News
Machine-Learning System Could Aid Critical Decisions in Sepsis Care
Nov 07, 2018
Research shows that sepsis is one of the most frequent causes of hospital admission and one of the most common causes of death in the intensive care unit (ICU) with the ER most often the first point of contact with the sepsis patient. This first-ever model, developed by the MGH/MIT team to specifically aid ER clinicians in sepsis care, aims to result in better outcomes for patients.
Citation for the Full-text Article
Matheson R. Machine-learning system could aid critical decisions in sepsis care. MIT News. November 7, 2018.
Latest News from CRICO
Get all your medmal and patient safety news here.
Roles and Experiences of Registered Nurses on Labor and Delivery Units in the United States During the COVID-19 Pandemic
News
This article, funded in-part by CRICO grants, examines the roles and experiences of labor and delivery (LD) nurses during the COVID-19 pandemic.
Evidence that Nurses Need to Participate in Diagnosis: Lessons From Malpractice Claims
News
This article, co-authored by Candello's Penny Greenberg, MS, RN, CPPS, uses Candello claims data and concluded that nurses should be involved in the diagnostic process to reduce the risk of patient harm.
Expert Consensus on Currently Accepted Measures of Harm
News
This article, co-authored by CRICO President and CEO Mark E. Reynolds and Luke Sato, MD, reported on expert consensus collected to identify key triggers and adverse events that lead to patient harm.
Malpractice Cases in Breast Surgery: An Assessment of Litigation Involving Surgeons
News
CRICO data analysts and researchers from Beth Israel Deaconess Medical Center collaborated to characterize the factors in liability cases involving breast cancer surgery. They used data from Candello's national repository (formerly called CBS database) to identify areas for quality improvement.