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Prediction of 30-Day Readmission Using Machine Learning

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ClinicalTrials.gov Identifier: NCT04849312
Recruitment Status : Not yet recruiting
First Posted : April 19, 2021
Last Update Posted : February 7, 2022
Sponsor:
Collaborator:
Biofourmis Inc.
Information provided by (Responsible Party):
David Levine, Brigham and Women's Hospital

Study Description
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Brief Summary:
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.

Condition or disease
Infection Heart Failure Chronic Obstructive Pulmonary Disease Asthma Gout Flare Chronic Kidney Diseases Hypertensive Urgency Atrial Fibrillation Rapid Anticoagulants; Increased

Study Design
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Study Type : Observational
Estimated Enrollment : 500 participants
Observational Model: Cohort
Time Perspective: Retrospective
Official Title: Prediction of 30-Day Readmission Using Machine Learning
Estimated Study Start Date : March 20, 2022
Estimated Primary Completion Date : December 1, 2022
Estimated Study Completion Date : December 1, 2022
Groups and Cohorts
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Group/Cohort
Training
A subset of patients that are used to train the machine learning algorithm.
Validation
A subset of patients that are "held back" and used to validate the algorithm's accuracy.


Outcome Measures
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Primary Outcome Measures :
  1. 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


Eligibility Criteria
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Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Subjects admitted at Brigham and Women's Hospital and Brigham and Women's Faulkner Hospital who meet primary diagnosis, age, and residence within 5 mile requirements and are enrolled in home hospital.
Criteria
Was a subject in the Brigham and Women's Home Hospital study and has a completed record in the study's database.
Contacts and Locations
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Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04849312


Contacts
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Contact: David Levine, MD MPH MA 617 732 7063 dmlevine@partners.org

Locations
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United States, Massachusetts
Brigham and Women's Hospital
Boston, Massachusetts, United States, 02115
Brigham and Women's Faulkner Hospital
Boston, Massachusetts, United States, 02130
Sponsors and Collaborators
Brigham and Women's Hospital
Biofourmis Inc.
Investigators
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Principal Investigator: David Levine, MD MPH MA Associate Physician
More Information
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Publications:

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Responsible Party: David Levine, Attending Physician, Brigham and Women's Hospital
ClinicalTrials.gov Identifier: NCT04849312    
Other Study ID Numbers: 2017P002583a
First Posted: April 19, 2021    Key Record Dates
Last Update Posted: February 7, 2022
Last Verified: February 2022
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Additional relevant MeSH terms:
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Lung Diseases, Obstructive
Pulmonary Disease, Chronic Obstructive
Kidney Diseases
Renal Insufficiency, Chronic
Atrial Fibrillation
Heart Diseases
Cardiovascular Diseases
 Arrhythmias, Cardiac
Pathologic Processes
Lung Diseases
Respiratory Tract Diseases
Urologic Diseases
Renal Insufficiency