Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44165, first published .
An Automatically Adaptive Digital Health Intervention to Decrease Opioid-Related Risk While Conserving Counselor Time: Quantitative Analysis of Treatment Decisions Based on Artificial Intelligence and Patient-Reported Risk Measures

An Automatically Adaptive Digital Health Intervention to Decrease Opioid-Related Risk While Conserving Counselor Time: Quantitative Analysis of Treatment Decisions Based on Artificial Intelligence and Patient-Reported Risk Measures

An Automatically Adaptive Digital Health Intervention to Decrease Opioid-Related Risk While Conserving Counselor Time: Quantitative Analysis of Treatment Decisions Based on Artificial Intelligence and Patient-Reported Risk Measures

John D Piette   1, 2 , MSc, PhD ;   Laura Thomas   1, 3 , MPH, LMSW ;   Sean Newman   1, 2 , MS ;   Nicolle Marinec   1, 2 , MPH ;   Joel Krauss   4 , MD ;   Jenny Chen   1, 2 , MPH ;   Zhenke Wu   5 , PhD ;   Amy S B Bohnert   1, 3 , PhD

1 Ann Arbor Department of Veterans Affairs Center for Clinical Management Research, Ann Arbor, MI, United States

2 Department of Health Behavior Health Education, School of Public Health, University of Michigan, Ann Arbor, MI, United States

3 Department of Anesthesiology, School of Medicine, University of Michigan, Ann Arbor, MI, United States

4 Department of Emergency Medicine, Trinity Health St. Joseph Mercy, Ann Arbor, MI, United States

5 Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States

Corresponding Author:

  • John D Piette, MSc, PhD
  • Ann Arbor Department of Veterans Affairs Center for Clinical Management Research
  • 2215 Fuller Road, Mail Stop 152
  • Ann Arbor, MI, 48105
  • United States
  • Phone: 1 734 223 0127
  • Email: jpiette@umich.edu