Identifying Future Research Priorities Using Value of Information Analyses: Left Atrial Appendage Occlusion Devices in Atrial Fibrillation

BACKGROUND Left atrial appendage occlusion devices are cost effective for stroke prophylaxis in atrial fibrillation when compared with dabigatran or warfarin. We illustrate the use of value-of-information analyses to quantify the degree and consequences of decisional uncertainty and to identify future research priorities. METHODS AND RESULTS A microsimulation decision-analytic model compared left atrial appendage occlusion devices to dabigatran or warfarin in atrial fibrillation. Probabilistic sensitivity analysis quantified the degree of parameter uncertainty. Expected value of perfect information analyses showed the consequences of this uncertainty. Expected value of partial perfect information analyses were done on sets of input parameters (cost, utilities, and probabilities) to identify the source of the greatest uncertainty. One-way sensitivity analyses identified individual parameters for expected value of partial perfect information analyses. Population expected value of perfect information and expected value of partial perfect information provided an upper bound on the cost of future research. Substantial uncertainty was identified, with left atrial appendage occlusion devices being preferred in only 47% of simulations. The expected value of perfect information was $8542 per patient and $227.3 million at a population level. The expected value of partial perfect information for the set of probability parameters represented the most important source of uncertainty, at $6875. Identified in 1-way sensitivity analyses, the expected value of partial perfect information for the odds ratio for stroke with left atrial appendage occlusion compared with warfarin was calculated at $7312 per patient or $194.5 million at a population level. CONCLUSION The relative efficacy of stroke reduction with left atrial appendage occlusion devices in relation to warfarin is an important source of uncertainty. Improving estimates of this parameter should be the priority for future research in this area.