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Prediction of 30-Day Readmission Using Machine Learning
Prediction of 30-Day Readmission Using Machine Learning

NCT04849312

CompletedN/A

Sponsor: Brigham and Women's Hospital

Conditions: Infection, Heart Failure, Chronic Obstructive Pulmonary Disease, Asthma, Gout Flare

Countries: United States

This is a retrospective observational study drawing on data from the Brigham and Women's Home Hospital database. Sociodemographic and clinic data from a training cohort were used to train a machine learning algorithm to predict the likelihood of 30-day readmission throughout a patient's admission. This algorithm was then validated in a validation cohort.

Eligibility overview

Sex: ALL

Age: 18 Years to —

Healthy volunteers: No

Study type: OBSERVATIONAL

Eligibility criteria
Was a subject in the Brigham and Women's Home Hospital study and has a completed record in the study's database.
Locations (2)
  • Boston, Massachusetts, United States
  • Boston, Massachusetts, United States