Open AccessDynamic Treatment Regimes for Managing Chronic Health Conditions: A Statistical Perspective
Author(s) -
Bibhas Chakraborty
Publication year - 2011
Publication title -
american journal of public health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.284
H-Index - 264
eISSN - 1541-0048
pISSN - 0090-0036
DOI - 10.2105/ajph.2010.198937
Subject(s) - perspective (graphical) , intervention (counseling) , health care , intensive care medicine , computer science , research design , medicine , ideology , chronic disease , management science , risk analysis (engineering) , data science , psychology , sociology , artificial intelligence , nursing , political science , economics , social science , politics , law
Dynamic treatment regimes are an emerging and important methodological area in health research, particularly in the management of chronic health conditions. This paradigm encompasses the ideological shift in research from the acute care model to the chronic care model. It allows individualization of treatment (type, dosage, timing) at each stage of intervention. Constructing evidence-based dynamic treatment regimes requires implementation of cutting-edge design and analysis tools. Here I briefly discuss some of these modern tools, namely the sequential multiple assignment randomized trial (SMART) design and a regression-based analysis approach called Q-learning.