Decision analytic model of the diagnostic pathways for patients with suspected non-alcoholic fatty liver disease using non-invasive transient elastography and multiparametric magnetic resonance imaging.

OBJECTIVES: The mortality associated with liver disease continues to increase, despite the improvements implemented in the UK healthcare as does the prevalence of non-alcoholic fatty liver disease (NAFLD), given the escalating prevalence of obesity. The currently available methods to assess and monitor the stage of liver disease present several limitations. Recently, multiparametric MRI has been developed to address these limitations. The aim of this study is to develop a decision analytic model for patients with suspected NAFLD, to investigate the effect of adding multiparametric MRI to the diagnostic pathway. PERSPECTIVE: The model takes the perspective of the UK National Health Service (NHS) as the service provider. METHODS: A simple decision-tree model was developed to compare the costs associated with 3 diagnostic pathways for NAFLD that use non-invasive techniques. First, using transient elastography alone; second, using multiparametric MRI as an adjunct to transient elastography and third, multiparametric MRI alone. The model was built to capture these clinical pathways, and used to compare the expected diagnostic outcomes and costs associated with each. RESULTS: The use of multiparametric MRI as an adjunct to transient elastography, while increasing screening costs, is predicted to reduce the number of liver biopsies required by about 66%. Used as the sole diagnostic scan, there remains an expected 16% reduction in the number of biopsies required. There is a small drop in the overall diagnostic accuracy, as in the current model, liver biopsy is presumed to give a definitive diagnosis. CONCLUSIONS: The inclusion of multiparametric MRI, either as an adjunct to or replacement of transient elastography, in the diagnostic pathway of NAFLD may lead to cost savings for the NHS if the model presumptions hold. Further high-quality clinical evidence and cost data are required to test the model's predictions.

Protocol for evaluation of the cost-effectiveness of ePrescribing systems and candidate prototype for other related health information technologies.

BACKGROUND: This protocol concerns the assessment of cost-effectiveness of hospital health information technology (HIT) in four hospitals. Two of these hospitals are acquiring ePrescribing systems incorporating extensive decision support, while the other two will implement systems incorporating more basic clinical algorithms. Implementation of an ePrescribing system will have diffuse effects over myriad clinical processes, so the protocol has to deal with a large amount of information collected at various 'levels' across the system. METHODS/DESIGN: The method we propose is use of Bayesian ideas as a philosophical guide.Assessment of cost-effectiveness requires a number of parameters in order to measure incremental cost utility or benefit - the effectiveness of the intervention in reducing frequency of preventable adverse events; utilities for these adverse events; costs of HIT systems; and cost consequences of adverse events averted. There is no single end-point that adequately and unproblematically captures the effectiveness of the intervention; we therefore plan to observe changes in error rates and adverse events in four error categories (death, permanent disability, moderate disability, minimal effect). For each category we will elicit and pool subjective probability densities from experts for reductions in adverse events, resulting from deployment of the intervention in a hospital with extensive decision support. The experts will have been briefed with quantitative and qualitative data from the study and external data sources prior to elicitation. Following this, there will be a process of deliberative dialogues so that experts can "re-calibrate" their subjective probability estimates. The consolidated densities assembled from the repeat elicitation exercise will then be used to populate a health economic model, along with salient utilities. The credible limits from these densities can define thresholds for sensitivity analyses. DISCUSSION: The protocol we present here was designed for evaluation of ePrescribing systems. However, the methodology we propose could be used whenever research cannot provide a direct and unbiased measure of comparative effectiveness.