In the clinical trial system, and our broader healthcare system, analysis of failure is not only rare, but has not evolved into a critical component of analysis. We have heard this from many people we have talked to, and in conversations happening in medicine. In a recent podcast with Ezra Klein, Atul Gawande talks about how failure in medicine should be reduced in the modern age because we know more, but we aren’t evaluating and implementing our knowledge and experience into practice. Ironically for us, if you remember our thoughts on the Atul Gawande in clinical trials, he also describes “scientific” trials as the way he is making sure soluenlightenedtions are implementable towards improving patient outcomes. The gold standard is being used to help understand failure!
Think back to the last time there was a plane crash, or a nuclear meltdown, or a major economic crash. Think of something less drastic, but just as catastrophic: the hole in the ozone layer, a weakening economy, or even a sports team that might not have won for a while. Society’s first reaction in situations like these is to understand why, and then take steps to make sure it doesn’t happen again. Luckily, in these systems, we have data, analysis, and even science built up to help understand why these failures happened. These details exist throughout the structure of the system; from the smallest scale of components in an airplane or nuclear reactor, to airplane navigation algorithms and electric grid network models, we have methodologies and processes in place to both prevent and understand failure. Not only that, in these systems, failure is a part of history, and learning from failure is not only mandatory but celebrated. Even in our personal lives, we are told that everyone fails, and the most enlightened ones eventually learn from it.
And that might be an insight that can really help us towards redefining the goals of the clinical trials system within the healthcare system. Rob Califf has said before that one of the biggest things the clinical trials system does is generate evidence for new treatments. But it also generates evidence for existing treatments, and it has the structure which could also be used to understand failure in the broader healthcare system. Often a faltering system can be rejuvenated by finding a new role for it in the broader context. Legacy computer systems, for example, are often the safer from cyber-attacks as they are older closed systems, while hackers prefer to go after open modern systems that are popular. They are often “re-faced” with modern interfaces to keep their old advantages and also be used for modern needs. This has in fact been the de-facto solution for many legacy systems, and the pathway is something the clinical trials system might be able to learn from. Atul Gawande recognizes the strengths of the current clinical trials system in its robust science, minimization of risk, and ability to prove causality. We can build on these strengths, and evolve the system to satisfy modern needs, and also solve major healthcare problems along the way. By analyzing failure, the clinical trials system would not only become more efficient, but it could also revolutionize the broader healthcare system.
Over the next few weeks, we will be diving into looking at learning from failure from various parts of the system, and how the CT system can contribute to learning from the failures of the healthcare system as a whole. Stay tuned.