Hidden Burden of Electronic Health Record‐Identified Familial Hypercholesterolemia: Clinical Outcomes and Cost of Medical Care

Abstract

Background Familial hypercholesterolemia ( FH ), is a historically underdiagnosed, undertreated, high‐risk condition that is associated with a high burden of cardiovascular morbidity and mortality. In this study, we use a population‐based approach using electronic health record ( EHR )‐based algorithms to identify FH . We report the major adverse cardiovascular events, mortality, and cost of medical care associated with this diagnosis. Methods and Results In our 1.18 million EHR‐ eligible cohort, International Classification of Diseases, Ninth Revision ( ICD ‐9 ) code‐defined hyperlipidemia was categorized into FH and non‐ FH groups using an EHR algorithm designed using the modified Dutch Lipid Clinic Network criteria. Major adverse cardiovascular events, mortality, and cost of medical care were analyzed. A priori associated variables/confounders were used for multivariate analyses using binary logistic regression and linear regression with propensity score–based weighted methods as appropriate. EHR FH was identified in 32 613 individuals, which was 2.7% of the 1.18 million EHR cohort and 13.7% of 237 903 patients with hyperlipidemia. FH had higher rates of myocardial infarction (14.77% versus 8.33%; P <0.0001), heart failure (11.82% versus 10.50%; P <0.0001), and, after adjusting for traditional risk factors, significantly correlated to a composite major adverse cardiovascular events variable (odds ratio, 4.02; 95% CI, 3.88–4.16; P <0.0001), mortality (odds ratio, 1.20; CI, 1.15–1.26; P <0.0001), and higher total revenue per‐year (incidence rate ratio, 1.30; 95% CI, 1.28–1.33; P <0.0001). Conclusions EHR ‐based algorithms discovered a disproportionately high prevalence of FH in our medical cohort, which was associated with worse outcomes and higher costs of medical care. This data‐driven approach allows for a more precise method to identify traditionally high‐risk groups within large populations allowing for targeted prevention and therapeutic strategies.

Leveraging population‐based exome screening to impact clinical care: The evolution of variant assessment in the Geisinger MyCode research project

“…Furthermore, EHR access also enables correlation of clinically relevant results with personal and family history of disease leading to more informed clinical care. Lastly, implementation of population genomic screening in an integrated, learning healthcare system allows longitudinal analyses of outcomes data and can inform future guidance on the personal, medical, and financial utility of such programs (Buchanan et al, 2020; Haggerty et al, 2017; Hao et al, 2020; Jones et al, 2018; Patel et al, 2019; Savatt et al, 2020) and facilitate expansion beyond what most programs are reporting at this time (Martin et al, 2020; Savatt et al, 2020).…”

Genetics of Hypercholesterolemia: Comparison Between Familial Hypercholesterolemia and Hypercholesterolemia Nonrelated to LDL Receptor

“…A lower prevalence of TX has been observed in the last decades due to long-term intensive lipid-lowering therapy and the early diagnosis of FH (Benn et al, 2012;Bea et al, 2017;Berberich and Hegele, 2019). Consequently, the absence of TX defines most of the subjects with HC as "probable FH" or "possible FH" (Patel et al, 2019), decreasing the sensitivity of DLCN and Simon Broome scores for the diagnosis of FH (Cuchel et al, 2014;Trinder et al, 2020). The choice of a high value of LDL-C, above 99th percentile (>250 mg/dl), and normal values of TG is highly sensitive but not too specific for the diagnosis of FH (Civeira and International Panel on Management of Familial Hypercholesterolemia, 2004;Benn et al, 2016;Trinder et al, 2019).…”

“…Recent data delivered a higher prevalence of FH than previously documented, with a general pooled estimation in 1:250 (0.4%) (Benn et al, 2016 ; Akioyamen et al, 2017 ) accounting about 1.7–5.6% of subjects with severe HC (Benn et al, 2012 ; Khera et al, 2016 ; Trinder et al, 2020 ). On the contrary, other forms of HC comprise a larger proportion of individuals in both population-based approach studies or large samples from different genetic backgrounds: 13.7% of 1.18 million of adults in the United States (Patel et al, 2019 ), about 10% of 48,781 participants in the UK Biobank cohort study (Trinder et al, 2020 ), up to 7% of 67,019 subjects from the Danish general population study (Benn et al, 2012 ) and 6.8% of 20,485 ASCVD-free subjects belonging to 12 cohorts from different countries (Khera et al, 2016 ) ( Table 2 ).…”

“…A lower prevalence of TX has been observed in the last decades due to long-term intensive lipid-lowering therapy and the early diagnosis of FH (Benn et al, 2012 ; Bea et al, 2017 ; Berberich and Hegele, 2019 ). Consequently, the absence of TX defines most of the subjects with HC as “probable FH” or “possible FH” (Patel et al, 2019 ), decreasing the sensitivity of DLCN and Simon Broome scores for the diagnosis of FH (Cuchel et al, 2014 ; Trinder et al, 2020 ).…”

“…However, this target is not attained for the greatest proportion of HC and FH populations (Perez-Calahorra et al, 2019 ; Pérez de Isla et al, 2019 ). Furthermore, <50% of these subjects, particularly young ones, are in chronic treatment with a high-intensity statin (Benn et al, 2012 ; Bucholz et al, 2018 ; Kotseva et al, 2019 ; Patel et al, 2019 ). The addition of other cardiovascular risk factors may modulate the intensity of the treatment in the rest of subjects with moderate HC (Mach et al, 2020 ).…”