I forgot to include an important disadvantage of the threshold model: It doesn't accurately predict the decisions of clinicians and patients in real life! This is partly a consequence of insufficiently accounting for differences in patient risk tolerances or other more idiosyncratic patient preferences (e.g. a patient who is relatively adverse to one specific test or treatment). It is also the consequence of how clinicians and patients alike don't always make "rational" decisions in practice as would otherwise be predicted by expected utility theory (which is an implied foundation of the threshold model). Expected utility theory and analysis (including its shortcomings) will be the topic of a forthcoming video in part 3 of this series. Another minor omission regarding "rule out" thresholds: An additional consideration to make before ruling out a serious diagnosis is how able and reliable the patient would be to return to the clinic or hospital should their condition worsen. For example, if you are ruling out a heart attack in a middle-aged patient in the ER, and the patient lives with their spouse a few blocks away, your threshold to rule it out would be different than if the patient was elderly, of limited mobility, and lived alone up a windy mountain road an hour from the nearest medical facility.
These videos are incredible! A big thank-you on behalf of the Australian junior doctor community who absolutely love your videos on clinical reasoning! Can't wait for the next installment in this series on the assessment of clinical reasoning :)
It could not be said better. Medicine is the art and science of dealing with uncertainty and every tool we have can help the reasoning process. Thank you.
It’s so sad that money pays a factor in running certain tests. Also, I really appreciate how you talk about STIs. A doctor broke the news that I had syphilis really terribly to me and just left me crying. I thought I was in a monogamous relationship like your example. I wish I had a doctor who was more understanding!
Thanks to this video you can understand more the reasons why doctors ask for some type of decision. Likewise, doctors must feel under a lot of pressure since sometimes the evaluations and decisions they make will decide whether the patient lives or not since every decision the patient makes doctor will be important to save the life of each patient
Dr Strong, Thank you very much for this enlightening video. I am wondering if you could do a threshold model analysis of Kidney or Bladder cancer for the present case? The age, unintentional weight loss combined with the symptoms are red flags indicating that we should not miss the malignancies for this patient. I am still not sure what is the best timing to initiate all tests for cancers? the answers will be variable based on the factors mentioned in the video but will be more helpful if there is a sample analysis from you. Many thanks!
Thank you for this wonderful series! I am a little uncomfortable with the term “risk averse” for a patient who prefers testing at a lower probability than average. Would “disease risk averse” be more accurate since they are choosing to weight risk from untreated disease more heavily than testing/treatment risk, but actually taking on additional testing risk? I am concerned "risk averse" gives patients or clinicians a false impression that potential treatment/testing harms are less "risky" than potential disease harms. "Uncertainty averse" could be another way of characterizing these patients.
I forgot to include an important disadvantage of the threshold model: It doesn't accurately predict the decisions of clinicians and patients in real life! This is partly a consequence of insufficiently accounting for differences in patient risk tolerances or other more idiosyncratic patient preferences (e.g. a patient who is relatively adverse to one specific test or treatment). It is also the consequence of how clinicians and patients alike don't always make "rational" decisions in practice as would otherwise be predicted by expected utility theory (which is an implied foundation of the threshold model). Expected utility theory and analysis (including its shortcomings) will be the topic of a forthcoming video in part 3 of this series.
Another minor omission regarding "rule out" thresholds: An additional consideration to make before ruling out a serious diagnosis is how able and reliable the patient would be to return to the clinic or hospital should their condition worsen. For example, if you are ruling out a heart attack in a middle-aged patient in the ER, and the patient lives with their spouse a few blocks away, your threshold to rule it out would be different than if the patient was elderly, of limited mobility, and lived alone up a windy mountain road an hour from the nearest medical facility.
Good history good exam make your impression use the golden hour well
These videos are incredible! A big thank-you on behalf of the Australian junior doctor community who absolutely love your videos on clinical reasoning! Can't wait for the next installment in this series on the assessment of clinical reasoning :)
It could not be said better. Medicine is the art and science of dealing with uncertainty and every tool we have can help the reasoning process. Thank you.
Dr. Strong your dedication is commendable. Words cannot describe my gratitude. ❤️
It’s so sad that money pays a factor in running certain tests.
Also, I really appreciate how you talk about STIs. A doctor broke the news that I had syphilis really terribly to me and just left me crying. I thought I was in a monogamous relationship like your example. I wish I had a doctor who was more understanding!
please more videos like this!
Doctor I hope you will. And I want to till that we NEED you to complete this course
Thanks to this video you can understand more the reasons why doctors ask for some type of decision. Likewise, doctors must feel under a lot of pressure since sometimes the evaluations and decisions they make will decide whether the patient lives or not since every decision the patient makes doctor will be important to save the life of each patient
Dr Strong, Thank you very much for this enlightening video. I am wondering if you could do a threshold model analysis of Kidney or Bladder cancer for the present case? The age, unintentional weight loss combined with the symptoms are red flags indicating that we should not miss the malignancies for this patient. I am still not sure what is the best timing to initiate all tests for cancers? the answers will be variable based on the factors mentioned in the video but will be more helpful if there is a sample analysis from you. Many thanks!
Amazing information
Great Sir very much appreciated
Thank you for this wonderful series! I am a little uncomfortable with the term “risk averse” for a patient who prefers testing at a lower probability than average. Would “disease risk averse” be more accurate since they are choosing to weight risk from untreated disease more heavily than testing/treatment risk, but actually taking on additional testing risk? I am concerned "risk averse" gives patients or clinicians a false impression that potential treatment/testing harms are less "risky" than potential disease harms. "Uncertainty averse" could be another way of characterizing these patients.
Thanks dr strong, do you have any recommended readings on this topic ?
There are some relevant papers in the video description.
Thank you sir!
Shouldn't you be saying 'risk averse' rather than 'risk adverse'?
Lol. If I said that, I'm gong to blame it on the last vestiges of my Philly accent.
@@StrongMed My comment was made in perfectly good faith. I hope I have not offended you. If I did, please excuse me. I am sorry.
No worries. Not offended at all! ;)
@@StrongMed Thank you! I feel relieved. Especially since I watch most of your videos and learn something new.
Just like yesterday wahslla in hospital
Oil
I feel safer controlling my genetic test