Personalized Treatment for Opioid Use Disorder

40 Pages Posted: 12 Jun 2019

See all articles by Kyra Gan

Kyra Gan

Carnegie Mellon University

Alan Andrew Scheller-Wolf

Carnegie Mellon University

Sridhar R. Tayur

Carnegie Mellon University - David A. Tepper School of Business

Date Written: May 16, 2019

Abstract

In order to be cost effective, an opioid use disorder (OUD) treatment must collect and utilize information on how a patient responds to different treatment regimens. Traditional methods of evaluating patient response – urine tests and self-reports – have not been effective: the number of days that a urine test can detect drug usage is relatively small, and self-reports are subject to response bias. In contrast, wearable devices can potentially help detect patient craving episodes and health status in real-time. A variety of wearable devices with different features and costs are available; whether such devices are practical in OUD treatments, and if so how they should be used, are critical questions. We build a sequence of partially observable Markov decision processes (POMDPs) and a Markov decision process (MDP) with budget constraints to address these questions. We provide a fast solution method for the POMDP models: a novel heuristic algorithm with an analytic error bound. Using our models, we perform a numerical study to investigate the value of incorporating different wearables in OUD treatments under various scenarios of budget, wearable precision, and patient treatment adherence (TA). We find that wearables can be valuable at moderate budgets for patients with low or moderate TA. This benefit increases as the wearable accuracy increases and as we use wearables to learn patients’ personalized treatment dynamics (PTD).

Keywords: MDP, POMDP, Budget Constraint, Personalized Treatment, Opioid Addiction

Suggested Citation

Gan, Kyra and Scheller-Wolf, Alan Andrew and Tayur, Sridhar R., Personalized Treatment for Opioid Use Disorder (May 16, 2019). Available at SSRN: https://ssrn.com/abstract=3389539 or http://dx.doi.org/10.2139/ssrn.3389539

Kyra Gan (Contact Author)

Carnegie Mellon University ( email )

Pittsburgh, PA 15213-3890
United States

Alan Andrew Scheller-Wolf

Carnegie Mellon University ( email )

Pittsburgh, PA 15213-3890
United States

Sridhar R. Tayur

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States

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