Why get de-identified data? Examples:
- Develop a predictive model to identify patients at high risk for hypoglycemia, with covariates and outcome data.
- Quickly search clinical notes to verify/determine use of specific terms that are written and may not be in the structured data
- Pattern recognition and machine learning to understand why patients with seemingly identical risk factors demonstrate such wide variety in cardiac disease manifestations and outcomes.
- You want to explore the data yourself, don't need patient identifiers and/or have very limited funding.
Your options:
- First time User? Request Data Access for Research
- Already using the De-identified clinical data warehouse or De-id OMOP? Join the active User Group!
TIP! Once you are approved and are granted access to UCSF's de-identified clinical data, you will automatically have access to the tools and applications! Start by requesting data access for research.
- De-identified Data Tools
- These include both point-and-click PatientExploreR tool, EMERSE and programmable options like the De-identified Clinical Data Warehouse (CDW) and access to the de-identified clinical notes via the Solr API.
- Information Commons
- Clinical data at scale and on high performance compute environment (HPC)
- An environment suited to pattern recognition and machine learning (Apache Spark)
- Currently provides de-identified structured data. De-identified images and de-identified clinical notes coming soon
- Data Extraction Consultation
- Get guidance from a UCSF expert who will help you define the data you need and clarify the data that is available.
- After the initial free hour, recharge fees will apply
- UC Health data may be requested, but processing time can be lengthy.
Compliance requirements
IRB approval not required
Online attestation AND training required
Data De-identification Validation required if sharing with external partners