mz-health/OMOP
mz-health
/
OMOP
mirror of https://github.com/OHDSI/CommonDataModel.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Updated Frequently Asked Questions (markdown)

clairblacketer 2017-12-11 09:37:30 -05:00
parent 8cc385931e
commit f740a3b75c
1 changed files with 36 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

36
Frequently-Asked-Questions.md

@ -123,3 +123,39 @@ While there are a variety of tools freely available from the community, these ar
* [RabbitInAHat](https://github.com/OHDSI/whiterabbit) - an application for interactive design of an ETL to the OMOP Common Data Model with the help of the the scan report generated by White Rabbit
* [Usagi](https://github.com/OHDSI/usagi) - an application to help create mappings between coding systems and the Vocabulary standard concepts.
**23. Who is responsible for updating the tools to account for data model changes, bugs, and errors?**
The community! All the tools are open source meaning that anyone can submit an issue they have found, offer suggestions, and write code to fix the problem.
**24. Do the current tools allow a user to define a treatment gap (persistence window) of any value when creating treatment episodes?**
Yes – the ATLAS tool allows you to specify a persistence window between drug exposures when defining a cohort (see image below).
![](https://github.com/OHDSI/CommonDataModel/blob/master/Documentation/CommonDataModel_Wiki_Files/ATLAS_Persistence_Window.PNG)
**25. Can the current tools identify medication use during pregnancy?**
Yes, you can identify pregnancy markers from various clinical domains, including conditions and procedures, for example ‘live birth’, and then define temporal logic to look for drug exposure records in some interval prior to the pregnancy end. In addition, members of the community have built an advanced logic to define pregnancy episodes with all pregnancy outcomes represented, which can be useful for this type of research.
**26. Do the current tools execute against the mapped values or source values?
The tools can execute against both source and mapped values, though mapped values are strongly encouraged. Since one of the aims of OHDSI is to create a distributed data network across the world on which to run research studies, the use of source values fails to take advantage of the benefits of the Common Data Model.
## Network Research Studies
**27. Who can generate requests?**
Anyone in the community! Any question that gains enough interest and participation can be a network research study.
**28. Who will develop the queries to distribute to the network?**
Typically a principal investigator leads the development of a protocol. The PI may also lead the development of the analysis procedure corresponding to the protocol. If the PI does not have the technical skills required to write the analysis procedure that implements the protocol, someone in the community can help them put it together.
**29. What language are the queries written in?**
Queries are written in R and SQL. The [SqlRender](https://github.com/OHDSI/sqlrender) package can translate any query written in a templated SQL Server-like dialect to any of the supported RDBMS environments, including Postgresql, Oracle, Redshift, Parallel Data Warehouse, Hadoop Impala, Google BigQuery, and Netezza.
**30. How do the queries get to the data partners and how are they run once there?**
OHDSI runs as a distributed data network. All analyses are publicly available and can be downloaded to run at each site. The packages can be run locally and, at the data partner’s discretion, aggregate results can be shared with the study coordinator.
Data partners can also make use of one of OHDSI's open-source tools called [ARACHNE](https://github.com/OHDSI/arachne), a tool to facilitate distributed network analytics against the OMOP CDM.