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Cost-utility Analysis of Searching Electronic Health Records and Cascade Testing to Identify and Diagnose Familial Hypercholesterolaemia in England and Wales

Overview
Journal Atherosclerosis
Publisher Elsevier
Date 2018 Jun 8
PMID 29879685
Citations 11
Authors
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Abstract

Background And Aims: The cost effectiveness of cascade testing for familial hypercholesterolaemia (FH) is well recognised. Less clear is the cost effectiveness of FH screening when it includes case identification strategies that incorporate routinely available data from primary and secondary care electronic health records.

Methods: Nine strategies were compared, all using cascade testing in combination with different index case approaches (primary care identification, secondary care identification, and clinical assessment using the Simon Broome (SB) or Dutch Lipid Clinic Network (DLCN) criteria). A decision analytic model was informed by three systematic literature reviews and expert advice provided by a NICE Guideline Committee.

Results: The model found that the addition of primary care case identification by database search for patients with recorded total cholesterol >9.3 mmol/L was more cost effective than cascade testing alone. The incremental cost-effectiveness ratio (ICER) of clinical assessment using the DLCN criteria was £3254 per quality-adjusted life year (QALY) compared with case-finding with no genetic testing. The ICER of clinical assessment using the SB criteria was £13,365 per QALY (compared with primary care identification using the DLCN criteria), indicating that the SB criteria was preferred because it achieved additional health benefits at an acceptable cost. Secondary care identification, with either the SB or DLCN criteria, was not cost effective, alone (dominated and dominated respectively) or combined with primary care identification (£63, 514 per QALY, and £82,388 per QALY respectively).

Conclusions: Searching primary care databases for people at high risk of FH followed by cascade testing is likely to be cost-effective.

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