Figure 5: Base-case cost-effectiveness plane showing incremental costs and QALYs of each diagnostic strategy Chronic Heart Failure Diagnosing heart failure The disaggregated costs and QALYs from the probabilistic base case analysis are summarised inTable 17, Table 18 and Table 19 below. Table 17: Breakdown of diagnostic costs Diagnostic strategy Mean cost per patient to diagnose Mean cost of echocardiography and specialist clinical assessment per patient Heart failure COPD Myocaridal ischaemia Echo all 106 309 77 235 Table 18: Breakdown of management costs Diagnostic strategy Heart failure COPD Myocardial ischaemia Echo all 379 651 36 Mean QALYs Mean cost Echo all ICER = 5,496 Chronic Heart Failure Diagnosing heart failure Diagnostic strategy Heart failure COPD Myocardial ischaemia Table 19: Breakdown of QALYs Diagnostic strategy Heart failure population Non-heart failure population Multiple sensitivity analyses were undertaken on the base case analysis including adjusting the proportion of HF-REF patients, extending the time to representation to the GP for false negatives, the prognostic differences for those with NT-proBNP levels above and below 400pg/ml, the composition of other conditions in the non-heart failure population, and the cost of NT-proBNP test. None of these led to a change in the optimal strategy. In addition, two scenario analyses usingalternative diagnostic accuracy study data from Verdu et al. 2012 and Zaphiriou et al. 2005 were undertaken. It was considered important that these were also run probabilistically. However, when applying the ordinal logistic regression to the Verdu study data, the mean specificity values did not match the original study values. This was thought to be due to the fact that both 280pg/ml and 125pg/ml have a sensitivity of 1.00 and don t follow an order as such. Therefore the Verdu study was run both probabilistically (using the ordinal logistic regression model data) and deterministically (using the reported study data). 