Chapter 6: Understanding Data Harmonization¶
Purpose & intended audience¶
This resource offers guidance to members of the CTSA informatics community including information about Data Harmonization that key stakeholders (leadership, researchers, clinicians, CIOs) can use at their institutions. This guidance can be useful to those who are new to Data Harmonization, as well as to those who are experts and may need assistance conveying the importance of Data Harmonization to a lay audience.
Why is this important?¶
Clinical data are among the most valuable artifacts within CTSA hubs. Appropriately leveraging these data for translational research purposes, while respecting privacy and honoring hub autonomy, will advance CTSA goals and demonstrate its power as a network. The Health Level 7 (HL7) FHIR standard has the potential to enable hubs to develop a next-generation repository from application program interfaces (APIs) that are built into every electronic health record (EHR). For optimal harmonization, these APIs need to be integration-ready, whether used directly for federated queries or for transformation to any number of common standards.
Status and how to contribute:¶
This document is currently in version 1.0 release. Comments from the community are appreciated for incorporation of next version. A commentable copy in Google doc form is available.
The live version (Chapter 6, Version 1.0) is rendered at:
https://reusable-data-best-practices.readthedocs.io
Takeaways¶
The categories of best practice include the following
- Data Harmonization Mission
- Governance
- Sustainability
- Workforce
- Infrastructure
- Relationship w the clinical enterprise
- Data practices
- External relationships and outreach
Acknowledgments¶
Co-leads: Boyd Knosp, University of Iowa (https://orcid.org/0000-0002-3834-3135); Catherine K. Craven, Icahn School of Medicine at Mount Sinai
Christopher G. Chute, Johns Hopkins University (https://orchid.org/0000-0001-5437-2545); Jeanne Holden-Wiltse, University of Rochester CTSI (https://orcid.org/0000-0003-2694-7465); Laura Paglione, Spherical Cow Group (https://orcid.org/0000-0003-3188-6273); Svetlana Rojevsky, Tufts Clinical and Translational Science Institute (https://orcid.org/0000-0002-8353-9006); Juliane Schneider, Harvard Catalyst | Clinical and Translational Science Center (https://orcid.org/0000-0002-7664-3331); Adam Wilcox, University of Washington.
Edited by:
- Lisa O’Keefe | Northwestern University | 0000-0003-1211-7583 | CRO:0000065
- Charisse Madlock-Brown | University of Tennessee Health Science Center | 000-0002-3647-1045
- Andréa Volz | Oregon Health & Science University | 0000-0002-1438-5664
Funding:¶
This work was supported by the National Institutes of Health’s National Center for Advancing Translational Sciences CTSA Program Center for Data to Health (Grant U24TR002306).