Incident 123: Epic Systems’s Sepsis Prediction Algorithms Revealed to Have High Error Rates on Seriously Ill Patients
Description: Epic System's sepsis prediction algorithms was shown by investigators at the University of Michigan Hospital to have high rates of false positives and false negatives, allegedly delivering inaccurate and irrelevant information on patients, contrasting sharply with their published claims.
Entities
View all entitiesAlleged: Epic Systems developed an AI system deployed by University of Michigan Hospital, which harmed sepsis patients.
Incident Stats
Incident ID
123
Report Count
3
Incident Date
2021-08-01
Editors
Sean McGregor, Khoa Lam
Incident Reports
Reports Timeline
Epic Systems, America’s largest electronic health records company, maintains medical information for 180 million U.S. patients (56% of the population). Using the slogan, “with the patient at the heart,” it has a portfolio of 20 proprietary …
Every year 1.7 million adults in the United States develop sepsis, a severe immune response to infection that kills about 270,000 people. Detecting the disease early can mean the difference between life and death.
One of the largest U.S. de…
Artificial intelligence (AI) and algorithmic decision-making systems — algorithms that analyze massive amounts of data and make predictions about the future — are increasingly affecting Americans’ daily lives. People are compelled to includ…
Variants
A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.
