Description
This project aims to
(1) develop and test a predictive model identifying emerging sepsis using artificial intelligence and machine learning, and (2) translate model-based learnings into improved operational criteria and a proposal to pilot the new identification method.
This project leverages in-hospital and ambulatory data from the Sutter Health electronic health record.
Principal Investigator
Funder
Greathouse Family Foundation/Sutter Philanthropy
Research Topics
Related Studies
Stupski Serious Illness Program Evaluation
Investigator: Sylvia Sudat, PhD
Improving the Outcomes of Older Adults with Psychosocial Vulnerability Undergoing Major Surgery.
Investigator: External PI, Principal Investigator
Improving Cancer Care
Investigator: Su-Ying Liang, Ph.D.
Multilevel Study of Lung Cancer Screening Guidelines Implementation (MUST)
Investigator: Jiang Li, Ph.D., MPH
Implementing Universal Lynch Syndrome Screening Across Multiple Healthcare Systems: Identifying Strategies to Facilitate and Maintain Programs in Different Organizations Contexts
Investigators: Monique de Bruin, M.D., MPH, External PI, Principal Investigator, Su-Ying Liang, Ph.D.
Severe Mental Illness and Patterns of Emergency Department Utilization
Investigator: Kristen M.J. Azar, R.N., BSN, MSN/MPH
Open and Ask Study
Investigators: Cheryl Stults, Ph.D., Albert S. Chan, M.D., M.S., FAAFP
The Impact of Lean Management on Primary Care Efficiency, Affordability, and the Patient Experience
Investigator: Su-Ying Liang, Ph.D.
Prevalence, Treatment and Outcomes of Asian Subgroups with Coronary Artery Disease in the U.S.
Investigators: Jiang Li, Ph.D., MPH, External PI, Principal Investigator