Big data in status epilepticus

Abstract

Status epilepticus care and treatment are already being touched by the revolution in data science. New approaches designed to leverage the tremendous potential of "big data" in the clinical sphere are enabling researchers and clinicians to extract information from sources such as administrative claims data, the electronic medical health record, and continuous physiologic monitoring data streams. Algorithmic methods of data extraction also offer potential to fuse multimodal data (including text-based documentation, imaging data, and time-series data) to improve patient assessment and stratification beyond the manual capabilities of individual physicians. Still, the potential of data science to impact the diagnosis, treatment, and minute-to-minute care of patients with status epilepticus is only starting to be appreciated. In this brief review, we discuss how data science is impacting the field and draw examples from the following three main areas: (1) analysis of insurance claims from large administrative datasets to evaluate the impact of continuous electroencephalogram (EEG) monitoring on clinical outcomes; (2) natural language processing of the electronic health record to find, classify, and stratify patients for prognostication and treatment; and (3) real-time systems for data analysis, data reduction, and multimodal data fusion to guide therapy in real time. While early, it is our hope that these examples will stimulate investigators to leverage data science, computer science, and engineering methods to improve the care and outcome of patients with status epilepticus and other neurological disorders. This article is part of the Special Issue "Proceedings of the 7th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures".

Keywords: Big data; Continuous EEG; Epilepsy; Multimodal data; Natural language processing; Status epilepticus.

Figure 1.

Use of cEEG in critically ill discharges from 2004 to 2013 by diagnostic subcategory. Data derived from National Inpatient Sample database. Numerator is the number of patients who underwent cEEG; denominator is the total discharges with a particular diagnosis. Figure reproduced with permission from Hill, et al., “Continuous EEG is associated with favorable hospitalization outcomes for critically ill patients,” Neurology, Jan 2019, 92 (1) e9–e18[20].

Figure 2.

Timeline of milestones for NLP in epilepsy. Integrated EpSO-based tools are highlighted with green arrows. EPILEPSIAE = Evolving Platform for Improving the Living Expectations of Patients Suffering from IctAl Events.

Figure 3.

Implanted devices with cloud connectivity. (A) Schematic of next-generation epilepsy management system using Medtronic investigational Summit RC+S. The device interfaces with a local PAD and the cloud to create a flexible platform with local and distributed computing, analytics, and data storage. Figure reproduced with permission from Kremen, et al., “Integrating Brain Implants with Local and Distributed Computing Devices: A Next Generation Epilepsy Management System,” IEEE:JTEHM, Sep 2018, Vol 6[53]. (B) Seizure detection paradigm using cloud computing. Potential seizure clips are identified using a hypersensitive, on-board seizure detector. These candidate clips are transmitted to a cloud platform for analysis using a highly accurate, computationally intensive algorithm. Figure reproduced with permission from Baldassano, et al., “Cloud computing for seizure detection in implanted neural devices,” Journal of Neural Engineering, Feb 2019, 16 (2)[88].

Figure 4.

ICU data analysis pipeline. The next generation of real-time data analysis platforms will incorporate multimodality data and employ machine learning algorithms to provide custom clinical event detections. By incorporating clinician feedback through reinforcement learning, these algorithms can intelligently adapt over time. cEEG=continuous EEG, ICP=intracranial pressure, PbO₂=brain tissue oxygen, CPP=cerebral perfusion pressure, HR=heart rate, cBP = continuous blood pressure, T=continuous temperature, SpO₂=blood oxygen saturation.