3 ms·

They need to add a difficulty correlated metric to the statistics. Maybe BMI and age? I am sure IVF clinics wouldn't offer the procedure to anyone over 35 if

• Lxr 9y ago
  I imagine it’s extremely difficult to come up with a metric that captures everything about the case. BMI, age, tumor type, tumor shape, history of kidney disease, diabetes, where do you stop?
  • MarkMc 9y ago
    You don't need a metric which captures everything about the case - you just need a statistical model whose risk assessment is at least as accurate as the surgeon's assessment. This is not as difficult as it sounds - in Chapter 21 of Thinking Fast and Slow, Kahneman makes a strong case that simple algorithms are very often better than expert clinical judgement.
• zzbzq 9y ago
  Rather than try to figure out some classification criteria, use a predictions market. Have surgeons predict their own chance of success. Preferably, gather multiple second++ opinions for each case. The difficulty of the surgery is based on some combination of the different surgeon's predictions. A surgeon's stats would then be based on his successful and unsuccessful surgeries, weighted against the difficulty. Using this method, not only can you still rank the surgeons based on the successes of their surgeries, but also on the accuracy of their predictions, which will be in larger sample size and also perhaps a better indicator of their mastery of medical knowledge.