Two-stage stochastic programming for interdisciplinary pain management

Abstract The goal of this research is to find an optimal adaptive treatment strategy to assist physicians in prescribing treatments for patients with chronic pain. This research proposes a two-stage stochastic programming (2SP) method to optimize a treatment procedure for interdisciplinary pain management. The 2SP model incorporates non-convex nonlinear mixed integer constraints, which are constructed based on data from a real pain management program. We derive a piecewise linear approximation method to approximate the non-convex nonlinear constraints in the 2SP model. Consequently, we formulate an equivalent mixed integer linear programming (MILP) model and then solve it using a commercial mixed-integer programming solver. A comparison of the policies generated by the MILP model with the policies generated by the original nonlinear 2SP model shows that, given limited CPU time, the policies generated by the MILP model outperform those of the original nonlinear 2SP model.

[1]  R. Shults,et al.  Opioid Prescribing in the United States. , 2018, The American journal of nursing.

[2]  Jay M. Rosenberger,et al.  Handling time-varying confounding in state transition models for dynamic optimization of adaptive interdisciplinary pain management , 2018 .

[3]  K. Herr,et al.  Assessment and Measurement of Pain in Adults in Later Life. , 2016, Clinics in geriatric medicine.

[4]  D. Irnich,et al.  [Multimodal pain therapy for treatment of chronic pain syndrome. Consensus paper of the ad hoc commission on multimodal interdisciplinary pain management of the German Pain Society on treatment contents]. , 2014, Schmerz.

[5]  U. Kaiser,et al.  Multimodale Schmerztherapie für die Behandlung chronischer Schmerzsyndrome , 2014, Der Schmerz.

[6]  Donald D. McGeary,et al.  Interdisciplinary chronic pain management: past, present, and future. , 2014, The American psychologist.

[7]  R. Gatchel,et al.  A decision-making framework for adaptive pain management , 2013, Health Care Management Science.

[8]  U. Hwang,et al.  Acute pain management in older adults in the emergency department. , 2013, Clinics in geriatric medicine.

[9]  Lee S. Simon.  RELIEVING PAIN IN AMERICA: A BLUEPRINT FOR TRANSFORMING PREVENTION, CARE, EDUCATION, AND RESEARCH , 2012, Military medicine.

[10]  J. Loeser.  Relieving pain in America. , 2012, The Clinical journal of pain.

[11]  Shabbir Ahmed,et al.  Two‐Stage Stochastic Integer Programming: A Brief Introduction , 2011 .

[12]  Nico Di Domenica,et al.  A review of scenario generation methods , 2010, Int. J. Comput. Sci. Math..

[13]  María Celeste Pizarro Romero,et al.  Introduction to Stochastic Programming , 2009 .

[14]  A. Date,et al.  Acute Pain Management , 2009, The Perioperative Medicine Consult Handbook.

[15]  M. Kramer,et al.  Estimating Response-Maximized Decision Rules With Applications to Breastfeeding , 2009 .

[16]  Joelle Pineau,et al.  Constructing evidence-based treatment strategies using methods from computer science. , 2007, Drug and alcohol dependence.

[17]  Ji Zhu,et al.  Methodological Challenges in Constructing Effective Treatment Sequences for Chronic Psychiatric Disorders , 2007, Neuropsychopharmacology.

[18]  S. Murphy,et al.  An experimental design for the development of adaptive treatment strategies , 2005, Statistics in medicine.

[19]  M. Moskowitz,et al.  Mechanisms of pain modulation in chronic syndromes , 2002, Neurology.

[20]  M. Hegel,et al.  Improving Primary Care for Depression in Late Life: The Design of a Multicenter Randomized Trial , 2001, Medical care.

[21]  Elizabeth D. Dolan,et al.  NEOS Server 4.0 Administrative Guide , 2001, ArXiv.

[22]  Ree Dawson,et al.  Flexible treatment strategies in chronic disease: clinical and research implications , 2000, Biological Psychiatry.

[23]  James M. Robins,et al.  Association, Causation, And Marginal Structural Models , 1999, Synthese.

[24]  R. K. Wood,et al.  Monte Carlo bounding techniques for determining solution quality in stochastic programs , 1999, Oper. Res. Lett..

[25]  L. Sobell,et al.  Problem drinkers: evaluation of a stepped-care approach. , 1998, Journal of substance abuse.

[26]  Jorge J. Moré,et al.  The NEOS Server , 1998 .

[27]  P. Hardy.  Chronic Pain Management: The Essentials , 1997 .

[28]  William Gropp,et al.  Optimization environments and the NEOS server , 1997 .

[29]  V. Strecher,et al.  Do tailored behavior change messages enhance the effectiveness of health risk appraisal? Results from a randomized trial. , 1996, Health education research.

[30]  John R. Satterthwaite,et al.  Handbook of Pain Management , 1994 .

[31]  B. T. Engel,et al.  A controlled study of a standardized behavioral stepped treatment for hypertension. , 1989, Psychosomatic medicine.

[32]  G. McCormick.  Nonlinear Programming: Theory, Algorithms and Applications , 1983 .

[33]  C. R. Sage,et al.  MATHEMATICS AND COMPUTER SCIENCE DIVISION. , 1967 .

[34]  Benjamin Pfaff,et al.  Pain Management An Interdisciplinary Approach , 2016 .

[35]  Jay M. Rosenberger,et al.  Outcome And State Transition Modeling For Adaptive Interdisciplinary Pain Management , 2013 .

[36]  Xiaomei Zhu,et al.  Two-Stage Stochastic Mixed-Integer Programs: Algorithms and Insights , 2009 .

[37]  Alexander Shapiro,et al.  A Tutorial on Stochastic Programming , 2007 .

[38]  Sovan Mitra.  A White Paper on Scenario Generation for Stochastic Programming , 2006 .

[39]  Susan A. Murphy,et al.  Adaptive Treatment Strategies: an Emerging Approach for Improving Treatment Effectiveness , 2003 .

[40]  R. Brooner,et al.  U Using Behavioral Reinforcement To Improve Methadone Treatment Participation , 2002 .

[41]  R J Little,et al.  Causal effects in clinical and epidemiological studies via potential outcomes: concepts and analytical approaches. , 2000, Annual review of public health.

[42]  Christine A. Shoemaker,et al.  Applying Experimental Design and Regression Splines to High-Dimensional Continuous-State Stochastic Dynamic Programming , 1999, Oper. Res..

[43]  Larry E. Toothaker,et al.  Multiple Regression: Testing and Interpreting Interactions , 1991 .

[44]  D. A. Kenny,et al.  The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. , 1986, Journal of personality and social psychology.

[45]  F. G. Hannington-Kiff.  The mechanisms of pain. , 1979, Nursing.