much more willing to risk harm by not providing something than by doing so. Patients are not happier to die of a clot than bleeding, he said. Some of this bias results from concerns about liability, but the harms can be equivalent. “We need to be honest about assessing the whole landscape,” he said.
Also, the chain of evidence between a decision and an outcome can be long and complex, the participant continued. Most anticoagulation outcomes are secondary outcomes, such as time in range or time to stable dosing as opposed to direct outcomes of bleeding and clotting. The question is how much confidence there is that those secondary outcomes are predictive of primary outcomes. Intermediate end points such as genetic testing may be able to help bolster that confidence by assessing risk.
The participant also noted that West’s family history already captured the risk of thrombophilia regardless of the status of his Factor V Leiden gene. Not using this family history represents an opportunity cost that needs to be recognized. “If we are spending our money on genomics, then that means we are ignoring other things. And in the realm of anticoagulation, if we focus on genomics, are we ignoring the opportunities to do other things like clinical decision support with guided dosing,” he asked. Similarly, is genotyping misplaced in urban settings where there are anticoagulation clinics?
Decision points can differ on the basis of the available evidence, Grosse said. For example, considering an option has a lower threshold of evidence than deciding to choose an option. Grosse also noted that clinicians will continue to make judgments about treatments for their individual patients regardless of standards that are set across a population, given the heterogeneity of preferences and treatment effects. “It is not one-size-fits-all.”
Ramsey said that the best approach would be to have a cost-effectiveness study for the average population and then to modify those results on the basis of the characteristics of each patient. A system can also be structured to encourage the more cost-effective approaches and discourage the cost-ineffective practices, with flexibility for individual decisions on the basis of patient characteristics.
Veenstra said that changing clinical management poses its own risks. For example, monitoring of phenotypes, as with INR measurements, works fairly well, and genomic-based treatment decisions need to be compared with that standard.
Finally, Ramsey mentioned that patients may not fully comprehend the impact of receiving a test result. They may test positive and be relieved that the condition was caught in time and they can be treated or they may test negative and feel they do not have to worry about developing a genetic condition. But patients tend not to learn about the untoward effects that a test can have, such as distress or anxiety to patients and their families, the development of a false sense of security regarding risk of disease, results