participants of mean age 57 (22–90) years with median follow-up of 14 (range, 3–39) months. Most (90%) had a hypercholesterolemia diagnosis but no specific FH diagnosis before disclosure; 29% had an FH diagnosis post-disclosure. After disclosure, clinicians made 36 prescription changes in 38% of participants, mostly in participants who did not achieve LDL cholesterol goals pre-disclosure (81%). However, clinicians wrote prescriptions for fewer participants post-disclosure (71/96, 74.0%) compared with pre-disclosure (81/96, 84.4%); side effects were documented for most discontinued prescriptions (23/25, 92%). Among the 16 participants with claims data, medication adherence improved (proportion of days covered pre-disclosure of 70% [SD, 24.7%] to post-disclosure of 79.1% [SD, 27.3%]; P =0.05). Among the 52 (54%) participants with LDL cholesterol values both before and after disclosure, average LDL cholesterol decreased from 147 to 132 mg/dL ( P =0.003). CONCLUSIONS: Despite disclosure of an FH risk variant, nonprescribing and nonadherence to lipid-lowering therapy remained high. However, when clinicians intensified medication regimens and participants adhered to medications, lipid levels decreased.

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Closing the gap: Identification and management of familial hypercholesterolemia in an integrated healthcare delivery system

Cited by 18 publications

References 35 publications

Familial Hypercholesterolemia Prevalence Among Ethnicities—Systematic Review and Meta-Analysis

Familial Hypercholesterolemia Prevalence Among Ethnicities—Systematic Review and Meta-Analysis

Applying implementation science to improve care for familial hypercholesterolemia

Impact of a Population Genomic Screening Program on Health Behaviors Related to Familial Hypercholesterolemia Risk Reduction

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