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Federated learning with embedded spaces
[ hands-on, Praful,Daniel ]
Federated learning with embedded spaces
[ hands-on, Praful,Daniel ]
...
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Real World Data FAIR
Real World Data FAIR
11:00 am, Wed 9 Apr 2025
Towards a FAIRer Real World Data Commons: real-time processing of individual level patient discharge reports collected by NY’s SPARCS program.
Towards a FAIRer Real World Data Commons: real-time processing of individual level patient discharge reports collected by NY’s SPARCS program.
We're pleased to have Dr. Jonas De Almeida to lead the discussion on the Real World Data series. We look forward to seeing you there!
Abstract:
To support quality improvement and research, the New York State Department of Health requires hospitals to submit patient discharge reports to the Statewide Planning and Research Cooperative System (SPARCS) Program, managed by the Office of Health Services Quality and Analytics (https://www.health.ny.gov/statistics/sparcs). Established in 1979 through collaboration between the healthcare industry and government, SPARCS aims to, among other goals, develop care management models that decrease patient readmission rates. The program has evolved to provide access to approximately two million new discharge records each year via state-of-the-art Socrata APIs. This presentation will explore the specific data available through SPARCS and the configuration of FAIR mechanisms enabling analysis by members of the public and by researchers, alike. We will conclude by examining the inherent trade-offs associated with open access to detailed, individual-level, real-world health data.
Recommended Readings:
Almeida, J. S., Hajagos, J., Saltz, J., & Saltz, M. (2019). Serverless OpenHealth at data commons scale-traversing the 20 million patient records of New York’s SPARCS dataset in real-time. PeerJ, 7, e6230. https://doi.org/10.7717/peerj.6230
García-Closas, M., Ahearn, T. U., Gaudet, M. M., Hurson, A. N., Balasubramanian, J. B., Choudhury, P. P., Gerlanc, N. M., Patel, B., Russ, D., Abubakar, M., Freedman, N. D., Wong, W. S. W., Chanock, S. J., Berrington de Gonzalez, A., & Almeida, J. S. (2023). Moving Toward Findable, Accessible, Interoperable, Reusable Practices in Epidemiologic Research. American Journal of Epidemiology, 192(6), 995–1005. https://doi.org/10.1093/aje/kwad040
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