IRIS provides a high-level descriptive summary of a population within a OMOP CDM-compliant database
Some Iris measures were incorporated in Achilles version 1.3 This version 1.1 uses CDM v5. Unlike v1.0, this version makes use of the Measurement table to go after lab results.
In terms of database engines - we tested the package on Postgres, MS SQL with no errors. For Oracle, there is a known bug and known fix for it (see Issues on GitHub for the fix).
The best way to use Iris is as R package and from within R.
install.packages("devtools")
devtools::install_github("OHDSI/SqlRender")
devtools::install_github("ODHSI/DatabaseConnector")
devtools::install_github("OHDSI/Iris")
?Iris::execute # To get extended help
# Run study
a<-Iris::execute(dbms = "postgresql", # Change to participant settings
user = "joebruin",
password = "supersecret",
server = "myserver",
cdmSchema = "cdm_schema",
cdmVersion = 4)
#show timing again
a$executionTime
#show results
a$result
#write to a file
write.csv(a$result,file='iris-results.csv',row.names = F)
# Email results file
Iris::email(from = "collaborator@ohdsi.org", # Change to participant email address
dataDescription = "CDM4 Simulated Data") # Change to participant data description
To reload saved results in R
# Load (or reload) study results
results <- Iris::loadOhdsiStudy(verbose = TRUE)
MEASURE RESULT EXPLANATION
G1 141,805,491 count of patients
G2 20,328,289,601 count of events
D2 90,024,522 count of patients with at least 1 Dx and 1 Rx
D3 112,148,500 count of patients with at least 1 Dx and 1 Proc
D4 5,939,621 count of patients with at least 1 Obs, 1 Dx and 1 Rx
D5 277,975 count of deceased patients
Relevant IRIS forum discussion is here http://forums.ohdsi.org/t/short-and-quick-way-to-describe-your-cdm-dataset/251
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