PREDICT: Pattern Representation and Evaluation of Data through Integration, Correlation, and Transformation
Abstract
The objective is to demonstrate that interactive data visualizations designed to transform and consolidate complex multimodal physiological data into integrated interactive displays will reduce clinician cognitive load and will result in reductions in medical error and improvements in patient care, safety, and efficiency. Research accomplishments include: 1) Devised methods to both filter and interpolate physiological data, 2) Created physiologic indices for clinically meaningful variation among several parameters using a version of empirical orthogonal functions, 3) Applied the above physiologic indices to create a patient overview visualization to help clinicians identify patients that are changing and inserted these indices into the sepsis specific decision support visualization, 4) Created a sepsis identification visualization tool to help clinicians identify patients headed for septic shock, and 5) Generated a visualization tool to help clinicians assess intracranial pressure and generate patient specific physiologic set-points for goal directed therapy, and 6) Demonstrate a real-time data feed to a visualization tool that contains elements from each of the three prototype visualizations. In the next period a cognitive experiment will be conducted to determine the effectiveness of these visualization tools.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 01, 2015
- Accession Number
- ADA624327
Entities
People
- Michael J. Schmidt
Organizations
- Columbia University