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In medical research, a dynamic treatment regime (DTR), adaptive intervention, or adaptive treatment strategy is a set of rules for choosing effective treatments for individual patients.[1] Historically, medical research and the practice of medicine tended to rely on an acute care model for the treatment of all medical problems, including chronic illness.[2] Treatment choices made for a particular patient under a dynamic regime are based on that individual's characteristics and history, with the goal of optimizing his or her long-term clinical outcome. A dynamic treatment regime is analogous to a policy in the field of reinforcement learning, and analogous to a controller in control theory. While most work on dynamic treatment regimes has been done in the context of medicine, the same ideas apply to time-varying policies in other fields, such as education, marketing, and economics.

See also[edit]


  1. ^ Lei, H.; Nahum-Shani, I.; Lynch, K.; Oslin, D.; Murphy, S. A. (2012), "A "SMART" design for building individualized treatment sequences", Annual Review of Clinical Psychology, 8: 21–48, doi:10.1146/annurev-clinpsy-032511-143152, PMC 3887122Freely accessible, PMID 22224838 
  2. ^ Wagner E. H.; Austin B. T.; Davis C.; Hindmarsh M.; Schaefer J.; Bonomi A. (2001). "Improving Chronic Illness Care: Translating Evidence Into Action". Health Affairs. 20 (6): 64–78. doi:10.1377/hlthaff.20.6.64. PMID 11816692. 

Further reading[edit]


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