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Cost-effectiveness of intelligent Liver Function test(iLFT) for investigation of patients with abnormal liver function tests Rezaei Hemami M1, Boyd K.

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Presentation on theme: "Cost-effectiveness of intelligent Liver Function test(iLFT) for investigation of patients with abnormal liver function tests Rezaei Hemami M1, Boyd K."— Presentation transcript:

1 Cost-effectiveness of intelligent Liver Function test(iLFT) for investigation of patients with abnormal liver function tests Rezaei Hemami M1, Boyd K. A1, Inglis S. K2, Dow E3, Dillon J.F2 1University of Glasgow, Glasgow, United Kingdom, 2University of Dundee, Dundee, United Kingdom, 3NHS, Dundee, United Kingdom Institute of Health & Wellbeing Health Economics and Health Technology Assessment (HEHTA) Background Within trial economic evaluation (CEA) Liver function tests (LFT) are widely used by GPs in UK. Step wedge RCT, before / after analysis, Tayside Scotland Abnormal results from these tests(ALFTs) are common. Resource use data (GP, nurse, lab tests) ALFTs are uninvestigated further OR lengthy retesting & referral Decision tree Current practice leads to unidentified curable liver disease which could be fatal, and costs patient & health services time & resources. Incremental cost per correct diagnosis Lifetime economic evaluation (CUA) iLFT is a semi-automated liver test cascading system Markov model Maximises efficiency of requesting LFTs. Alcoholic Liver Diseases (ALD) & Non Alcoholic Fatty Liver Diseases (NAFLD) Earlier detection of potentially curable liver disease. Aim Patients with liver disease could enter in detected or non-detected states, then they followed pathway of disease Determine cost-effectiveness of iLFT compared to routine practice for evaluating ALFTs in Scotland. Costs, utilities, transitional probabilities and treatment effect, were estimated from SCALE data, expert opinion and literature. Methods Sensitivity analysis Perspective: National Health Service. Deterministic: four scenarios based on definition of normal range for ALT and patients exclusion criteria Economic evaluation alongside trial & decision model. Probabilistic: Mont Carlo simulation Fig1 long-term model Fig2 CE plan for lifetime model Primary diagnostic outcomes Scenario analyses Control N=486 iLFT N=54 Probability difference (95%CI)* N(proportion) Disease diagnosis (true positive) 120(0.25) 38(0.7) 0.45 (0.32, 0.59) No disease diagnosis (true negative) 81 (0.17) 12(0.22) 0.06 (-0.06, 0.17) Correct diagnosis (true positive & true negative) 201 (0.41) 50(0.93) 0.51 (0.43, 0.59) Scenario Arm Within trial Lifetime model Mean cost Correct diagnosis probability ICER Mean QALYs Base case Control £185 0.41 £284 £59764 8.52 iLFT dominates iLFT £327 0.93 £56544 8.54 1 All cases £137 £32032 9.71 £263 0.95 £33807 9.72 2 Alternative ALT normal range £184 0.92 £53162 8.86 £343 £50261 8.88 3 Excluding not investigated in control group £255 0.73 £400 £58952 8.60 £56059 8.62 Results Within trial: iLFT higher costs, improved diagnosis. iLFT was cost effective with an ICER of 284£. Lifetime: iLFT dominant Conclusion: iLFT is deliverable, requiring only innovative developments and adjustments to; existing laboratory hardware and software. It can reduce the number of LFT’s not rechecked/not investigated which are potential cases for fatal disease in future. This system is clearly more effective at diagnosing liver disease than the routine practice. iLFT has a higher correct diagnosis rate and cost in short-term, in lifetime model it dominates. The results were robust to PSA and different scenario Contact details: Mohsen Rezaei Hemami Acknowledgment: We would like to acknowledge the iLFT trial team and Chief Scientist Office for funding this study


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