Prediction of 30-Day Readmission Using Machine Learning
NCT ID: NCT04849312
Last Updated: 2022-02-07
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
500 participants
OBSERVATIONAL
2022-03-20
2022-12-01
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
RETROSPECTIVE
Study Groups
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Training
A subset of patients that are used to train the machine learning algorithm.
No interventions assigned to this group
Validation
A subset of patients that are "held back" and used to validate the algorithm's accuracy.
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
18 Years
ALL
No
Sponsors
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Biofourmis Inc.
INDUSTRY
Brigham and Women's Hospital
OTHER
Responsible Party
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David Levine
Attending Physician
Principal Investigators
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David Levine, MD MPH MA
Role: PRINCIPAL_INVESTIGATOR
Associate Physician
Locations
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Brigham and Women's Hospital
Boston, Massachusetts, United States
Brigham and Women's Faulkner Hospital
Boston, Massachusetts, United States
Countries
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Central Contacts
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References
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Merrill RK, Ferrandino RM, Hoffman R, Shaffer GW, Ndu A. Machine Learning Accurately Predicts Short-Term Outcomes Following Open Reduction and Internal Fixation of Ankle Fractures. J Foot Ankle Surg. 2019 May;58(3):410-416. doi: 10.1053/j.jfas.2018.09.004. Epub 2019 Feb 23.
Li Q, Yao X, Echevin D. How Good Is Machine Learning in Predicting All-Cause 30-Day Hospital Readmission? Evidence From Administrative Data. Value Health. 2020 Oct;23(10):1307-1315. doi: 10.1016/j.jval.2020.06.009. Epub 2020 Sep 7.
Xue Y, Klabjan D, Luo Y. Predicting ICU readmission using grouped physiological and medication trends. Artif Intell Med. 2019 Apr;95:27-37. doi: 10.1016/j.artmed.2018.08.004. Epub 2018 Sep 10.
Morel D, Yu KC, Liu-Ferrara A, Caceres-Suriel AJ, Kurtz SG, Tabak YP. Predicting hospital readmission in patients with mental or substance use disorders: A machine learning approach. Int J Med Inform. 2020 Jul;139:104136. doi: 10.1016/j.ijmedinf.2020.104136. Epub 2020 Apr 18.
Loreto M, Lisboa T, Moreira VP. Early prediction of ICU readmissions using classification algorithms. Comput Biol Med. 2020 Mar;118:103636. doi: 10.1016/j.compbiomed.2020.103636. Epub 2020 Feb 1.
Bolourani S, Tayebi MA, Diao L, Wang P, Patel V, Manetta F, Lee PC. Using machine learning to predict early readmission following esophagectomy. J Thorac Cardiovasc Surg. 2021 Jun;161(6):1926-1939.e8. doi: 10.1016/j.jtcvs.2020.04.172. Epub 2020 May 29.
Arvind V, London DA, Cirino C, Keswani A, Cagle PJ. Comparison of machine learning techniques to predict unplanned readmission following total shoulder arthroplasty. J Shoulder Elbow Surg. 2021 Feb;30(2):e50-e59. doi: 10.1016/j.jse.2020.05.013. Epub 2020 Jun 9.
Other Identifiers
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2017P002583a
Identifier Type: -
Identifier Source: org_study_id
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