Application of machine learning methodology to assess the performance of DIABETIMSS program for patients with type 2 diabetes in family medicine clinics in Mexico.

Journal: BMC medical informatics and decision making
PMID: 31718638

Abstract

BACKGROUND: The study aimed to assess the performance of a multidisciplinary-team diabetes care program called DIABETIMSS on glycemic control of type 2 diabetes (T2D) patients, by using available observational patient data and machine-learning-based targeted learning methods.

Authors

  • Yue You
    Pennsylvania State University, University Park, PA, USA.
  • Svetlana V Doubova
    Epidemiology and Health Services Research Unit, CMN Siglo XXI, Mexican Institute of Social Security, Av. Cuauhtemoc 330, Col. Doctores, Mexico City, Mexico. svetlana.doubova@gmail.com.
  • Diana Pinto-Masis
    Interamerican Development Bank, 1300 New York Ave NW, Washington DC, 20577E, USA.
  • Ricardo Pérez-Cuevas
    Interamerican Development Bank, 6 Montrose Road, Kingston 6, Jamaica.
  • Víctor Hugo Borja-Aburto
    Direccion de Prestaciones Medicas, Instituto Mexicano del Seguro Social, Mexico City, Mexico.
  • Alan Hubbard
    Division of Biostatistics, University of California, Berkeley, California, United States of America.

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