Development of Machine Learning Algorithms for Prediction of Sustained Postoperative Opioid Prescriptions After Total Hip Arthroplasty.

Journal: The Journal of arthroplasty

Published Date: Oct 1, 2019

Abstract

BACKGROUND: Postoperative recovery after total hip arthroplasty (THA) can lead to the development of prolonged opioid use but there are few tools for predicting this adverse outcome. The purpose of this study is to develop machine learning algorithms for preoperative prediction of prolonged opioid prescriptions after THA.

Authors

Aditya V Karhade

Computational Neurosciences Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Joseph H Schwab

Department of Orthopedic Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA. Electronic address: jhschwab@mgh.harvard.edu.
Hany S Bedair

Department of Orthopedic Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA.

Keywords

Aged Algorithms Analgesics, Opioid Arthroplasty, Replacement, Hip Female Humans Logistic Models Machine Learning Male Middle Aged Opioid-Related Disorders Pain, Postoperative Postoperative Period Prescriptions Retrospective Studies Risk Assessment

External Resources

View on PubMed Access via DOI PubMed (31327647)

Development of Machine Learning Algorithms for Prediction of Sustained Postoperative Opioid Prescriptions After Total Hip Arthroplasty.

Abstract

Authors

Keywords

External Resources

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