Massachusetts Institute of Technology

The General Hospital Corporation

Michael Filbin

Thomas Heldt

Andrew Tomas Reisner

George Cheeran Verghese

Max H Dunitz

Systems and methods are disclosed for sepsis care management. First data regarding a patient and second data regarding a clinician's treatment of a patient are received by at least one processor. The first data regarding the patient is processed to assess a likelihood that the patient would benefit from administration of each of one or more critical actions for treatment of sepsis, wherein at least one of the one or more critical actions relates to a request for at least one additional diagnostic action. A target treatment protocol, comprising a decision for each of the one or more critical actions, is determined based on the assessed likelihoods. The second data regarding a clinician's treatment of the patient is compared to the target treatment protocol and a notification is provided to the clinician if the second data is incompatible with the target treatment protocol.

System and method for sepsis care task management

A method to quantitatively predict a patient's serum lactate level, comprising measuring arterial blood pressure and heart rate from the patient, computing estimates of one or more cardiovascular parameters from the measured arterial blood pressure and heart rate, providing one or more classifiers that have been trained on a training data set including a reference set of arterial blood pressure, heart rate, and serum lactate levels and using the one or more classifiers to estimate the serum lactate level of the patient.

Growing community of inventors

Jamaica Plain, MA, United States of America

Michael Filbin