Alistair W Vickery1, Jackie Ryan2, Jing Pang2, Jacquie Garton-Smith3, Gerald F Watts2. 1. School of Primary, Aboriginal and Rural Health Care, University of Western Australia, Perth, WA, Australia. Electronic address: Alistair.vickery@uwa.edu.au. 2. Lipid Disorders Clinic, Cardiovascular Medicine, Royal Perth Hospital, School of Medicine and Pharmacology, University of Western Australia, Perth, WA, Australia. 3. Cardiovascular Health Network, Royal Perth Hospital, Perth WA, Australia.
Abstract
BACKGROUND: Familial hypercholesterolaemia (FH) is a common autosomal co-dominant condition that causes premature cardiovascular disease. Awareness of FH is poor and only 10-15% of the affected population is identified. Electronic health records provide an opportunity to increase detection and awareness in general practice OBJECTIVE: To determine whether a simple electronic extraction tool can increase detection of FH in general practice. METHOD: An extraction tool applied to general practice electronic health records (EHR) to screen for FH, total cholesterol and low density lipoprotein cholesterol (LDL-c) levels in association with entered diagnostic criteria and demographic data in five general practices. RESULTS: Of 157,290 active patients examined, 0.7% (n=1081) had an LDL-c>5.0 mmol/L representing 1 in 146 of active patients. An additional 0.8% (n=1276) patients were at possible risk of FH. Of those with an LDL-c>5.0 mmol/L 43.7% of patients had no record of being prescribed statins. Twenty patients (0.013%) had a clinical diagnosis of FH entered in the EHR. CONCLUSIONS: Patients at high risk of FH can be identified by a simple electronic screening method in general practice. Clinical data entry is variable in general practice. Targeted screening enables clinical assessment of patients at risk of cardiovascular disease and using the DLCNS will enable primary care to increase identification of FH. Approximately one in five patients extracted using this method, are likely to have phenotypically probable FH, making it a useful screening tool.
BACKGROUND:Familial hypercholesterolaemia (FH) is a common autosomal co-dominant condition that causes premature cardiovascular disease. Awareness of FH is poor and only 10-15% of the affected population is identified. Electronic health records provide an opportunity to increase detection and awareness in general practice OBJECTIVE: To determine whether a simple electronic extraction tool can increase detection of FH in general practice. METHOD: An extraction tool applied to general practice electronic health records (EHR) to screen for FH, total cholesterol and low density lipoprotein cholesterol (LDL-c) levels in association with entered diagnostic criteria and demographic data in five general practices. RESULTS: Of 157,290 active patients examined, 0.7% (n=1081) had an LDL-c>5.0 mmol/L representing 1 in 146 of active patients. An additional 0.8% (n=1276) patients were at possible risk of FH. Of those with an LDL-c>5.0 mmol/L 43.7% of patients had no record of being prescribed statins. Twenty patients (0.013%) had a clinical diagnosis of FH entered in the EHR. CONCLUSIONS:Patients at high risk of FH can be identified by a simple electronic screening method in general practice. Clinical data entry is variable in general practice. Targeted screening enables clinical assessment of patients at risk of cardiovascular disease and using the DLCNS will enable primary care to increase identification of FH. Approximately one in five patients extracted using this method, are likely to have phenotypically probable FH, making it a useful screening tool.
Authors: Nadeem Qureshi; Maria Luisa R Da Silva; Hasidah Abdul-Hamid; Stephen F Weng; Joe Kai; Jo Leonardi-Bee Journal: Cochrane Database Syst Rev Date: 2021-10-07
Authors: Katherine E Mues; Alina N Bogdanov; Keri L Monda; Larisa Yedigarova; Alexander Liede; Lee Kallenbach Journal: Clin Epidemiol Date: 2018-11-15 Impact factor: 4.790
Authors: Alex Kitsos; Gregory M Peterson; Matthew D Jose; Masuma Akter Khanam; Ronald L Castelino; Jan C Radford Journal: J Prim Care Community Health Date: 2019 Jan-Dec
Authors: Leo E Akioyamen; Jacques Genest; Shubham D Shan; Rachel L Reel; Jordan M Albaum; Anna Chu; Jack V Tu Journal: BMJ Open Date: 2017-09-01 Impact factor: 2.692
Authors: Ralph K Akyea; Nadeem Qureshi; Joe Kai; Simon de Lusignan; Julian Sherlock; Christopher McGee; Stephen Weng Journal: BJGP Open Date: 2020-12-15