Hi Christian,
I guess my use of textbook vs. trade-press was more of a metaphor for intent and style. We obviously want to enable the community, but the community is made up a lot of different roles. What I have seen of the outline so far seems directed to higher level approaches like management, architects, and yes, academics, and less geared toward in-the-weeds developers.
For instance, Measurement seems fairly straight forward. I know lab tests are measurements. I also know that vitals are measurements. However, as a developer, I need to find these in different places in my source database. But what other measurements might I be missing? Are there measurements for oncology or transplants (for instance) that may be low volume but important for research? I don’t know, but it’s my job to find them. That being the case, the definition of a measurement, how it might be used in research studies, and some illustrative examples, take on added importance.
Perhaps a better example is device.
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Epic’s definition of a device is something that records a measurement, like a blood pressure cuff. Is that an important device for OMOP? I’m guessing not.
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There are NDC codes in the device domain (a lot of them are sunscreens). Are those important? Possibly.
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It turns out blood and blood products are also devices (biological), so I am inferring the device (blood) by the procedure (transfusion). Are there other such devices which I can infer? Highly likely.
Without a deeper understanding of what a device is, I’ve got little chance of finding all the devices I need to find.
So my suggestions in the other post are requests for additional details, examples, and just plain advice, for how to develop an OMOP structured database.