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.
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.
There are NDC codes in the device domain (a lot of them are sunscreens). Are those important? Possibly.
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.