Natural experiments can be used to perform experiments that would be difficult (or impossible) to perform in a fully randomized trial. These "experiments" are carried out by analyzing data to focus on certain attributes of interest while controlling for other attributes. One example was looking at flu shots by birthday. Children with summer birthdays typically have their well child visits at a time when a flu vaccine is not available. They must return at a later time to get the shot. This extra friction leads to a lower flu vaccination rate and a higher prevalence of the flu.
The book looks at many other random experiments. They typically used anonymized insurance or medicare claims. They also pull down datasets of doctors, events and other things to correlate. Somet results are counter-intuitive. Emergency heart operations tend to have a higher success rate when a cardiology convention is going on. Some lend themselves to explanation. Younger hospitalists tend to have better outcomes because they are more knowledgeable in the latest practices. However, older doctors that see the greatest number cases tend to also have good performance, likely because they have had a chance to learn modern practices. With surgeons, older surgeons do have better outcomes.
There were many other examples of experiments in the book. The authors have a very open approach, with a willingness to accept criticism of their methods. There may be confounding circumstances that impact the results that are seen. People often change their behavior when they know they are being measured. Trying to improve medical outcomes can be extremely challenging. If we find a good measure, participants will often find a way to maximize that measure without necessarily improving overall outcomes. How do we make medicine better? We need to look at the big picture of the human experience, but also realize that humans are providing the medical care. The experience of receiving the care can be as impactful as the actual care received. How do we maximize everything? We have a significant challenge.
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