The characteristics of patients with possible familial hypercholesterolemia—screening a large payer/provider healthcare delivery system

Author:

Elis A1,Leventer-Roberts M2,Bachrach A2,Lieberman N3,Durst R4,Knobler H5,Balicer R2

Affiliation:

1. Department of Internal Medicine, Beilinson Hospital, Rabin Medical Center, Petah Tikva, Israel

2. Clalit Research Institute

3. Medical Policy Division, Clalit Health Services, Tel Aviv, Israel

4. The Center for Research Prevention and Treatment of Atherosclerosis, Hadassah Hebrew University Medical Center, Jerusalem, Israel

5. The Institute of Diabetes, Endocrinology, and Metabolism, Kaplan Medical Center, Rehovot, Israel

Abstract

Abstract Background Familial hypercholesterolemia (FH) is an under-diagnosed condition. Aim We applied standard laboratory criteria across a large longitudinal electronic medical record database to describe cross-sectional population with possible FH. Methods A cross-sectional study of Clalit Health Services members. Subjects who met the General Population MED-PED laboratory criteria, excluding: age <10 years, documentation of thyroid, liver, biliary or autoimmune diseases, a history of chronic kidney disease stage 3 or greater, the presence of urine protein >300 mg/l, HDL-C>80 mg/dl, active malignancy or pregnancy at the time of testing were considered possible FH. Demographic and clinical characteristics are described at time of diagnosis and at a single index date following diagnosis to estimate the burden on the healthcare system. The patient population is also compared to the general population. Results The study cohort included 12 494 subjects with out of over 4.5 million members of Clalit Health Services. The estimated prevalence of FH in Israel was found to be 1:285. These patients are notably positive for, and have a family history of, cardiovascular disease and risk factors. For most of them the LDL-C levels are not controlled, and only a quarter of them are medically treated. Conclusions By using the modified MED-PED criteria in a large electronic database, patients with possible FH can be identified enabling early intervention and treatment.

Publisher

Oxford University Press (OUP)

Subject

General Medicine

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