EVALUATING THE COST-EFFECTIVENESS OF MONITORING TESTS
Method(s): We generalize on the existing literature for modelling the cost-effectiveness of monitoring tests in three ways: 1. We allow the test to be administered repeatedly for more than two periods; 2. In addition to the “monitoring testing” strategy, we incorporate a “wait” strategy in which both test and treatment are skipped, as well as a “treat” strategy in which patients are treated without testing; and 3. We adopt a global optimization approach where optimal decisions for each period of a monitoring regime are determined depending on the proceeding periods. We illustrate with a numerical example using data from a Ca125 test for monitoring ovarian cancer.
Result(s): The results from this study show that the net health benefits from the monitoring test and the treatment will be maximized by finding globally optimal solutions in each period in comparison to the following two alternatives: Locally optimal solutions, where optimal test cut-offs in each period are determined independent of the proceeding periods and conventionally optimal solutions, where a fixed cut-off is chosen for all periods.
Conclusion(s): Optimal test cut-offs in a monitoring regime are population case-mix and health system specific and should not be assumed to be portable. To assume portability is to reduce the population health impact (value) of test technologies.