Rapid identification of familial hypercholesterolemia from electronic health records

The SEARCH study

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

Background: Little is known about prevalence, awareness, and control of familial hypercholesterolemia (FH) in the United States. Objective: To address these knowledge gaps, we developed an ePhenotyping algorithm for rapid identification of FH in electronic health records (EHRs) and deployed it in the Screening Employees And Residents in the Community for Hypercholesterolemia (SEARCH) study. Methods: We queried a database of 131,000 individuals seen between 1993 and 2014 in primary care practice to identify 5992 (mean age 52 ± 13 years, 42% men) patients with low-density lipoprotein cholesterol (LDL-C) ≥190 mg/dL, triglycerides <400 mg/dL and without secondary causes of hyperlipidemia. Results: Our EHR-based algorithm ascertained the Dutch Lipid Clinic Network criteria for FH using structured data sets and natural language processing for family history and presence of FH stigmata on physical examination. Blinded expert review revealed positive and negative predictive values for the SEARCH algorithm at 94% and 97%, respectively. The algorithm identified 32 definite and 391 probable cases with an overall FH prevalence of 0.32% (1:310). Only 55% of the FH cases had a diagnosis code relevant to FH. Mean LDL-C at the time of FH ascertainment was 237 mg/dL; at follow-up, 70% (298 of 423) of patients were on lipid-lowering treatment with 80% achieving an LDL-C ≤100 mg/dL. Of treated FH patients with premature CHD, only 22% (48 of 221) achieved an LDL-C ≤70 mg/dL. Conclusions: In a primary care setting, we found the prevalence of FH to be 1:310 with low awareness and control. Further studies are needed to assess whether automated detection of FH in EHR improves patient outcomes.

Original languageEnglish (US)
JournalJournal of Clinical Lipidology
DOIs
StateAccepted/In press - Mar 4 2016

Fingerprint

Hyperlipoproteinemia Type II
Electronic Health Records
Hypercholesterolemia
LDL Cholesterol
Primary Health Care
Natural Language Processing
Lipids
Christianity
Hyperlipidemias
Physical Examination
Triglycerides
Databases

Keywords

  • Awareness
  • Control
  • EEpidemiology
  • Electronic health records
  • Electronic phenotyping
  • Familial hypercholesterolemia
  • Hypercholesterolemia
  • Informatics
  • Prevalence
  • Screening

ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism
  • Nutrition and Dietetics
  • Cardiology and Cardiovascular Medicine

Cite this

@article{42a9be9d3dbb4b4a9a440b41aa1cbe29,
title = "Rapid identification of familial hypercholesterolemia from electronic health records: The SEARCH study",
abstract = "Background: Little is known about prevalence, awareness, and control of familial hypercholesterolemia (FH) in the United States. Objective: To address these knowledge gaps, we developed an ePhenotyping algorithm for rapid identification of FH in electronic health records (EHRs) and deployed it in the Screening Employees And Residents in the Community for Hypercholesterolemia (SEARCH) study. Methods: We queried a database of 131,000 individuals seen between 1993 and 2014 in primary care practice to identify 5992 (mean age 52 ± 13 years, 42{\%} men) patients with low-density lipoprotein cholesterol (LDL-C) ≥190 mg/dL, triglycerides <400 mg/dL and without secondary causes of hyperlipidemia. Results: Our EHR-based algorithm ascertained the Dutch Lipid Clinic Network criteria for FH using structured data sets and natural language processing for family history and presence of FH stigmata on physical examination. Blinded expert review revealed positive and negative predictive values for the SEARCH algorithm at 94{\%} and 97{\%}, respectively. The algorithm identified 32 definite and 391 probable cases with an overall FH prevalence of 0.32{\%} (1:310). Only 55{\%} of the FH cases had a diagnosis code relevant to FH. Mean LDL-C at the time of FH ascertainment was 237 mg/dL; at follow-up, 70{\%} (298 of 423) of patients were on lipid-lowering treatment with 80{\%} achieving an LDL-C ≤100 mg/dL. Of treated FH patients with premature CHD, only 22{\%} (48 of 221) achieved an LDL-C ≤70 mg/dL. Conclusions: In a primary care setting, we found the prevalence of FH to be 1:310 with low awareness and control. Further studies are needed to assess whether automated detection of FH in EHR improves patient outcomes.",
keywords = "Awareness, Control, EEpidemiology, Electronic health records, Electronic phenotyping, Familial hypercholesterolemia, Hypercholesterolemia, Informatics, Prevalence, Screening",
author = "Safarova, {Maya S.} and Liu, {Hongfang D} and Kullo, {Iftikhar Jan}",
year = "2016",
month = "3",
day = "4",
doi = "10.1016/j.jacl.2016.08.001",
language = "English (US)",
journal = "Journal of Clinical Lipidology",
issn = "1933-2874",
publisher = "Elsevier BV",

}

TY - JOUR

T1 - Rapid identification of familial hypercholesterolemia from electronic health records

T2 - The SEARCH study

AU - Safarova, Maya S.

AU - Liu, Hongfang D

AU - Kullo, Iftikhar Jan

PY - 2016/3/4

Y1 - 2016/3/4

N2 - Background: Little is known about prevalence, awareness, and control of familial hypercholesterolemia (FH) in the United States. Objective: To address these knowledge gaps, we developed an ePhenotyping algorithm for rapid identification of FH in electronic health records (EHRs) and deployed it in the Screening Employees And Residents in the Community for Hypercholesterolemia (SEARCH) study. Methods: We queried a database of 131,000 individuals seen between 1993 and 2014 in primary care practice to identify 5992 (mean age 52 ± 13 years, 42% men) patients with low-density lipoprotein cholesterol (LDL-C) ≥190 mg/dL, triglycerides <400 mg/dL and without secondary causes of hyperlipidemia. Results: Our EHR-based algorithm ascertained the Dutch Lipid Clinic Network criteria for FH using structured data sets and natural language processing for family history and presence of FH stigmata on physical examination. Blinded expert review revealed positive and negative predictive values for the SEARCH algorithm at 94% and 97%, respectively. The algorithm identified 32 definite and 391 probable cases with an overall FH prevalence of 0.32% (1:310). Only 55% of the FH cases had a diagnosis code relevant to FH. Mean LDL-C at the time of FH ascertainment was 237 mg/dL; at follow-up, 70% (298 of 423) of patients were on lipid-lowering treatment with 80% achieving an LDL-C ≤100 mg/dL. Of treated FH patients with premature CHD, only 22% (48 of 221) achieved an LDL-C ≤70 mg/dL. Conclusions: In a primary care setting, we found the prevalence of FH to be 1:310 with low awareness and control. Further studies are needed to assess whether automated detection of FH in EHR improves patient outcomes.

AB - Background: Little is known about prevalence, awareness, and control of familial hypercholesterolemia (FH) in the United States. Objective: To address these knowledge gaps, we developed an ePhenotyping algorithm for rapid identification of FH in electronic health records (EHRs) and deployed it in the Screening Employees And Residents in the Community for Hypercholesterolemia (SEARCH) study. Methods: We queried a database of 131,000 individuals seen between 1993 and 2014 in primary care practice to identify 5992 (mean age 52 ± 13 years, 42% men) patients with low-density lipoprotein cholesterol (LDL-C) ≥190 mg/dL, triglycerides <400 mg/dL and without secondary causes of hyperlipidemia. Results: Our EHR-based algorithm ascertained the Dutch Lipid Clinic Network criteria for FH using structured data sets and natural language processing for family history and presence of FH stigmata on physical examination. Blinded expert review revealed positive and negative predictive values for the SEARCH algorithm at 94% and 97%, respectively. The algorithm identified 32 definite and 391 probable cases with an overall FH prevalence of 0.32% (1:310). Only 55% of the FH cases had a diagnosis code relevant to FH. Mean LDL-C at the time of FH ascertainment was 237 mg/dL; at follow-up, 70% (298 of 423) of patients were on lipid-lowering treatment with 80% achieving an LDL-C ≤100 mg/dL. Of treated FH patients with premature CHD, only 22% (48 of 221) achieved an LDL-C ≤70 mg/dL. Conclusions: In a primary care setting, we found the prevalence of FH to be 1:310 with low awareness and control. Further studies are needed to assess whether automated detection of FH in EHR improves patient outcomes.

KW - Awareness

KW - Control

KW - EEpidemiology

KW - Electronic health records

KW - Electronic phenotyping

KW - Familial hypercholesterolemia

KW - Hypercholesterolemia

KW - Informatics

KW - Prevalence

KW - Screening

UR - http://www.scopus.com/inward/record.url?scp=84994128046&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84994128046&partnerID=8YFLogxK

U2 - 10.1016/j.jacl.2016.08.001

DO - 10.1016/j.jacl.2016.08.001

M3 - Article

JO - Journal of Clinical Lipidology

JF - Journal of Clinical Lipidology

SN - 1933-2874

ER -