Prediction of 30-Day Readmission Using Machine Learning

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.

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Key information

Conditions

Infection Anticoagulants; Increased Asthma Atrial Fibrillation Rapid Bronchial Diseases Cardiovascular Diseases Chronic Disease Chronic Kidney Diseases Chronic Obstructive Pulmonary Disease Disease Attributes Female Urogenital Diseases Female Urogenital Diseases and Pregnancy Complications Gout Flare Heart Diseases Heart Failure Hypersensitivity Hypersensitivity, Immediate Hypertension Hypertensive Crisis Hypertensive Urgency Immune System Diseases Infections Kidney Diseases Lung Diseases Lung Diseases, Obstructive Male Urogenital Diseases Pathologic Processes Pathological Conditions, Signs and Symptoms Pulmonary Disease, Chronic Obstructive Renal Insufficiency Renal Insufficiency, Chronic Respiratory Hypersensitivity Respiratory Tract Diseases Urogenital Diseases Urologic Diseases Vascular Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Brigham and Women's Faulkner Hospital, Boston, Massachusetts, United States

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Was a subject in the Brigham and Women's Home Hospital study and has a completed record in the study's database.

Treatment and study plan

Primary outcomes

30-Day Readmission [ yes / no ]

Time frame: From date of admission to 30-days post-discharge (31 to 54 days)

Unplanned hospital admission within 30 days of having been discharged

Sponsors and collaborators

Lead sponsor

Brigham and Women's Hospital

Other

Collaborators

Biofourmis Inc.

Registry information

Important dates

Study start: 2017
Primary completion: 2019
Study completion: 2019
First posted: Apr 19, 2021
Registry last updated: Mar 17, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Completed