title: A new electronic screening tool for identifying risk of familial hypercholesterolaemia in general practice.
abstract: To evaluate the performance of a new electronic screening tool (TARB-Ex) in detecting general practice patients at potential risk of familial hypercholesterolaemia (FH).
  
  
  
  Medical records for all active patients seen between 2012 and 2014 (n=3708) at a large general practice in Perth, Western Australia were retrospectively screened for potential FH risk using TARB-Ex. Electronic extracts of medical records for patients identified with potential FH risk (defined as Dutch Lipid Clinic Network Criteria (DLCNC) score ≥5) through TARB-Ex were reviewed by a general practitioner (GP) and lipid specialist. High-risk patients were recalled for clinical assessment to determine phenotypic FH diagnosis. Performance was evaluated against a manual record review by a GP in the subset of 360 patients with high blood cholesterol (cholesterol ≥7 mmol/L or low-density lipoprotein cholesterol ≥4.0 mmol/L).
  
  
  
  Thirty-two patients with DLCNC score ≥5 were identified through electronic screening compared with 22 through GP manual review. Sensitivity was 95.5% (95% CI 77.2% to 99.9%), specificity was 96.7% (95% CI 94.3% to 98.3%), negative predictive accuracy was 99.7% (95% CI 98.3% to 100%) and positive predictive accuracy was 65.6% (95% CI 46.9% to 8%). Electronic screening was completed in 10 min compared with 60 h for GP manual review. 10 of 32 patients (31%) were considered high risk and recalled for clinical assessment. Six of seven patients (86%) who attended clinical assessment were diagnosed with phenotypic FH on examination.
  
  
  
  TARB-Ex screening is a time-effective and cost-effective method of systematically identifying potential FH risk patients from general practice records for clinical follow-up.
authors: General Practice and Primary Care Research, School of Medicine, The University of Notre Dame Australia, Fremantle, Western Australia, Australia.
authors: Lakkhina
authors: L
authors: Troeung
authors: General Practice and Primary Care Research, School of Medicine, The University of Notre Dame Australia, Fremantle, Western Australia, Australia.
authors: Diane
authors: D
authors: Arnold-Reed
authors: General Practice and Primary Care Research, School of Medicine, The University of Notre Dame Australia, Fremantle, Western Australia, Australia.
authors: Wendy
authors: W
authors: Chan She Ping-Delfos
authors: Cardiometabolic Clinic, Royal Perth Hospital, Perth, Western Australia, Australia School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australia.
authors: Gerald F
authors: GF
authors: Watts
authors: Cardiometabolic Clinic, Royal Perth Hospital, Perth, Western Australia, Australia School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australia.
authors: Jing
authors: J
authors: Pang
authors: Mosman Park Medical Group, Mosman Park, Western Australia, Australia.
authors: Marija
authors: M
authors: Lugonja
authors: Institute for Health Research, The University of Notre Dame Australia, Fremantle, Western Australia, Australia.
authors: Max
authors: M
authors: Bulsara
authors: Mosman Park Medical Group, Mosman Park, Western Australia, Australia.
authors: David
authors: D
authors: Mortley
authors: General Practice and Primary Care Research, School of Medicine, The University of Notre Dame Australia, Fremantle, Western Australia, Australia Port Macquarie Base Hospital, Port Maquarie, New South Wales, Macquarie, Australia Royal North Shore Hospital, St Leonards, New South Wales, Australia.
authors: Matthew
authors: M
authors: James
authors: General Practice and Primary Care Research, School of Medicine, The University of Notre Dame Australia, Fremantle, Western Australia, Australia Mosman Park Medical Group, Mosman Park, Western Australia, Australia.
authors: Tom
authors: T
authors: Brett
mesh_terms: D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000097:blood; D002784:Cholesterol / Q000097:blood*; D008078:Cholesterol, LDL / Q000097:blood; D003362:Cost-Benefit Analysis; D057225:Data Mining / Q000191:economics; D057286:Electronic Health Records / Q000191:economics; D005260:Female; D058006:General Practice / Q000191:economics; D017048:Health Care Costs; D006801:Humans; D006938:Hyperlipoproteinemia Type II / Q000097:blood / Q000175:diagnosis* / Q000191:economics; D008297:Male; D008403:Mass Screening / Q000191:economics / Q000379:methods*; D008875:Middle Aged; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D014904:Western Australia; D055815:Young Adult
chemical_list: D015415:Biomarkers; D008078:Cholesterol, LDL; D002784:Cholesterol