A Novel Method for Assessing Risk-Adjusted Diagnostic Coding Specificity for Depression Using a U.S. Cohort of over One Million Patients.

Autor: Glass A; School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA., Melton NC; Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA., Moore C; School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA., Myrick K; Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA., Thao K; School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA., Mogaji S; School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA., Howell A; School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA., Patton K; School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA., Martin J; ITS Data Science, Premier, Inc., Charlotte, NC 28277, USA., Korvink M; ITS Data Science, Premier, Inc., Charlotte, NC 28277, USA., Gunn LH; School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA.; Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA.; School of Public Health, Faculty of Medicine, Imperial College London, London W6 8RP, UK.

Publikováno v: Diagnostics (Basel, Switzerland) [Diagnostics (Basel)] 2024 Feb 15; Vol. 14 (4). Date of Electronic Publication: 2024 Feb 15.