A common longitudinal intensive care unit data format (CLIF) for critical illness research

RATIONALE: Critical illness threatens millions of lives annually. Electronic health record (EHR) data are a source of granular information that could generate crucial insights into the nature and optimal treatment of critical illness.

OBJECTIVES: Overcome the data management, security, and standardization barriers to large-scale critical illness EHR studies.

METHODS: We developed a Common Longitudinal Intensive Care Unit (ICU) data Format (CLIF), an open-source database format to harmonize EHR data necessary to study critical illness. We conducted proof-of-concept studies with a federated research architecture: (1) an external validation of an in-hospital mortality prediction model for critically ill patients and (2) an assessment of 72-h temperature trajectories and their association with mechanical ventilation and in-hospital mortality using group-based trajectory models.

MEASUREMENTS AND MAIN RESULTS: We converted longitudinal data from 111,440 critically ill patient admissions from 2020 to 2021 (mean age 60.7 years [standard deviation 17.1], 28% Black, 7% Hispanic, 44% female) across 9 health systems and 39 hospitals into CLIF databases. The in-hospital mortality prediction model had varying performance across CLIF consortium sites (AUCs: 0.73–0.81, Brier scores: 0.06–0.10) with degradation in performance relative to the derivation site. Temperature trajectories were similar across health systems. Hypothermic and hyperthermic-slow-resolver patients consistently had the highest mortality.

CONCLUSIONS: CLIF enables transparent, efficient, and reproducible critical care research across diverse health systems. Our federated case studies showcase CLIF’s potential for disease sub-phenotyping and clinical decision-support evaluation. Future applications include pragmatic EHR-based trials, target trial emulations, foundational artificial intelligence (AI) models of critical illness, and real-time critical care quality dashboards.

Juan C Rojas, Patrick G Lyons, Kaveri Chhikara, Vaishvik Chaudhari, Sivasubramanium V Bhavani, Muna Nour, Kevin G Buell, Kevin D Smith, Catherine A Gao, Saki Amagai, Chengsheng Mao, Yuan Luo, Anna K Barker, Mark Nuppnau, Michael Hermsen, Jay L Koyner, Haley Beck, Rachel Baccile, Zewei Liao, Kyle A Carey, Brenna Park-Egan, Xuan Han, Alexander C Ortiz, Benjamin E Schmid, Gary E Weissman, Chad H Hochberg, Nicholas E Ingraham, William F Parker