The Challenge

The mission of the Working Group on Neurocritical Care Informatics is to facilitate the seamless collection and use of data to optimize the management and outcomes of patients in neurocritical care.  Our end point is the creation of a more meaningful medical record (dashboard) that enables precision management of brain injuries.

The brain is the least understood organ in the body and injuries to the brain are multi-faceted and highly complex. Attempts to develop effective therapeutic methods in the past decades have largely failed (Maas AI et al., J Neurotrauma, 2012). This lack of progress is due, in part, to (1) the absence of data to correctly classify brain injured patients into groups where targeted therapy might be most effective and, (2) the lack of data to determine precise endpoints to evaluate new methods. Current neurocritical care units are complex, data-rich environments, where information extraction and consolidated review remain sub-optimal (Schmidt JM et al., Neurocrit Care, 2014). Informatics methods that have been developed remain untested on large populations due to difficulties in scalability.

Our goals are multi-faceted and aim to promote awareness of the benefit to patients and clinicians that would result from a comprehensive approach to the use and integration of data in the neuro ICU: it would promote workflow efficiency and patient safety, it would facilitate timely and effective care and, ultimately, it would improve patient outcomes. Furthermore, we aim to expand the development of tools that extract actionable information from the broad set of physiological and neurological variables being monitored in neuro ICUs. By being presented with integrated, meaningful and interactive information at the point-of-care, care teams will be empowered in their evaluation of the patient’s medical status. Consequently, clinicians will be able to develop more effective and individualized treatments and they will better identify early indicators of worsening conditions in order to act preemptively.

Our mission is achieved by hosting open meetings and by cooperatively developing tools, guidelines and requirements for the creation of easily deployable and scalable data infrastructures in neurocritical care.

Managing brain injury in a more individualistic manner will require data from diverse sources (physiology, imaging, biomarkers, genomics, etc.). The data will need to be integrated, annotated, analyzed, and visualized. It will need to be archived in a manner that can be shared for retrospective analysis, research, and education. A seamless architecture for neurocritical care data is highly desirable but has been very elusive with many barriers slowing progress. Our project will address shortcomings in three areas of technology:

Data Aggregation

The connected Neuro ICU must gather data from multiple sources to provide a comprehensive view of the patient as well as input to analytics and visualization.  These sources include medical devices, lab data, imaging, therapeutic measures (nursing action, drugs, etc.), and the medical record.

One of these areas, medical device connectivity, has been particularly problematic.  There is no widely adopted standard for medical devices to output their data. Additionally, in medical device communication protocols there is a wide range of quality (high quality to error-prone) and capabilities (robust communications to none at all). Today’s solutions for recording medical device data are generally focused on populating the electronic medical record and not on obtaining data at the resolution required for advanced analytics. And many of the newer devices specific to nerocritical care use terms (labels, descriptions, etc.) for their outputs that have no standardized nomenclature and can lead to confusion when aggregated into a larger database.

Some of the data we want to collect (labs, images, medical record data) reside in separate repositories and access to it ranges from easy (images using the DICOM standard) to difficult (medical record data).

This focus area will attempt to identify, facilitate, and/or create methods for the collection of comprehensive data required for managing the neurocritical care patient.

Data Management, Standards, and Sharing

There is an acute need to develop standards for identifying data and metadata both physiologic and phenotypic.  The same holds with methods and techniques for collecting, annotating, and archiving data. Multi-center trials generally spend an inordinate amount of time and money trying to accomplish this…many of them re-inventing the wheel. Solving this problem will provide a cost benefit to funding agencies and will accelerate advances in the quality of care due to the information that can be mined from a unified database.

In this topic we will work with data repositories as well as helping to expand the NINDS Common Data Elements.  We will review and work with various standards and data organizations to provide recommendations. We will also work with data repositories such as FITBIR.

Analytics and Visualization

Once the data is collected, there is a need to extract value.  The value may differ depending on the consumer of the data and thus the analytics will likely span a range of techniques from simple metrics to machine learning.  This topic will cover these techniques as well as associated regulatory processes.