Nice debate here. But it is getting long. Let me see:
Correct. If the source tells us what the episodes are we are all set. But the debate is about derivation when you don’t have that, à la @Gowtham_Rao’s phenotypes. He claims all you need is regular OMOP tables and you can do it, reliably, from the Conditions and Modifiers.
That would be wonderful. But apart from the fact that we are far away from having the logic for such algorithms for disease episodes, the question remains: Could they work without the context of the source data? Is this an ETL job, or an universal phenotype-like job?
You seem to be claiming that the Type concept will provide sufficient context for each Modifier (stage, grade, mets, nodes) telling us how much the algorithm should believe it. But there is more trouble lurking:
- What about unstructured imaging and path lab reports?
- What about contradictions between EHR and registries, or contradictions between different source information?
- What about incomplete information? For example, some ambulatory clinic will record chemotherapy, but it will not record surgery in a adjuvant or neoadjuvant setting, or autologous stem cell transplantation. Similarly, administration of oral chemotherapy is often organized differently than parenteral.
In other words, all this is so messy that we need to give the ETLer some serious power to make the right choices. That is the point of the Episodes. The analyst using OMOP tables alone would be lost.
That’s a good thing. In our workgroup, we are actually debating things. 
You realize that all OMOP databases are ETLed, do you? The ETLer has to make a ton of decisions of how to interpret the source data in such a way that it fits the intended representation of the CDM and vocabulary. And no, those decisions are not peer-reviewable. Plus: If anything I am not mistrusting the ETLer like you do. But if algorithms can make her life easier I am all for it.
What is that? And how is that not used for studies? Let me quote @Patrick_Ryan:
True. @Patrick_Ryan made a list and he community voted on them. Where did it get its wisdom from? They are needed for disease setting and outcomes in the studies folks are running all the time.
But you are right, I shouldn’t debate the phenotypes here, except whether or not they are the same thing as the episodes.
Back in Phebruary they certainly were. Do you have outcomes that are not conditions now?
You’d be surprised to hear that from me, but actually if we could create standardized episodes purely from structured data in the OMOP tables I don’t think we’d need them. We’d just use your phenotypes. Episodes only have a life if they need to be populated pre or peri-OMOP.
That’s what it boils down to. I hope you and @rimma will be right. Till then, my hope is we can arrive at some mixture: standard algorithms, that are using OMOP tables, but are configured with information the ETLer has obtained from the source data or by asking folks in the institution.