Sepsis and septic shock case identification from electronic health records: an open-source workflow and comparison of cohorts by criteria - Summary - MDSpire
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Sepsis and septic shock case identification from electronic health records: an open-source workflow and comparison of cohorts by criteria
To derive sepsis and septic shock cases from electronic health records and provide a transparent, reproducible workflow with publicly available programming code, enhancing the reliability of sepsis identification.
Key Findings:
The study outlines a complete data workflow methodology for sepsis case identification, demonstrating its effectiveness.
Sepsis and septic shock cases were identified using CDC ASE and Sepsis-3 clinical criteria, with specific results indicating the accuracy of the workflow.
Programming code for data extraction and cohort identification is publicly available on GitHub, promoting transparency.
Interpretation:
The availability of a transparent and reproducible workflow enhances the reliability of sepsis case identification, supporting broader adoption in healthcare systems and improving patient outcomes.
Limitations:
Variability in case identification approaches may still exist despite the open-source framework, potentially affecting the reliability of results.
The study is limited to a single health system, which may affect generalizability and applicability to other settings.
Conclusion:
This work provides a comprehensive methodology for sepsis identification from EHRs, promoting reproducibility and transparency in research.
by Seth R. Bauer, Lyla Mourany, Paul R. Gunsalus, Alex Milinovich, Sandra L. Kane-Gill, Xiaofeng Wang, Yasir Tarabichi, Vidula Vachharajani, Jarrod E. Dalton
