Stanford
STAnford medicine Research data Repository

Research IT and Research Informatics Center host a number of office hours, and online tutorials sessions. We provide access to documentation and code, monitor a slack channel and provide mechanisms to file bug reports.

Research support

STARR Tools

STARR Tools (fka STRIDE) is the most mature self-service tool in STARR portfolio. It has been running at Stanford since 2008, and supports hundreds of IRBs and researchers. It is currently running on cloud and uses cloud native architecture. You can access data in Stanford data model, use intuitive cohort and chart review tools. For documentation on how to get started, FAQ and more, please visit the STARR Tools website. (link)

 

OMOP, ATLAS and Advanced Cohort Engine (ACE)

STARR-OMOP has been running at Stanford since 2019. ATLAS Cohort analysis tool from OHDSI consortium has been running since 2020. In addition to Stanford generated resources, there is significant documentation from the OHDSI community. 

  • Self service: Get access to STARR-OMOP-deid and ATLAS 
  • Slack channel: You can ask the community any STARR OMOP related questions on starrdatausers.slack.com. Research IT staff and Nero team monitors this channel. Your questions may be answered by other knowledgeable users. We also announce new releases, and features on the channel.
  • Code: Access to sample code in Stanford gitlab is made available to Stanford researchers with access to OMOP data. You get access to python notebooks using Synpuf( Medicare Claims Synthetic Public Use data files in OMOP CDM ver 5.3.1). Our goal is to help users gain familiarity with the OMOP CDM with publicly available data. The same code is applicable to STARR OMOP dataset.
  • Office hours: Office Hour details are available here. Office hour timings are also announced/updated on the slack channel.
  • External training material by OHDSI community and EHDEN Academy:
    • ATLAS Tutorials: This is a set of video tutorials on the use and functionality of ATLAS and has been released by the OHDSI community. (link)
    • European Health Data and Evidence Network (EHDEN): EHDEN Academy has a number of training modules including, Extract, Transform, and Load (ETL) processes to go from raw observational data to the OMOP Common Data Model, OHDSI Tools, Deep diving into ATLAS with focus on phenotype definition, characterisation and evaluation, population-level effect estimation, and patient-level prediction. (link)
  • Research Technology training:

  • OMOP and ATLAS documentation by OHDSI (public access):

    • OMOP CDM Specification: OHDSI consortium provided detailed specification of the OMOP CDM v5.3.1 data model.

    • Themis rules: These rules guide the CDM development with the goal of  developing standardized tools and methods and drive quality, reproducibility and efficiency.
    • Book Of OHDSI: A central knowledge repository for OHDSI describing the OHDSI community, OHDSI data standards, and OHDSI tools.
    • ATLAS wiki and github: ATLAS Wiki and github repository maintained by the OHDSi community

  • STARR-OMOP documentation by Research Technology:

    • STARR-OMOP Technical Specifications document: This document provides details regarding the underlying STARR-OMOP data, transformations, quality metrics and techniques such as de-identification. This g-doc is accessible with SUNetID.
    • Questions users like you have asked: FAQ and much more. This g-doc is accessible with SUNetID.
    • STARR-OMOP manuscript: We specifically recommend reading the Supplementary Material for methodologies and analytics.
    • STARR-OMOP data dictionary: In addition to tables required for OMOP CDM 5.3.1, the dataset contains some extra columns which are not strictly part of the CDM definition, but have been added for increased source/patient traceability. The STARR OMOP identified dataset is created using Clarity tables which only include the patient and encounter data that is permissible for research. This deid dataset does not contain psychiatric notes, or other confidential notes. This g-sheet is publicly accesible.
  • Identified OMOP or a Limited Data Set: Request a consultation service

PEDSNet Pediatric Data 

Research Technology team develops and maintains PEDSNet data model as part of our participation in PEDSNet consortium. PEDSNet is optimized for pediatric research. This data has limited access right now. Please request a data consultation if you want to learn more. Here are some external resources:

Other

For all other help, request a consultation.