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. 2025 Sep 8.
doi: 10.1097/CCM.0000000000006851. Online ahead of print.

Data Science to Improve ICU Benchmarking

Jorge I F Salluh  1   2   3 , Giulliana M Moralez  1 , Filipe Amado  1 , Gaston Burghi  4
Affiliations

Data Science to Improve ICU Benchmarking

Jorge I F Salluh et al. Crit Care Med. .
No abstract available

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Conflict of interest statement

The authors have disclosed that they do not have any potential conflicts of interest.

References

    1. Azizmalayeri M, Brinkman S, de Keizer NF, et al.: Enhancing quality of care assessments: Managing atypical patients in ICU benchmarking in The Netherlands. Crit Care Med 2025 Aug 15. [online first]
    1. Soares M, Bozza FA, Angus DC, et al.: Organizational characteristics, outcomes, and resource use in 78 Brazilian intensive care units: The ORCHESTRA study. Intensive Care Med 2015; 41:2149–2160
    1. Moralez GM, Amado FS, Martins GAR, et al.: How to use intensive care unit scoring systems: A practical guide for the intensivist. Crit Care Sci 2025; 37:e20250347
    1. Salluh JIF, Quintairos A, Dongelmans DA, et al.; Linking of Global Intensive Care (LOGIC) and Japanese Intensive care PAtient Database (JIPAD) Working Group: National ICU registries as enablers of clinical research and quality improvement. Crit Care Med 2024; 52:125–135
    1. Salluh JIF, Chiche JD, Reis CE, et al.: New perspectives to improve critical care benchmarking. Ann Intensive Care 2018; 8:17

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