Intelligent Liver Function Testing (iLFT): A trial of automated diagnosis and staging of liver disease in Primary Care

Abstract Background Liver function tests (LFTs) are frequently requested blood tests which may indicate liver disease. LFTs are commonly abnormal, the causes of which can be complex and frequently under investigated. This can lead to missed opportunities to diagnose and treat liver disease at an early stage. We developed an automated investigation algorithm, which would maximise early diagnosis of liver related diseases. Our aim was to determine whether this new pathway of care, Intelligent Liver Function testing (iLFT) increased diagnosis of liver disease and was cost-effective. Methods We developed an automated system that further investigated abnormal LFTs on initial testing samples to generate a probable diagnosis and management plan. We integrated an automated investigation algorithm into the laboratory management system, based on minimal diagnostic criteria, liver fibrosis estimation, and reflex testing for causes of liver disease. This algorithm then generated a diagnosis and/or management plan. A stepped-wedged trial design was utilised to compare LFT outcomes in General Practices in the 6 months before and after introduction of the iLFT system. Diagnostic outcomes were collated and compared. Results Using iLFT, the diagnosis of liver disease was increased by 43%. It was cost-effective with a low initial incremental cost-effectiveness ratio (ICER) of £284 per correct diagnosis, and a saving to the NHS of £3,216 per patient lifetime. Conclusions iLFT increases liver diagnosis, improves quality of care, and is highly cost-effective. This can be achieved with minor changes to working practices and exploitation of functionality existing within modern laboratory diagnostics systems. Lay Summary There is a growing epidemic of advanced liver disease, this could be offset by early detection and management. Checking liver blood tests (LFTs) should be an opportunity diagnose liver problems, but abnormal results are often incompletely investigated. In this study we were able to substantially increase the diagnostic yield of the abnormal LFTs using the automated iLFT system. With the addition of referral recommendations and management plans, this strategy provides optimum investigation and management of LFTs and is cost saving to the NHS.