Maximizing the Value of Mobile Health Monitoring by Avoiding Redundant Patient Reports: Prediction of Depression-Related Symptoms and Adherence Problems in Automated Health Assessment Services
Maximizing the Value of Mobile Health Monitoring by Avoiding Redundant Patient Reports: Prediction of Depression-Related Symptoms and Adherence Problems in Automated Health Assessment Services
John D Piette
1
, PhD, ScM ;
Jeremy B Sussman
1
, MD ;
Paul N Pfeiffer
2
, MD ;
Maria J Silveira
1
, MD ;
Satinder Singh
3
, PhD ;
Mariel S Lavieri
4
, PhD
1
VA Center for Clinical Management Research and Division of General Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States
2
VA Center for Clinical Management Research and Department of Psychiatry, Ann Arbor VA Healthcare System and University of Michigan, Ann Arbor, MI, United States
3
Artificial Intelligence Laboratory, Department of Electrical Engineering and Computer Science, College of Engineering, University of Michigan, Ann Arbor, MI, United States
4
Deparment of Industrial and Operations Engineering, College of Engineering, University of Michigan, Ann Arbor, MI, United States
Corresponding Author:
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John D Piette, PhD, ScM
-
VA Center for Clinical Management Research and Division of General Medicine
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Department of Internal Medicine
-
University of Michigan
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PO Box 130170
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Ann Arbor, MI, 48113-0170
-
United States
-
Phone:
1 734-936-4787
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Fax: 1 734-936-8944
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Email: jpiette@umich.edu