In the beginning of this series, you learned why to do ceas and how to compare net costs to health outcomes.Then you learned about dalys and qalys, and how to present cea results the base case.In this segment, cea sensitivity analyses, we show you how to quantify the importance of uncertainty in your analysis.Ceas have lots of uncertainty.There may be dozens of input variables affecting your estimates of cost and dalys, if the model is of typical complexity.Each input has uncertainty.This may be formal confidence bounds, for example hiv incidence of 1.5 per hundred personyears,.
95 confidence interval 1.1 to 2.0 or differences in estimates across studies or a lack of relevant formal studies, forcing reliance on expert opinion.This uncertainty in inputs can lead to large uncertainty in cea results.Sensitivity analyses are ceas version of 95 confidence intervals in empirical studies.Welldesigned sensitivity analyses deal systematically with this uncertainty.Each input is considered in isolation, and in combination with other inputs.Sensitivity analyses can convince audiences that results are robust that is, that the same basic conclusion holds despite uncertainty in the precise numerical findings.Or, in contrast, that results depend on the.
Value of certain inputs.Sensitivity analyses can show that high profile uncertainties such as intervention effectiveness or the lifetime costs of treating a disease, which many readers worry about may not affect findings significantly.In sum, sensitivity analyses are mandatory.But they're also interesting.And fun.Here s an efficient and fun way to summarize oneway sensitivity analyses.It's called a tornado diagram, because of the shape.Each horizontal bar indicates the uncertainty in the icer associated with uncertainty in that input.A longer bar means more uncertainty.Thus, for this analysis of gestational diabetes screening and treatment, the input value that.
Most affects results is the cost of postpartum care at the top, spanning $900 to $2,400 per daly averted and the input value that least affects results is the cost of type 2 diabetes in the children of women with gestational diabetes at the bottom, spanning $1,600 to $1,680 per daly averted.Multiway sensitivity analyses are the perfect way to summarize the aggregate effect of uncertainty in all inputs.A monte carlo simulation, as shown here, calculates the distribution of results from many iterations of the model in this example, 20,000 iterations.The histogram shows the frequency of narrow ranges of results.
It indicates that the most common result is very similar to the base case of $1,640, with 90 of simulations between $400 and $4,000.23.5 1sensitivity analyses do more than just quantify the impact of uncertainty in model input values.They help the analyst understand a model that can get pretty complex.If results change in predictable ways as input values are widely varied, this is evidence of the model's sound structure.Conversely, unexpected patterns may reveal technical errors in the model.Occasionally, such unexpected results uncover interesting dynamics in the.
Cea.One example of such an interesting dynamic from our work is when the cost of antiretroviral therapy for hiv didn't affect the results because it appeared appropriately in two offsetting parts of the model.Sensitivity analyses also bolster acceptance of the cea.They demonstrate transparency to the reader, and thus build trust in the model's functioning and findings.Indeed, and counter to my original intuition, documenting uncertainty via sensitivity analyses tends to foster the audience's emphasis on the base case.With sas, the reader can think only, how certain are these results with sas, the.
Distraction of unexplored uncertainty is removed, and the reader tends to return to a focus on the base case.Of course, some sas reveal massive uncertainty due to a poorly understood input, and that becomes the main finding.But most ceas have a solid trend in results, and once sas demonstrate that, the uncertainty slips into the background.That's all for sensitivity analyses.There's lots more to learn, and eventually to do typically to 13 of total cea effort is needed to design, conduct, interpret, and respond to sas.Up next timing in ceas.
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