Please see the PubMed reference below for background information about this phenotype & algorithm (a copy also attached).
This is based on a phenotype algorithm that was already published a couple years ago by NU, and has been further refined in collaboration with Geisinger whom also has expertise in this area. In addition, given that ICD-10 codes just started being used w/in the last year, we have updated the algorithm w/ those codes & have re-run & re-validated it at both NU & Geisinger. Finally, we have added logic to sub-divide the CRS cases into those w/ and w/o nasal polyps, which is simply a division based on the coded data already used for the CRS phenotype.
The final version of the algorithm for other sites to run, is almost the same as the published version (a copy also attached -the algorithm to use is depicted in Figure 2 and is described in the footnotes of that figure and in the text of the manuscript) w/ 3 additions and 1 correction as follows: an updated flowchart is attached which depicts these changes:
1) ICD-10 codes (in attached Excel file of diagnosis and procedure codes)
2) dividing up cases into those with vs. without nasal polyps for sub-phenotype analysis
3) Controls must have been seen in person in the last 2 years (in an inpatient, outpatient, or ED encounter - the same types of encounters that all diagnoses must originate as in the published algorithm).
Correction: ICD-9 codes for cystic fibrosis corrected (2 removed: 277.9 and V13.8x)
*** If you use SNOMED codes, we have limited ablility to test, but can add SNOMED codes for those sites that use it, please just let us know.
To make it easy to implement, there is a KNIME workflow attached, created by Geisinger & tested at both sites, that any site can easily use. Instructions are in the workflow itself. KNIME is freely avail. s/w that can be downloaded from knime.org to run on any platform, and can connect to any DB or file type. The workflow simply reads in your encounter diagnoses and procedure data in the specified format in the workflow, and then executes all the phenotype logic for you, and outputs the data in the data dictionary format.
Please do NOT use the current PhEMA version of this algorithm is in progress, it is a draft -- the PhEMA software needs an upgrade for it to accomodate "seen by specialist," which won't happen in time for this to be run, so we won't be using it for this phenotype except for testing by NU.