In the Value set development spreadsheet Jim just posted, I note a "CLARITY EXTRACT FILE INVENTORY" that seems designed to show what epic clarity tables are needed for each data domain.
At the hackathon, my presentation briefly covered some static analysis of the HERON ETL code to extract depndency information. Since then, in the portable epic ETL ticket<https://informatics.gpcnetwork.org/trac/Project/ticket/71> I've refined it to look at (roughly) one data domain at a time, and the results are in the same ballpark. For example, etl-deps-load_epic_diagnosis.csv<https://informatics.gpcnetwork.org/trac/Project/attachment/ticket/71/etl-deps-load_epic_diagnosis.csv><https://informatics.gpcnetwork.org/trac/Project/raw-attachment/ticket/71/etl-deps-load_epic_diagnosis.csv> tells us the following CLARITY tables are used: 1. CLARITY_EDG 2. PAT_ENC_DX 3. PROBLEM_LIST In Jim's spreadsheet, he lists PROBLEM_LIST and CLARITY_EDG under ICD-9-CM diagnoses. He lists more tables under SNOMED CT diagnoses. The HERON ETL code doesn't harvest that SNOMED data yet (at least - the KUMC branch doesn't. Maybe the UNMC branch does by now). The static analysis tool I'm hacking together produces CSV files and also converts them to diagrams using dot: etl-deps-load_epic_diagnosis.dot.svg<https://informatics.gpcnetwork.org/trac/Project/attachment/ticket/71/etl-deps-load_epic_diagnosis.dot.svg><https://informatics.gpcnetwork.org/trac/Project/raw-attachment/ticket/71/etl-deps-load_epic_diagnosis.dot.svg> . I've done the exercise for 5 of our load tasks (much like data domains) so far: 1. etl-deps-load_epic_diagnosis.csv<https://informatics.gpcnetwork.org/trac/Project/attachment/ticket/71/etl-deps-load_epic_diagnosis.csv><https://informatics.gpcnetwork.org/trac/Project/raw-attachment/ticket/71/etl-deps-load_epic_diagnosis.csv> * etl-deps-load_epic_diagnosis.dot.svg<https://informatics.gpcnetwork.org/trac/Project/attachment/ticket/71/etl-deps-load_epic_diagnosis.dot.svg><https://informatics.gpcnetwork.org/trac/Project/raw-attachment/ticket/71/etl-deps-load_epic_diagnosis.dot.svg> 2. etl-deps-load_epic_demographics.csv<https://informatics.gpcnetwork.org/trac/Project/attachment/ticket/71/etl-deps-load_epic_demographics.csv><https://informatics.gpcnetwork.org/trac/Project/raw-attachment/ticket/71/etl-deps-load_epic_demographics.csv> * etl-deps-load_epic_demographics.dot.svg<https://informatics.gpcnetwork.org/trac/Project/attachment/ticket/71/etl-deps-load_epic_demographics.dot.svg><https://informatics.gpcnetwork.org/trac/Project/raw-attachment/ticket/71/etl-deps-load_epic_demographics.dot.svg> 3. etl-deps-load_epic_labs.csv<https://informatics.gpcnetwork.org/trac/Project/attachment/ticket/71/etl-deps-load_epic_labs.csv><https://informatics.gpcnetwork.org/trac/Project/raw-attachment/ticket/71/etl-deps-load_epic_labs.csv> * etl-deps-load_epic_labs.dot.svg<https://informatics.gpcnetwork.org/trac/Project/attachment/ticket/71/etl-deps-load_epic_labs.dot.svg><https://informatics.gpcnetwork.org/trac/Project/raw-attachment/ticket/71/etl-deps-load_epic_labs.dot.svg> 4. etl-deps-load_epic_med_facts.csv<https://informatics.gpcnetwork.org/trac/Project/attachment/ticket/71/etl-deps-load_epic_med_facts.csv><https://informatics.gpcnetwork.org/trac/Project/raw-attachment/ticket/71/etl-deps-load_epic_med_facts.csv> * etl-deps-load_epic_med_facts.dot.svg<https://informatics.gpcnetwork.org/trac/Project/attachment/ticket/71/etl-deps-load_epic_med_facts.dot.svg><https://informatics.gpcnetwork.org/trac/Project/raw-attachment/ticket/71/etl-deps-load_epic_med_facts.dot.svg> 5. etl-deps-load_epic_social_history.csv<https://informatics.gpcnetwork.org/trac/Project/attachment/ticket/71/etl-deps-load_epic_social_history.csv><https://informatics.gpcnetwork.org/trac/Project/raw-attachment/ticket/71/etl-deps-load_epic_social_history.csv> * etl-deps-load_epic_social_history.dot.svg<https://informatics.gpcnetwork.org/trac/Project/attachment/ticket/71/etl-deps-load_epic_social_history.dot.svg> -- Dan
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