Prediction of Expected Length of Hospital Stay Using Machine Learning

March 16, 2026 updated by: David Levine, Brigham and Women's Hospital
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 length of stay throughout a patient's admission. This algorithm was then validated in a validation cohort.

Study Overview

Status

Withdrawn

Conditions

Study Type

Observational

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • United States
    • Massachusetts
      • Boston, Massachusetts, United States, 02115
        • Brigham and Women's Hospital
      • Boston, Massachusetts, United States, 02130
        • Brigham and Women's Faulkner Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

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.

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Length of Stay
Time Frame: From date of admission to date of discharge (1 to 24 days)
The time spent by each patient in Home Hospital from time of admission to time of discharge, measured in hours
From date of admission to date of discharge (1 to 24 days)

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Brigham and Women's Hospital

Collaborators

Biofourmis Inc.

Investigators

  • Principal Investigator: David Levine, MD MPH MA, Associate Physician

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

March 20, 2021

Primary Completion (Estimated)

August 1, 2026

Study Completion (Estimated)

December 1, 2026

Study Registration Dates

First Submitted

March 2, 2021

First Submitted That Met QC Criteria

March 2, 2021

First Posted (Actual)

March 5, 2021

Study Record Updates

Last Update Posted (Actual)

March 17, 2026

Last Update Submitted That Met QC Criteria

March 16, 2026

Last Verified

March 1, 2026

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2017P002583b

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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