Generalisability of economic analyses.

Abstract

As healthcare expenditures account for a greater share of the economy throughout the developed world, it has become increasingly recognised that economic analyses of healthcare interventions are important. Common economic analyses in healthcare include cost analyses, cost-benefit analyses, and cost-effectiveness analyses. A cost analysis examines the costs of the interventions and the downstream costs from the treatment as well, but does not include outcomes. A cost-benefit analysis assumes that the outcomes are similar, and converts all treatments and outcomes into costs. A cost-effectiveness analysis provides the results as an incremental cost-effectiveness ratio (ICER). The ICER has incremental costs in the numerator divided by incremental outcome differences in the denominator. The gold standard for a cost-effectiveness analysis is to utilise quality-adjusted life years in the denominator, which allows CEA ratios to be compared between different clinical settings. An ICER that has a reduction in costs in the numerator and improved outcomes in the denominator is deemed a dominant strategy. The authors describe an economic analysis that appears to be just such a dominant strategy, using placental growth factor (PlGF) as a way to augment the diagnosis of pre-eclampsia (Duhig et al. BJOG 2019;126:1390–8). The take home from the abstract is that there is a cost saving of £149. However, in the body of the manuscript, the use of PlGF is only cost saving in 56% of the iterations of the Monte Carlo simulation model that was run. This is akin to having a nonsignificant P-value when two clinical outcomes are compared. We usually say that such outcomes are not different with such a statistical test. I commend the authors for conducting Monte Carlo simulations, as too often they are not conducted for cost-effectiveness analyses, but it is important to incorporate the probabilistic results in the topline communication. Even though not statistically significant, why would PlGF lead to a reduction in costs? From the original trial, it appeared that the use of the test led to a more rapid diagnosis of pre-eclampsia (2 versus 4 days) and the test was used to triage whether women had their evaluation inpatient or outpatient. Therein lies the greatest source of cost saving from the test. However, for generalisability, would clinicians in different settings be willing to use the PlGF test in this fashion? For those who routinely evaluate most potential pre-eclampsia patients without severe features as outpatients already, there would seemingly be no potential for cost savings. When clinicians are unwilling to use the test to send patients out, given that those with a negative PlGF test still had a 12% chance of having pre-eclampsia, it may not lead to a savings either. Thus, when considering an economic analysis, the devil is in the detail; consideration of the costs included and how they apply to different clinical environments and practices is imperative. Honestly, in the end, for the majority of women, we have relatively inexpensive screening and diagnostic tests for pre-eclampsia (blood pressure checks and urinalysis). Thus, I am not exactly sure how this PlGF test would improve on the diagnostic approaches for most patients. However, there may be some sub-populations where we are more challenged (e.g. those with chronic hypertension) for which this test may lead to clearer diagnoses; at the very least it does not appear to lead to substantially greater costs. None declared. A completed disclosure of interests form is available to view online as supporting information. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.