Dorikka comments on Open thread, Oct. 19 - Oct. 25, 2015 - Less Wrong

3 Post author: MrMind 19 October 2015 06:59AM

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Comment author: raydora 20 October 2015 12:21:01AM *  0 points [-]

I don't have any surefire methods that don't require a very basic working knowledge of medicine, but a general rule of thumb is the physician's opinion of the algorithmic approach to medical decision making. If it is clearly negative, I'd be willing to bet that the physician is bad. Not quite the same as finding a good one, but decent for narrowing your search.

Along with this, look for someone who thinks in terms of possibilities rather than certainties in diagnoses.

All assuming you're looking for a general practitioner, of course. I wouldn't select surgeons based on this rule of thumb, for instance.

If you're looking for someone who simply has good tableside manner, then reviews and word of mouth do work.

Comment author: Dorikka 20 October 2015 02:49:15AM 2 points [-]

Any particular evidence in favor of this approach, anecdotal or otherwise?

Comment author: raydora 08 November 2015 03:29:06AM 1 point [-]

Late reply, I know!

Standardizing decisions through checklists and decision trees has, in general, shown to be useful if the principles behind those algorithms are based on a reliable map. In medical practice, that's probably the evidence-based medicine approach to screening, diagnosis, and treatment.

In addition, all this assumes that patient management skills are not a concern, since it's not something I personally consider important (from the point of view of a patient) when considering a provider of any medical or technical service. If you typically require more from your physician (and many people do see physicians as societal pillars and someone to talk to their non-medical problems about) than medical evaluation and treatment, then it is something to keep in mind.

Anecdotally, every medical provider I've encountered who was a vocal opponent of clinical decision support systems had a tendency to jump to dramatic conclusions that were later proven wrong.

This is one of the few studies on the subject that isn't behind a paywall.