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Development and Validation of a Machine Learning Algorithm After Primary Total Hip Arthroplasty: Applications to Length of Stay and Payment Models.

著者 Ramkumar PN , Navarro SM , Haeberle HS , Karnuta JM , Mont MA , Iannotti JP , Patterson BM , Krebs VE
J Arthroplasty.2018 Dec 27 ; ():.
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Value-based payment programs in orthopedics, specifically primary total hip arthroplasty (THA), present opportunities to apply forecasting machine learning techniques to adjust payment models to a specific patient or population. The objective of this study is to (1) develop and validate a machine learning algorithm using preoperative big data to predict length of stay (LOS) and patient-specific inpatient payments after primary THA and (2) propose a risk-adjusted patient-specific payment model (PSPM) that considers patient comorbidity.
PMID: 30665831 [PubMed - as supplied by publisher]
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