During a successful Phase 2 effort, Etiometry collaborated with multiple world-class pediatric centers to develop, validate, and deploy novel analytics that combine multiple physiologic data streams into a probabilistic assessment of inadequate oxygen delivery to critically ill patients. The analytics were integrated into the Etiometry Platform with the goal of improving physician situational awareness and preventing adverse outcomes in post-surgical pediatric cardiac patients in the ICU. During this time the platform and the analytics received FDA 510(k) clearance and were deployed in six pediatric Cardiac Intensive Care Units (CICUs). The Phase 2B effort will build on these achievements by expanding the platform?s capabilities and respective FDA cleared indications. The Etiometry Platform will integrate the new analytics into formal ICU patient care protocols that will be evaluated in a multi-center multi-arm adaptive randomization clinical trial. If successful, the results of will be used to support FDA clearance with specific claims of clinical effectiveness. The ultimate objective of the proposed SBIR effort will be demonstrate that the clinical analytics can significantly affect clinical outcomes of critically ill pediatric patients.

Public Health Relevance

Patient care in the ICU is extraordinarily complex, especially given the number of continuous clinical measurements and the volume of data to be analyzed by hospital staff. The Etiometry Platform will provide analytics based decision support, which helps clinicians detect and treat critical medical risks more effectively, leading to better health outcomes and reduced care cost.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
Project #
2R44HL117340-05
Application #
9512432
Study Section
Special Emphasis Panel (ZHL1)
Program Officer
Evans, Frank
Project Start
2012-07-13
Project End
2021-04-30
Budget Start
2018-05-15
Budget End
2019-04-30
Support Year
5
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Etiometry, LLC
Department
Type
DUNS #
961840241
City
Boston
State
MA
Country
United States
Zip Code
Baronov, Dimitar; McManus, Michael; Butler, Evan et al. (2015) Next generation patient monitor powered by in-silico physiology. Conf Proc IEEE Eng Med Biol Soc 2015:4447-53