Howard Harrell

speaker

1,260 appearances 4 recordings 1 series first heard May 2026 last heard 23 Jul

Howard Harrell’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 4 in all, peaking in Jul 2026 with 2.

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Thinking About Ob/Gyn · Episode 11.11 When Evidence Misleads · 28 May 2026 podcast

One another reason why this is so important, as you pointed out, Dr.

Harrell, is that most people's interfacing with the clinical literature now is through these AI search tools like open evidence and doxsemity.

And many times in their algorithm, they will privilege meta-analyses and systematic reviews.

But it has been so humbling to look at these trials and to see the kinds of decisions they make and how that actually can lead you astray.

You cannot just take the

Their word for the conclusions and say the average meta-analysis has to be better than the average single center randomized controlled trial.

The other concern, or the other point I want to make, is that what we're really trying to solve for meta-analyses and systematic reviews is how do we synthesize disparate sources of data into a good general claim about a question that we care.

Yeah.

And this is the same sort of process or a similar sort of process that you do when you're applying a diagnosis to a patient.

I, as a fourth-year medical student, will take lots of different pieces of a patient's story, physical exam, and labs, and come up with a diagnostic label.

But Dr.

Harrell, with his clinical experience, is gonna take those and read it appropriately, recognize when there's concordance and disconcordance, and actually apply a different

different diagnostically or apply it sooner in the diagnostic process.

That same process of good synthesis versus bad synthesis also applies to meta-analysis.

There are so many different ways when you had a very sophisticated tool for producing general knowledge.

There are many sophisticated tricks you tied up your sleeve to get the result that you want.

And I love the way you framed it as manufactured certainty.

One thing that I think is a very useful set of questions to ask when you're interpreting trials like this is to ask yourself, any trial is trying to answer does something work here if it's an interventional trial?

But your job as a doctor is to ask yourself, will that thing, if it works somewhere, work here?

And when you look at this meta-analysis that Dr.

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