I took a quick look and didn't see any critical issues. I can't say I studied it very closely though.
I hope they're leaving plenty of time for feedback after they provide code. That's when I expect to be able to do a thorough review. Has there been any investigation of R as an alternative to SAS? Is there some reason we shouldn't use an Open Source solution? -- Dan ________________________________ From: [email protected] [[email protected]] on behalf of Swander, Lena C [[email protected]] Sent: Tuesday, November 17, 2015 4:01 PM To: [email protected] Subject: ADAPTABLE Base Phenotype Feedback (by Friday, Nov. 20) The coordinating center is requesting feedback on the ADAPTABLE base phenotype draft (ticket #263<https://informatics.gpcnetwork.org/trac/Project/attachment/ticket/263/2015-11-03b%20ADAPTABLE%20base%20phenotype%20-%20DRAFT.pdf>, and attached) by Friday, Nov. 20. This draft is primarily in narrative form. The CC will write a SAS code based on this draft and site feedback. GPC Dev leads, please provide feedback to [email protected] by Nov. 20 for GPC-wide consolidation and submission. Thank you, Lena Swander Project Coordinator | Institute for Clinical and Translational Science MPH Candidate 2016 | Department of Epidemiology College of Public Health, University of Iowa Office Phone: 319-384-9936 [For reference, Dr. Russ Waitman's comments: * Adding Diagnosis and Procedure codes to the eligibility criteria * Consider NCDR registry data as a possible source system to obtain the coronary artery stenosis and ejection fraction * We’ve brought our NCDR PCI data into i2b2 and then things like degree of stenosis are explicit not requiring NLP * https://informatics.kumc.edu/work/browser/heron_load/ncdr_concepts_load.sql * <https://informatics.kumc.edu/work/browser/heron_load/ncdr_constants.sql> https://informatics.kumc.edu/work/browser/heron_load/ncdr_constants.sql * https://informatics.kumc.edu/work/browser/heron_load/ncdr_facts_load.sql * When will we get a CDM query? Right now we are all reinventing the wheel * That really would have the specificity to known versus the text doc that references categories which I don’t think are instantiated in the model. For example I don’t think about AHRQ-CCS Diagnosis Category 100, but we can talk ICD9, ICD10, SNOMED]
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