Z. M. Grinspan (1, 2, 3), Y. C. Eldar (4), D. Gopher (5), A. Gottlieb (5), R. Lammfromm (5), H. S. Mangat (3, 6), N. Peleg (4), S. Pon (2, 3), I. Rozenberg (4), N. D. Schiff (3, 6, 7), D. E. Stark (8), P. Yan (3, 6), H. Pratt (9), B. E. Kosofsky (2, 3, 6, 7)
(1) Department of Healthcare Policy & Research, Weill Cornell Medicine, New York, NY; (2) Department of Pediatrics, Weill Cornell Medicine, New York, NY; (3) New York-Presbyterian Hospital, New York, NY; (4) Faculty of Electrical Engineering, Technion Israel Institute of Technology, Haifa, Israel; (5) Faculty of Industrial Engineering and Management, Technion Israel Institute of Technology, Haifa, Israel; (6) Department of Neurology, Weill Cornell Medicine, New York, NY; (7) Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY; (8) Departments of Medicine and Bioengineering, Stanford University, Stanford, CA; (9) Faculties of Medicine and Biomedical Engineering, Technion Israel Institute of Technology, Haifa, Israel
Pediatric intensive care units [N02.278.388.493.390], neurology [H02.403.600], biomedical engineering [H02.070], informatics [L01.313], data display [F02.784.412.221]
Background: Physicians caring for children with serious acute neurologic disease must process overwhelming amounts of physiological and medical information. Strategies to optimize real time display of this information are understudied.
Objectives: Our goal was to engage clinical and engineering experts to develop guiding principles for creating a pediatric neurology intensive care unit (neuroPICU) monitor that integrates and displays data from multiple sources in an intuitive and informative manner.
Methods: To accomplish this goal, an international group of physicians and engineers communicated regularly for one year. We integrated findings from clinical observations, interviews, a survey, signal processing, and visualization exercises to develop a concept for a neuroPICU display.
Results: Key conclusions from our efforts include: (1) A neuroPICU display should support (a) rapid review of retrospective time series (i.e. cardiac, pulmonary, and neurologic physiology data), (b) rapidly modifiable formats for viewing that data according to the specialty of the reviewer, and (c) communication of the degree of risk of clinical decline. (2) Specialized visualizations of physiologic parameters can highlight abnormalities in multivariable temporal data. Examples include 3-D stacked spider plots and color coded time series plots. (3) Visual summaries of EEG with spectral tools (i.e. hemispheric asymmetry and median power) can highlight seizures via patient-specific “fingerprints.” (4) Intuitive displays should emphasize subsets of physiology and processed EEG data to provide a rapid gestalt of the current status and medical stability of a patient.
Conclusions: A well-designed neuroPICU display must present multiple datasets in dynamic, flexible, and informative views to accommodate clinicians from multiple disciplines in a variety of clinical scenarios.