| > It’s generally difficult to quantify such risks in any meaningful manner According to the literature 33 out of 100 patients who underwent this operation in the US within the past 10 years died. 90% of those had complicating factors. You [ do / do not ] have such a factor. Who knows if any given layman will appreciate the particular quantification you provide but I'm fairly certain that data exists for the vast majority of serious procedures at this point. I've actually had this exact issue with the veterinarian. I've worked in biomed. I pulled the literature for the condition. I had lots of different numbers but I knew that I didn't have the full picture. I'm trying to quantify the possible outcomes between different options being presented to me. When I asked the specialist, who handles multiple such cases every day, I got back (approximately) "oh I couldn't say" and "it varies". The latter is obviously true but the entire attitude is just uncooperative bullshit. > puts you in a damned-if-does, damned-if-it-doesn’t-work-out situation Not really. Don't get me wrong, I understand that a litigious person could use just about anything to go after you and so I appreciate that it might be sensible to simply refuse to answer. But from an academic standpoint the future outcome of a single sample does not change the rigor of your risk assessment. > Doctors are in no way incentivised to do so Don't they use quantifications of risk to determine treatment plans to at least some extent? What's the alternative? Blindly following a flowchart? (Honest question.) > The returned chance of 1/3 probably had an error margin of +/-33% itself What do you mean by this? Surely there's some error margin on the assessment itself but I don't see how any of us commenting could have any idea what it might have been. |
Everyone has complicating factors. Age, gender, ethnicity, obesity, comorbidities, activity level, current infection status, health history, etc. Then you have to factor in the doctor's own previous performance statistics, plus the statistics of the anaesthesiologist, nursing staff, the hospital itself (how often do patients get MRSA, candidiasis, etc.?).
And, of course, the more factors you take into account, the fewer relevant cases you have in the literature to rely on. If the patient is a woman, how do you correctly weight data from male patients that had the surgery? What are the error bars on your weighting process?
It would take an actuary to chew through all the literature and get a maximally accurate estimate based on the specific data that is known for that patient at that point in time.