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.
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Improving Diagnosis in Health Care
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The greatly anticipated report, Improving Diagnosis in Health Care, released by the Institute of Medicine (IOM), a division of the National Academies of Sciences, Engineering, and Medicine, shines a light on the risks to patients and providers in missed, delayed, or wrong diagnoses. Included in the report, in addition to three case studies, are several references to the analysis done for the CRICO Strategies 2014 Benchmarking Report Malpractice Risks in the Diagnostic Process.
I-PASS and SBAR Handoff Tools Have Proven Benefits
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The Patient Safety & Quality Healthcare magazine highlights the CRICO Strategies 2015 CBS Benchmarking Report on communication failures. The report was the catalyst for a recent Patient Safety Monitor Journal published interview, where patient safety experts weighed in on why nearly one-third of malpractice claims involve a communication failure, leading to significant patient harm.
A Perioperative Teamwork Instructor Training Program for Supporting Perioperative Teamwork
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A research abstract presenting the CRICO and Center for Medical Simulation (CMS) educational program focused on inter-professional educators to prepare them to lead training programs was selected as 2nd place award winner and will be presented at the 15th Annual International Meeting on Simulation in Healthcare, January 10th–14th, 2015.