Revisiting Clinical Outcome Prediction for MIMIC-IV

Tom Röhr, Alexei Figueroa, Jens-Michalis Papaioannou, Conor Fallon, Keno Bressem, Wolfgang Nejdl, Alexander Löser


Abstract
Clinical Decision Support Systems assist medical professionals in providing optimal care for patients.A prominent data source used for creating tasks for such systems is the Medical Information Mart for Intensive Care (MIMIC).MIMIC contains electronic health records (EHR) gathered in a tertiary hospital in the United States.The majority of past work is based on the third version of MIMIC, although the fourth is the most recent version.This new version, not only introduces more data into MIMIC, but also increases the variety of patients.While MIMIC-III is limited to intensive care units, MIMIC-IV also offers EHRs from the emergency department.In this work, we investigate how to adapt previous work to update clinical outcome prediction for MIMIC-IV.We revisit several established tasks, including prediction of diagnoses, procedures, length-of-stay, and also introduce a novel task: patient routing prediction.Furthermore, we quantitatively and qualitatively evaluate all tasks on several bio-medical transformer encoder models.Finally, we provide narratives for future research directions in the clinical outcome prediction domain. We make our source code publicly available to reproduce our experiments, data, and tasks.
Anthology ID:
2024.clinicalnlp-1.18
Volume:
Proceedings of the 6th Clinical Natural Language Processing Workshop
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Tristan Naumann, Asma Ben Abacha, Steven Bethard, Kirk Roberts, Danielle Bitterman
Venues:
ClinicalNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
208–217
Language:
URL:
https://aclanthology.org/2024.clinicalnlp-1.18
DOI:
10.18653/v1/2024.clinicalnlp-1.18
Bibkey:
Cite (ACL):
Tom Röhr, Alexei Figueroa, Jens-Michalis Papaioannou, Conor Fallon, Keno Bressem, Wolfgang Nejdl, and Alexander Löser. 2024. Revisiting Clinical Outcome Prediction for MIMIC-IV. In Proceedings of the 6th Clinical Natural Language Processing Workshop, pages 208–217, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
Revisiting Clinical Outcome Prediction for MIMIC-IV (Röhr et al., ClinicalNLP-WS 2024)
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PDF:
https://preview.aclanthology.org/ingest-2024-clasp/2024.clinicalnlp-1.18.pdf