Row 20396

Row ID: 20396 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 20396 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

Physician here. AI is already making in-roads to make tedious things less tedious, such as automating some aspects of writing clinical documentation, which may help physician burnout. That will not directly help patients, but it makes things more efficient on the backend. AI tools are doing some initial reads for radiological images in some places to help the radiologists.

In terms of AI that will directly help patients, we've long already had the technology to do that but due to the culture of medicine it is far under-utilized. For example, we still have a lot of unnecessary misdiagnosis. Despite learning great diagnostic skills in medical school and beyond and learning about cognitive biases that can affect accurate diagnosis, the culture of medicine is still that a doctor should just know everything by memory, so if you have to look something up, it is because you are inexperienced or a bad doctor. But no matter how experienced and well-studied a physician is, mistakes will happen when things are not done systematically. See The Checklist Manifesto by Atul Gawande for a whole treatise on this.

As someone who has personally faced misdiagnosis as a patient because of anchoring bias and premature closure, I wish my physician had used a clinical decision support system to offer a wide set of possible diagnoses (the differential diagnosis) as opposed to just jumping on the first diagnosis that seemed half-way consistent with the symptoms.

So until it becomes culturally acceptable and the norm that doctors utilize technology to help make diagnosis or treatment decisions, nothing will change no matter how good the technology gets.

FieldValue
text Physician here. AI is already making in-roads to make tedious things less tedious, such as automating some aspects of writing clinical documentation, which may help physician burnout. That will not directly help patients, but it makes things more efficient on the backend. AI tools are doing some initial reads for radiological images in some places to help the radiologists. In terms of AI that will directly help patients, we've long already had the technology to do that but due to the culture of…
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-21
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Raw Record

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  "text": "Physician here. AI is already making in-roads to make tedious things less tedious, such as automating some aspects of writing clinical documentation, which may help physician burnout. That will not directly help patients, but it makes things more efficient on the backend. AI tools are doing some initial reads for radiological images in some places to help the radiologists.\n\nIn terms of AI that will directly help patients, we've long already had the technology to do that but due to the culture of medicine it is far under-utilized. For example, we still have a lot of unnecessary misdiagnosis. Despite learning great diagnostic skills in medical school and beyond and learning about cognitive biases that can affect accurate diagnosis, the culture of medicine is still that a doctor should just know everything by memory, so if you have to look something up, it is because you are inexperienced or a bad doctor. But no matter how experienced and well-studied a physician is, mistakes will happen when things are not done systematically. See The Checklist Manifesto by Atul Gawande for a whole treatise on this. \n\nAs someone who has personally faced misdiagnosis as a patient because of anchoring bias and premature closure, I wish my physician had used a clinical decision support system to offer a wide set of possible diagnoses (the differential diagnosis) as opposed to just jumping on the first diagnosis that seemed half-way consistent with the symptoms.\n\nSo until it becomes culturally acceptable and the norm that doctors utilize technology to help make diagnosis or treatment decisions, nothing will change no matter how good the technology gets.",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-21",
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